Projection-based stereolithography for direct 3D printing of heterogeneous ultrasound phantoms.

Modern ultrasound (US) imaging is increasing its clinical impact, particularly with the introduction of US-based quantitative imaging biomarkers. Continued development and validation of such novel imaging approaches requires imaging phantoms that recapitulate the underlying anatomy and pathology of interest. However, current US phantom designs are generally too simplistic to emulate the structure and variability of the human body. Therefore, there is a need to create a platform that is capable of generating well-characterized phantoms that can mimic the basic anatomical, functional, and mechanical properties of native tissues and pathologies. Using a 3D-printing technique based on stereolithography, we fabricated US phantoms using soft materials in a single fabrication session, without the need for material casting or back-filling. With this technique, we induced variable levels of stable US backscatter in our printed materials in anatomically relevant 3D patterns. Additionally, we controlled phantom stiffness from 7 to >120 kPa at the voxel level to generate isotropic and anisotropic phantoms for elasticity imaging. Lastly, we demonstrated the fabrication of channels with diameters as small as 60 micrometers and with complex geometry (e.g., tortuosity) capable of supporting blood-mimicking fluid flow. Collectively, these results show that projection-based stereolithography allows for customizable fabrication of complex US phantoms.

Introduction

Ultrasound (US) imaging has long been a valuable tool for medical diagnostics due to its non-invasive nature, high resolution, dynamic-imaging capabilities, and its capacity to assess tissue properties beyond simple anatomy (e.g., blood flow or tissue stiffness) [1]. In addition to traditional anatomy-based US applications, the use of US-based quantitative imaging biomarkers (QIB)–such as assessing volume blood flow (VBF), tissue perfusion with contrast-enhanced US (CEUS), or shear wave speed (SWS) elasticity imaging–offers tremendous potential in providing more effective, patient-specific, rational clinical care [2, 3]. However, translating QIB methods from research tools to clinical practice has proven challenging, in large part because the imaging phantoms needed to support robust quality assurance (QA) programs for these modalities are often insufficient. Given the strong dependence of QIBs on the specific functional (e.g., blood flow) and anatomical (e.g., vessel topology) aspects of an interrogated biological system, current imaging phantoms often do not adequately simulate the wide range of structural complexities and biological variation inherent in a human subject due to their overly “simplistic design.” This leads to overestimated measurements for precision, particularly reproducibility, and inaccurate assessment of bias [4-7]. Studies have noted that many physiological (e.g., vessel permeability) and anatomical (e.g., vessel scale and dimensionality) characteristics are not accurately replicated in current imaging phantoms [8, 9]. The RSNA QIB Alliance (QIBA) Metrology Working Group recently warned that “phantoms do not represent the complexity of human targets; thus, precision is often overestimated” [10]. Consequently, they claimed that “improved realism of phantoms [is an] area worthy of further investment” [10]. To this end, an improved phantom platform is critical for validation and optimization of more established US-based QIB methods (e.g., VBF, CEUS, & SWS), while such a platform would also be of tremendous value in the development of newer QIB approaches, such as super-resolution imaging, acoustic angiography, or photoacoustic-US oxygen saturation imaging. To meet these needs, the next-generation imaging phantom platform should be capable of capturing the scale, tortuosity, density, and functionality of vasculature and of emulating the tissue backscatter heterogeneity, viscoelasticity, and anisotropy that is characteristic of human biology.

Although homogeneous tissue-mimicking phantoms made of hydrogels, rubbers, and other tissue-mimicking materials are widely available, both commercially (e.g., CIRS, Nuclemed, True Phantom) and otherwise, most provide only gross, organ-level anatomy- and physiology-mimicking properties [11-15]. While such tissue-mimicking extent is generally sufficient for routine imaging and system QA testing, these phantoms ultimately lack the heterogeneity and functional aspects (e.g., realistic blood flow) ideal for use with US-based QIB imaging. For instance, phantoms for Doppler imaging and elasticity imaging should include flow-supporting channels and regions of varying stiffness, respectively. Unfortunately, there currently exist limitations in fabricating realistic and well-characterized phantoms with the degree of spatial control necessary to make such voxel-specific changes in desired phantom properties.

To address the traditionally limited geometric complexity in phantoms, researchers have investigated tissue-mimicking phantoms via additions of materials such as tube-like structures and inclusions of varying backscatter and/or stiffness to homogeneous tissue-mimicking phantom bases. However, such processes are generally time and labor intensive (i.e., require multiple casting sessions), are generally compatible with only basic geometries, and often introduce imperfections (e.g., air, other unintended materials) that generate imaging artifacts [16-20]. Similar methodology has been used to create tissue-containing phantoms that are anatomically realistic at both macro- and micro-scales but whose use is generally limited owing to their relative lack of characterization compared with wholly fabricated phantoms [21, 22].

Three-dimensional (3D) printing can address many of these fabrication challenges by giving researchers control over every voxel within the print volume [22]. Indeed, multiple groups have used 3D printing to develop custom molds for generating US phantoms that mimic patient anatomy. As an example, fused deposition modeling (FDM) has been used to fabricate plastic molds for casting US phantoms of the thyroid [23], a fluid-flow phantom [24], and phantoms with bone-like inclusions to mimic the spine [25] and rib cage [26]. This process can also be used to create molds of individual tissue-mimicking components with varying levels of backscatter, which are then combined to produce US phantoms mimicking whole organs, such as the human heart or placenta [27]; however, these processes inherently require significant time and effort while limiting the ultimate phantom complexity (i.e., variation in sub-voxel structural, acoustic, and stiffness properties) that is reasonably achievable.

The recent expansion of 3D printing techniques beyond plastic-based FDM has enabled researchers to fabricate phantoms directly from soft materials. For example, commercially available inkjet-based printing systems have been used to directly fabricate silicone-based models of abdominal aortas for inclusion in US phantoms. Although promising, these phantoms were orders of magnitude stiffer than typical soft tissue, with storage moduli on the order of 1 MPa [28]. Other groups have used inkjet technology to generate regions of binary hyperechogenicity at the imaging voxel level; however, the need for a support material during the fabrication process ultimately limits control over the phantoms’ contrast and spatial resolution [29, 30]. Additionally, several tested materials do not provide adequate US image quality to qualify as potential tissue-mimicking phantoms [31, 32]. Therefore, challenges remain with respect to 3D printing phantoms using soft materials with varying levels of backscatter or stiffness in a single fabrication session.

To improve the quality and ease of fabrication of phantoms for a wide range of US-mediated imaging modalities, we used projection-based stereolithography (pSLA) to fabricate phantoms containing voxel-specific US backscatter, direct-printed targets for elasticity imaging, and with open-channel networks for high-resolution Doppler imaging. We previously used a pSLA technique developed to print binary structures using poly(ethylene glycol) (PEG)-based hydrogels [33]. While this class of hydrogel has been shown to generate material with US properties (i.e., speed of sound, attenuation) generally in the range of human tissues [34], this previous work did not explore formulations and fabrications designed exclusively for the purpose of making the specimen amenable for high-quality, clinical US imaging. In this work, we incorporated an additional functionality into our existing 3D-printing technique to vary the levels of light exposure within each printed layer and voxel, thereby permitting fine spatial control of US backscatter and stiffness. Our semi-automated approach can print at rates of up to 3 cm (in the Z axis) per hour, permitting the timely production of fully customized and cured imaging phantoms. Ultimately, our method provides researchers with the ability to develop phantoms with customized backscatter and elasticity values as well as with complex vasculature such that they may be made sufficiently realistic and detailed to generally mimic tissue for further development and validation of functional and QIB US imaging techniques.

Materials and methods

Hydrogel materials and synthesis

PEG diacrylate (PEGDA) of molecular weight (MW) of 6 or 35 kDa was synthesized, as described previously [35]. Briefly, PEG of the desired MW was reacted with triethylamine and acryloyl chloride in dichloromethane under anhydrous conditions with argon overnight. Lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) was prepared, as described previously [36]. Briefly, dimethyl phenylphosphinite was reacted with 2,3,6-trimethylbenzoyl chloride under argon overnight at room temperature. A 4-molar excess lithium bromide in 2-butanone was added to the mixture, which was then heated to 50°C to allow the formation of a solid precipitate. The mixture was cooled to room temperature for 4 hours and then filtered with excess 2-butanone and diethyl ether. For phantom samples used in the stability experiment, a gelatin methacrylate (GelMA) additive was synthesized, as described previously [33]. PEGDA and GelMA macromers were dissolved in phosphate-buffered saline (PBS) to make pre-polymer solutions. Using 1H NMR [35], percent acrylation of PEGDA was determined to be 99%, and yields generally ranged from 80–90% for batch sizes of up to 350 g. For LAP preparation, yields of up to 90% were achieved for batch sizes of up to 30 g.

Design and fabrication of phantoms

US phantoms were fabricated using a pSLA system, as described previously [33]. Briefly, this 3D printing system consisted of a Z-stage print platform opposing a transparent PEGDA resin basin coated with Polydimethylsiloxane (PDMS) to avoid PEGDA adhesion and a PRO4500 optical engine emitting a 405-nm ultraviolet light (Wintech Digital Systems Technology Corp., Carlsbad, CA), achieving a nominal 50-μm print resolution, and allowing a maximal print volume (X/Y/Z) of 50x40x65 mm. Note that Phantom 15, which contained small channels capable of supporting flow, was fabricated with a higher-resolution pSLA system that used a PRO6500 optical engine (Wintech Digital Systems Technology Corp.) that can achieve a nominal 10-μm print resolution. Phantoms were fabricated layer by layer (Fig 1) from a liquid pre-polymer solution that solidified upon exposure to light. During the 3D printing process, light absorption and scattering through the layers caused an exposure gradient, and therefore a gradient in PEGDA photocuring, which manifested as a discontinuity of local crosslinking density at layer boundaries (Fig 1C) [37]. This crosslinking discontinuity consequently results in a mass density discontinuity (i.e., acoustic impedance mismatch), generating varied levels of US backscatter. Additionally, as elasticity and crosslinking density are directly linked, this printing method provides a mechanism for creation of tunable elasticity phantoms based on differing photocuring times.

Fig 1

3D printing of phantoms.

A CAD model was translated into (A) the desired phantom. (B) PEGDA material was extruded in layers of set thicknesses and (C) photocured with ultraviolet light (purple) from the bottom. (D) Inclusions were incorporated within the PEGDA material by spatially varying light exposure time. (E) Subsequent layers were then extruded and photocured using the same technique until (F) the physical phantom was fabricated.

The desired geometries of the US phantoms were designed using SolidWorks (Dassault Systems, Velizy-Villacoublay, France) to generate computer-aided design (CAD) models for each test sample. The printer control software, Creation Workshop (EnvisionTEC, Inc., Dearborn, MI), was used to slice 3D models into layers and generate the machine code (G-code) to control the position of the Z-platform. All hydrogels were fabricated using a pre-polymer solution containing varying concentrations of PEGDA as a base, tartrazine as a photoabsorber, and with 34 mM LAP as a photoinitiator (17 mM LAP for the GelMA formulation). The concentration of PEGDA was modified to impart different mechanical properties to the resulting hydrogels, and the concentration of tartrazine was modified depending on the thickness of the print layers. Inclusion of GelMA was investigated given its demonstrated impact on the swelling and stability behavior of constructs when mixed with PEGDA [38]. Finally, the per-layer exposure time was also modified depending on the PEGDA concentration and layer thickness. Printing parameters for each phantom are outlined in Table 1. Gels were stored in either deionized (DI) water or PBS prior to imaging. This rehydration process also flushed any unreacted solution from vessel lumen and washed the phantom of tartrazine to provide transparent media.

Table 1

Description of hydrogel formulations, additives and print parameters for phantoms.

	Phantom Description	Figure	Layer (μm)	PEGDA Formulation	Additives	Tartrazine (mM)	Cure Time (sec)	Print Time (min)
1	200-μm Layer	2, 3, S2	200	20 wt% 6 kDa	None	1.4	4	5
2	50-μm Layer	2, 3, S2	50	20 wt% 6 kDa	None	2.15	8.5	35
3	200-μm Optical	2, 3	200	20 wt% 6 kDa	1.0 mg/mL FITC-Dextran (150 kDa)	1.4	4	5
4	50-μm Optical	2, 3	50	20 wt% 6 kDa	1.0 mg/mL FITC-Dextran (150 kDa)	2.15	8.5	35
5	Additive-free Contrast	2, 3, 4	50	20 wt% 6 kDa	None	2.15	9.5 (Base)1	24
6	Xanthan Contrast	2, S5	50	20 wt% 6 kDa	0.833 mg/mL Xanthan Gum	2.15	9.5 (Base)1	24
7	Xanthan and Low Silica Contrast	2, 4, S5	50	20 wt% 6 kDa	0.1 mg/mL Silica & 0.833 mg/mL Xanthan Gum	2.15	9.5 (Base)1	24
8	Xanthan and High Silica	S5	50	20 wt% 6 kDa	1.0 mg/mL Silica & 0.833 mg/mL Xanthan Gum	2.15	9.5	24
9	Speed of Sound	2	100	20 wt% 6 kDa	None	2.25	11	35
10	PEGDA Stability	2	100	20 wt% 6 kDa	None	2.25	11	11
11	PEGDA-GelMA Stability	2	50	3.25% 3.4 kDa	10% GelMA & 10% glycerol	2.25	8	17
12	Compliant Elasticity	2	50	20 wt% 1:3 6:35 kDa	None	2.15	5 (Base)2	36
13	Stiff Elasticity	2	50	20 wt% 6 kDa	None	2.15	8 (Base)3	54
14	Anisotropic Elasticity	2, S1, S3	50	20 wt% 1:3 6:35 kDa	None	2.15	5 (Base) 7.5 (Stripes)	28
15	Small-Channel Flow	5	50	20 wt% 6 kDa	None	2.81	12.5	15
16	Serpentine Flow	5, S4	50	80 wt% 1:1 6:35 kDa	None	2.15	3.5	6
17	Tumor Flow	6	50	80 wt% 1:1 6:35 kDa	0.1 mg/mL Silica 0.833 mg/mL Xanthan Gum	2.15	6 (Base) 2 (Tumor)	25

1. Additional targets were printed with 7 cure times (10, 10.5, 12, 14.5, 19.5, 24.5, & 39.5 total seconds) within the phantom.

2. Additional targets were printed with 3 cure times (7.5, 10, & 12.5 total seconds).

3. Additional targets were printed with 3 cure times (12, 17, & 20 total seconds).

Local US backscatter was generated through voxel-level (acoustic) impedance mismatches at print-layer boundaries. It is important to note that most of the printed backscatter results from specular scattering, as adjacent print voxels were generally photocured to present with the same impedance mismatch. But because adjacent 50-μm print voxels (i.e., below the typical resolution for clinical US) can be made to have varied mismatches (e.g., the anisotropic elasticity phantom), it is possible to generate diffuse scattering. However, the print voxels’ relative size and regular periodicity severely limit their ability to generate fully developed speckle, which requires highly dense acoustic scatterers of random phase/amplitude within an imaging voxel. Therefore, we fabricated multiple phantoms (Phantoms 7 and 17) with 0.1 mg/mL of 40-μm diameter silica particles (MIN-U-SIL-40, U.S. Silica Co., Mill Creek, OK) and one phantom (Phantom 8) with 1.0 mg/mL of silica particles to provide US speckle more typical of soft tissue, as has been demonstrated in previous work of conventional gelatin-based phantoms [12].

US imaging setup

All imaging studies–except for those involving elasticity imaging–were conducted on a Vevo 2100 US system (FUJIFILM VisualSonics Inc., Toronto, Canada) using MS200 (9–18 MHz bandwidth), MS400 (18–38 MHz), or MS700 (30–70 MHz) linear array transducers. This system has a built-in stepper motor to translate the transducer in the elevation dimension to acquire 3D imaging data. Beamformed imaging data were then exported into MATLAB (Mathworks, Natick, MA) for analysis and visualization. US elasticity imaging was performed on a Vantage 128 system (Verasonics, Inc., Kirkland, WA) using an L11-4v (4.5–11 MHz) linear array transducer. For all imaging studies, the printed phantom was secured to a gelatin (8 wt%) base using cyanoacrylate glue to mitigate reverberation artifacts at the distal edge. The phantom was then coupled to the transducer via a PBS or deionized (DI) water bath, except for Doppler imaging studies, in which US gel was used for coupling.

Assessment of US properties and stability

To investigate the US properties of the printed phantoms, we acquired volumetric B-mode US data of phantoms with different print-layer thicknesses (Phantoms 1,2; Fig 2A) using 12 (MS200), 30 (MS400), & 50 (MS700) MHz center frequencies. In addition, optically translucent phantoms were fabricated with 1 mg/mL of 150 kDa fluorescein isothiocyanate (FITC)−dextran (MilliporeSigma, Burlington, MA), an agent known to photobleach rapidly, added to the print solution (Phantoms 3,4). These phantoms were imaged with fluorescence microscopy using a TE Eclipse epifluorescence microscope (Nikon Instruments Inc., Melville, NY) for comparison with acquired US images.

Fig 2

Imaging phantom schematics.

(A) Layer thickness phantom (Phantoms 1–4). (B) Contrast phantoms with printed inclusions of different sizes and photocuring times (Phantoms 5–7). (C) Speed of sound phantom (Phantom 9). (D) Temporal stability phantom (Phantoms 10,11). (E) Elasticity phantom with three inclusions of increased photocuring time (Phantoms 12,13). (F) Anisotropic elasticity phantom with columns printed in a checkerboard pattern in the X-Z plane (Phantom 14). (G) Serpentine flow phantom (Phantom 16). (H) Tumor flow phantom with a vascular-mimicking branched channel and a tumor-mimicking inclusion in the center (Phantom 17). Note that ∅ denotes object diameter.

To further characterize US signals generated within the phantoms, B-mode volumetric imaging was performed with the aforementioned transducers/frequencies to assess all 7 levels of varied photocuring time within the contrast phantoms (Phantoms 5–7; Fig 2B), which consisted of rectangular patterns within the X-Y plane. A custom Python script was developed to alter the order of G-code so that certain shapes of selected layers received a secondary light exposure before proceeding to the next Z-position (S1 Fig). Xanthan gum, a common food additive, was added in some phantoms to prevent silica particles from settling during the printing process. B-mode images (30 MHz; MS400) of Phantoms 6–8 were qualitatively assessed to visualize the difference in scatterer distribution across multiple silica concentrations. In addition, because PEGDA degrades via hydrolysis, we assessed the temporal stability of the US signal from the printed targets (i.e., regions with additional cure time) and the base hydrogel (i.e., the region with no additional cure time) over 6 weeks. Matched acquisitions were performed 1, 3, & 6 weeks after baseline imaging following fabrication to assess imaging temporal stability. All imaging parameters (e.g., gain, transmit power, TGC, dynamic range, and position within the field of view) remained constant across imaging sessions. Signal and contrast-to-noise ratio (CNR) were analyzed from the B-Mode US data across five slices in each printed target for all 4 time-points via the establishment of regions of interest (ROIs) within each printed target and matched ROIs in the base hydrogel region. Signal was reported as the mean within the ROI, whereas CNR was defined as [39]. where μ is the mean B-mode signal within the printed-target ROI, μ is the mean signal within an ROI outside of the printed target, σ is the standard deviation of the signal within the printed-target ROI, and σ is the standard deviation within the ROI outside the printed target. Using this method, we compared matched ROIs in the printed target and a region of equal area in the phantom background at equal depth.

To assess print stability and fidelity, rectangular phantoms with a 1mm-inner-diameter linear lumen (Phantoms 10,11; Fig 2D) were printed and immediately stored in DI water or PBS at 4 or 25°C. In addition to a standard PEGDA formulation (Phantom 10), a second PEGDA formulation containing GelMA (Phantom 11) was also tested. B-mode volumetric imaging (30 MHz; MS400) was performed on matched pairs (i.e., duplicate phantoms) of each formulation stored at each temperature, with the phantom lumen positioned perpendicular to the transducer axis for four time-points: 0 (i.e., immediately after printing), 1, 2, & 4 weeks following printing. For each time-point, three imaging slices separated by 3–4 mm were chosen, and the midsection extent in the Y- and Z-axis of the rectangular phantom’s walls and lumen was measured using digital calipers in the VevoLAB analysis package (FUJIFILM VisualSonics, Toronto, ON, Canada). Precision was assessed by the standard deviation of measurements for a constant geometric feature (e.g., lumen) across three locations for the same phantom; reproducibility was assessed by comparing the percent difference in geometric features between two matched phantoms; stability was assessed by tracking the change in geometric features for a given phantom over time; and accuracy (i.e., print fidelity) was assessed by comparing the dimensions of printed GelMA-containing phantoms to their CAD dimensions.

To assess the speed of sound through phantom samples at US frequencies, a uniform rectangular phantom with no inclusions (Phantom 9; Fig 2C) was placed on a stainless-steel plate and secured with a Saran plastic wrap (S. C. Johnson & Son, Inc., Racine, WI) strip (i.e., the width of the phantom) overtop. The plate was then put in an UMS Research US measurement water tank containing a 2-axis translation stage with transducer holder (Precision Acoustics Ltd., Dorchester, England); the tank was filled with degassed DI water at a temperature of 20.0 ⁰C. Using a UT320 pulser-receiver (UTEX Scientific Instruments Inc., Mississauga, Ontario, Canada) connected to a DSOX3024A oscilloscope (Keysight Technologies, Santa Rosa, CA), an US pulse was transmitted and received via an unfocused, circle transducer positioned 25 mm above a region of the plate not containing the phantom. The transducer was then translated laterally to five regions (separated by ~3 mm) overhead the phantom sample, and the pulse-echo scheme was repeated at each. Speed of sound through the sample was then determined using the pulse-echo substitution method [11]. The following unfocused, circle immersion transducers (UTX, Inc., Holmes, NY) were used with these center frequencies (MHz), element diameters (in.), & -6dB bandwidth (%): 2.25, 0.5, & 85; 5.0, 0.5, & 73; 10.0, 0.375, & 91.

Elasticity imaging

To create elasticity imaging phantoms, two different PEGDA formulations with printed 5-mm spherical inclusions (Fig 2E) were used: one (Phantom 12) with a base cure time of 5 seconds containing three printed spherical targets with total cure times of 7.5, 10, & 12.5 seconds and one (Phantom 13) with a base cure time of 8 seconds with 3 targets exposed for 12, 16, or 20 seconds. Imaging and analysis code was adapted from Deng et al. for acquisition [40]. Briefly, an acoustic radiation force impulse excitation “push” of 900 cycles at a 6.25-MHz center frequency was focused at a 20-mm depth within the phantom, 5-mm laterally from each target (Fig 2E), to generate a shear wave that was then tracked with pulse-echo US to determine local SWS of the material. Shear wave velocity through the phantom background and the inclusions was measured [39, 41] to obtain Young’s modulus estimates assuming a linear, isotropic, elastic medium. Each phantom was imaged 10 times for statistical analysis.

We fabricated a third elasticity imaging phantom (Phantom 14) to demonstrate transverse anisotropy of shear wave propagation. While the background of the phantom was cured for 5 seconds, columns running throughout the phantom in a checkerboard fashion were cured for a total time of 7.5 seconds (Fig 2F). The phantom was then placed on a rotating base to allow for image acquisitions at 0°, 45°, & 90° angular positions. Shear wave imaging was performed in the same manner as described previously, beginning with the transducer’s long axis oriented parallel to the axis of the printed column targets (i.e., 0°; Fig 2F). The phantom was then rotated to create a 45° angle between the column targets and the transducer and then a 90° angle (i.e., transducer’s long axis perpendicular to the column targets), and shear wave imaging was performed 10 times at each angular position.

3D flow imaging

Doppler imaging was used to assess the printing technique’s ability to generate flow-supporting channels (Phantom 15). To this end, we infused 3-μm polystyrene beads (Magsphere Inc., Pasadena, CA) diluted at a ratio of 1:15 in 25% glycerol solution as flow imaging targets [42]. This suspension was then infused into the phantom using a syringe pump (New Era Pump Systems, Inc., Farmingdale, NY) at flow rates of 100, 25, 25, & 10 μL/min for CAD-based lumen diameters of 500, 300, 250, & 150 μm, respectively. Note that tartrazine concentration was increased to 2.81 mM for this phantom to increase light absorption and thus minimize unwanted curing from the stronger backlight of the high-resolution projector, while layers were printed perpendicular to the channel axis to limit light penetration into the channels. The phantom was coupled to the transducer with US gel to prevent water coupling into the channels, and color Doppler US imaging (30 MHz; MS400) of the flowing beads was performed using a pulse repetition frequency (PRF) of 2–3 kHz. Upon validation of flow throughout all phantom channels, channel diameters were measured from B-mode images with the VevoLAB analysis package’s digital calipers; the diameter at the narrowest measured point within the channel was recorded.

Next, a phantom was fabricated to image flow through a planar ‘serpentine’ channel architecture containing a single channel, with a nominal 1-mm diameter with straight sections separated by 180° turns (Phantom 16; Fig 2G). It was perfused with the same glycerol solution at a flow rate of 100 μL/min, and then color Doppler imaging data (1-kHz PRF; 24 MHz; MS400) were acquired for the purpose of reconstructing the 3D-flow vector components. The phantom was placed on the rotating base to provide 0°, 45°, & 90° acquisition angles with both +15 and -15° beam steering angles at each rotation angle (i.e., six unique views for each voxel). After imaging, Doppler values from all six acquisitions were imported into MATLAB and spatially co-registered to six degrees of freedom with an affine transform to obtain the X-, Y-, & Z-vector components for flow velocity at each voxel.

Finally, we fabricated an anatomy-mimicking vascularized tumor phantom with a hypoechoic tumor-mimicking printed target flanked by a 3D branched vessel network (Phantom 17) that included a common entry channel that branched into two distinct 3D vessels (Fig 2H). Note that Phantoms 16 & 17 were fabricated using 80 wt% PEGDA with a MW ratio (6:35 kDa) of 1:1 to improve the robustness of the resulting gel and minimize damage from the needle insertion required to create a fluid input port. Using the same glycerol solution, the phantom was perfused with a flow rate of 200 μL/min (to account for the larger channel diameters) and then coupled to the transducer with US gel and imaged using the same 3D color Doppler imaging and reconstruction protocol implemented for Phantom 16. These data were then used to calculate the magnitude of the fluid velocity, which was displayed as a 3D rendering fused with the B-mode data using the ParaView data analysis and visualization platform (Kitware, Inc., Clifton Park, NY) [43].

Results and discussion

US backscatter was generated at the boundary of each printed layer (Fig 3C), resulting from local density mismatches induced at hydrogel-layer boundaries (Fig 3B). In the optical phantoms with FITC-dextran, fluorescence intensity within each layer was inversely correlated with distance from the light source (Fig 3A), indicating that light exposure (i.e., from the projector source) was highest in the most proximal portion of each layer. Because extrusion printing is used, regions with the highest light exposure from one layer are inherently adjacent to regions with the lowest light exposure from the next layer, leading to discontinuities in light exposure through depth (Fig 3A). In B-mode images of matched phantoms, these exposure discontinuities were aligned with the US scattering generated at each layer boundary (Fig 3C), demonstrating that the “stacking” of photocured layers that occurs with extrusion printing produces local density discontinuities that result in hyperechoic regions.

Fig 3

Investigation of acoustic backscatter generation using optical and US imaging.

(A) Fluorescence imaging slice of Phantom 3 printed with 200-μm layers showing photobleached areas of high light exposure (blue arrow) and regions of low light exposure (red arrow). (B) Schematic of assumed phantom density, where dark regions indicate higher local density (blue arrow) and light regions indicate lower density (red arrow). The light source is below the phantom in the Z-direction (purple arrow). (C) Zoomed-in subsection (purple box in [D]) from Phantom 1 with 200-μm layers and imaged using 50-MHz B-mode US. Density mismatches appear as hyperechoic, while continuous-density regions appear anechoic. (D) 50-MHz (left) and 12-MHz (right) B-mode US images of Phantom 1 with 200-μm layers. (E) B-mode US images of Phantom 5 with two rectangular inclusions (orange arrows) printed with 50-μm layers at 50 MHz (top) and 12 MHz (bottom).

Hyperechoic layer boundaries were clearly visible in Phantom 1 (printed with 200-μm layers) when the 50-MHz transducer was used; however, these distinct boundaries were blurred at 30 MHz and difficult to distinguish at all at 12 MHz due to the spatial averaging resulting from lower-frequency imaging (Fig 3D). For phantoms printed with 50-μm layers, the print-layer boundaries were spatially averaged even using a 50-MHz center frequency, and they were indistinguishable at 12 MHz (S2 Fig), indicating that such print-voxel size is well suited for fabricating phantoms intended for more typical clinical US frequencies (i.e., <12 MHz).

Different cure times in laterally adjacent voxels in the X-Y plane of the phantom produced different echogenicity levels (i.e., rectangular inclusions in Fig 3E). Quantifying the backscatter signal in regions of increased exposure in Phantoms 5–7 revealed a nonlinear effect of cure time on US signal, where the first few additional seconds (i.e., the leftmost printed targets in Fig 4A and 4B) generated a large increase in the US signal relative to the baseline. However, this backscatter signal increased and then leveled off after an additional exposure of 5 seconds (i.e., the rightmost printed inclusions; Fig 4C). This increase in US signal within the targets was noted at all three investigated imaging frequencies, and in phantoms with and without xanthan gum or silica (Phantoms 5–7). Phantoms with silica concentrations of 1 mg/mL (i.e., Phantom 8) provide scattering more consistent with speckle than phantoms with lower silica concentrations (i.e., 0.1 mg/mL; Phantom 7) or phantoms with no silica added (i.e., Phantom 6; S5 Fig). As part of future work, silica and xanthan gum concentrations can be optimized in combination with print-layer thickness (i.e., to ensure complete photocuring in the presence of additional scatterers) to ensure that silica particles do not settle and/or aggregate during the phantom photocuring process.

Fig 4

Backscatter patterning and photocuring dependence.

C-scan US images of patterned phantoms (A) without silica particles (Phantom 4) and (B) with silica particles (Phantom 7; 0.1 mg/mL). (C) US backscatter signal and (D) CNR for each additional cure time over 6 weeks imaged at 30 MHz in Phantom 7. The data points for additional cure time in (C) and (D) each correspond to a unique printed target in the phantoms shown in (A) and (B).

Because PEGDA hydrogels can degrade over time via hydrolysis [44], we tested the temporal stability of the backscatter signal they generate. The US signal from all 1.5-mm printed targets in Phantom 5 (Fig 4A) decreased over time (Fig 4C). However, the CNR remained relatively stable over 6 weeks of storage and imaging (Fig 4D). Focal regions of hyperechogenicity (e.g., X,Y = 3,2 in Fig 4A) are likely a result of dust contamination during printing, an effect that can be mitigated by physically shielding the open print stage from the environment and/or by placing the stage in a (slight) negative-pressure vacuum hood. Morphologic changes of phantoms were also assessed immediately following printing and during storage. Hydrogels containing GelMA (Phantom 11) stored in PBS were morphologically most stable (S1 Table), experiencing an average (i.e., for both dimensions of the phantom body and lumen) absolute dimensional change compared to their CAD design of 5.2% (day of print) and 4.8% (31 days after print) at 4°C and 4.4% (day of print; this value was also used as the estimate for accuracy) and 6.6% (31 days after) at 25°C. Hydrogels without GelMA (Phantom 10) stored in PBS were less stable, experiencing an average absolute dimensional change compared to their CAD design of 12.4% (day of print) and 26.1% (31 days after print) at 4°C and 8.2% (day of print) and 21.1% (31 days after print) at 25°C. Hydrogels stored in DI water, regardless of storage temperature, immediately experienced significant (>20%) dimensional increases (i.e., both lumen and body) when compared to their initial CAD dimensions, an expected result given the osmotic imbalance between the PBS-based phantoms and (salt-free) DI water. Across all combinations, reproducibility measurements between matched phantoms differed by an average of 2.8%, while the average precision between measurements within the same phantom was 3.0%. Although print accuracy was estimated at 4.4%, such a metric can be difficult to characterize as interaction of the phantom with the measurement environment (e.g., PBS) can quickly cause changes from the original print geometry. In future work, we intend to investigate different PEG crosslinking chemistries that are more resistant to hydrolysis. For example, we previously demonstrated that PEG-diacrylamide is compatible with our fabrication technique [33], and this material has been shown to be resistant to hydrolysis [44].

We also characterized the group velocity through our hydrogel formulation (Phantom 9) to be 1527±1, 1523±2, & 1527±1 m/s for 2.25, 5, & 10MHz, respectively. This result is similar to work done by Aliabouzar et al., which reported sound speed values between 1500–1600 m/s for the same class of hydrogel [34]. This prior study also demonstrated that similar 3D-printed PEGDA-based samples as those investigated in our study present with US attenuation that is consistent with soft tissue, reporting average attenuation values of 0.54, 0.85, & 1.27 dB cm-1 MHz-1 when measured with center frequencies of 2.25, 5, 10 MHz, respectively.

Shear wave imaging data for the compliant elasticity phantom (Phantom 12) showed mean shear wave velocities between 1.6±0.1 and 2.3±0.1 m/s within regions of 5 and 12.5 seconds of cure time, respectively (S2 Table). These shear wave velocities correspond to Young’s moduli of 7.6 and 15.6 kPa, respectively, assuming a linear, isotropic, elastic medium; these values are within the range reported for in vivo imaging of soft tissue [41]. The stiff elasticity phantom (Phantom 13) presented a similar trend of increasing shear wave velocity with cure time; however, Young’s modulus estimates within the inclusions were significantly higher than typical soft tissue values, ranging from 72.9 to 123.6 kPa (S2 Table). In future studies, we will investigate the use of shorter photocuring times to establish a more precise relationship between cure time and stiffness; we will also examine the correlation between changes in US backscatter and stiffness as a function of photocuring time.

For the anisotropy elasticity phantom (Phantom 14), measured shear wave velocity (S2 Table) increased from 2.3±0.03 m/s to 2.6±0.08 m/s when the transducer was rotated from perpendicular (90°) to parallel (0°) with the printed column inclusions. These results yielded a significant 12% increase in shear wave velocity based on orientation, demonstrating transverse shear wave anisotropy within the phantom. Visualizations of the shear wave propagation over time for the 0° orientation can be seen in S3 Fig. Further development of this phantom model could prove useful for modeling tissues with striated fibers, such as muscle, as this phantom contained periodic anisotropic, chord-like structures which could mimic naturally occurring fiber orientation.

The goal in creating the small-channel flow phantom (Phantom 15) was to fabricate a phantom with channels approaching the order of size common for capillaries. The channel diameters were inconsistent throughout the extent due to differences in light scattering during photocuring, but diameters were measured as small as 60 μm (Fig 5A). Despite this inconsistency, all channels supported flow that tended to be laminar in nature upon investigation with quantitative analysis based on Doppler imaging.

Fig 5

Generation of phantoms with flow-supporting channels.

(A) B-mode US images (left) of Phantom 15 showing fluorescent microbeads injected into channels and zoomed-in regions (right; cyan dashed boxes) show channels as small as 60 μm remain open and support flow. (B) Zoomed-in views of two regions within the red box in (C). A physical imperfection (i.e., the hyperechoic point denoted by yellow arrow) within the fabricated channel caused disturbances in the symmetry of the parabolic flow profiles within this region (top); downstream from the imperfection, the flow returned to normal (bottom). Dashed black box indicates the location of the image cut-out shown in S4 Fig. (C) Doppler-derived flow velocity vectors through the serpentine channel (Phantom 16). (D) Zoomed-in view of the region in the green box in (C) showing a symmetric, parabolic velocity profile.

In the serpentine flow phantom (Phantom 16), the printed channels sustained parabolic flow profiles (Fig 5C, 5D). However, flow profile inconsistencies occurred in some locations (i.e., yellow arrow in Fig 5B), corresponding to regions of physical phantom irregularities, as confirmed with B-mode US imaging. Representative 2D images of Doppler overlaid B-mode data from Phantom 16 are provided in S4 Fig. As the phantom generally sustained a symmetric parabolic flow pattern, we are confident in our ability to fabricate a phantom with predictable flow patterns, and in future work, we will investigate more complex flow geometries.

The tumor flow phantom (Phantom 17) demonstrates variable levels of US contrast (i.e., hypoechoic tumor relative to background) and branching channels that can support fluid flow. In Fig 6C, a 3D rendering of the magnitude of Doppler-estimated flow velocity is fused with an US B-mode rendering, showing the printed “tumor” in the central region. Cross-sectional flow profiles (rightmost images in Fig 6C) present expected fluid flow patterns, with the central region of the channel lumen experiencing the highest velocity flow and continuous flow being observed throughout the channel.

Fig 6

3D reconstruction of flow around a hypoechoic tumor region.

(A) B-mode C-scan of Phantom 17 showing a hypoechoic tumor inclusion flanked by two vessels. (B) 3D B-mode US rendering of Phantom 17 and (C) this rendering fused with the magnitude of Doppler-estimated flow velocity through the channel network; to the right, cross-sectional flow profiles are provided for three representative locations, indicated by the dashed red lines.

The fabrication method proposed in this work provides a framework for voxel-specific US phantoms, which can be designed to bear the physical and acoustic properties shared by many soft tissues. The process not only generates US phantoms with properties that can be modified via both light exposure and external additives, but it allows for the production of an entire phantom in a single print session regardless of complexity. Note that the maximal print size of phantoms can be increased by increasing the size of the print platform. Additionally, a gelatin block can be cast around finer-detail, printed hydrogels with conventional backfill techniques to increase effective imaging depth and ensure adequate transducer coupling to the larger (hybrid) phantom. In the future, the proposed 3D-printing platform could be utilized with patient-derived anatomical data from CT or MRI to integrate actual patient data when fabricating a well-characterized phantom. The platform’s demonstrated viability for embedded living cells [33] also offers unique opportunities for highly precise and potentially more realistic in vitro imaging studies. Ultimately, this US phantom fabrication process provides a first step toward making phantoms that are realistic enough to assist in the development and validation of the next generation of US-based functional and quantitative imaging methods.

Conclusions

Our pSLA 3D printing technique is a viable approach for effectively fabricating phantoms for a broad range of US-mediated imaging applications. By modifying instructions for our 3D printing system, we can control the amount of light delivered to different regions within the hydrogel to manipulate both the local backscatter coefficient and stiffness while maintaining US properties consistent with soft tissue. Ultimately, we demonstrated the capacity to fabricate US phantoms in a single, semi-automated process containing patterns of complex and customizable backscatter, regions of varied and anisotropic elasticity consistent with soft tissue, and open-channel networks that can mimic naturally occurring vasculature and support flow. Collectively, these results show that projection-based stereolithography shows tremendous promise in providing a next-generation US fabrication phantom platform.

Function of custom Python script to incorporate differential curing within each layer.

(A) A Python script adds regions of secondary exposure to the primary background exposure to produce the illumination pattern for the printed object at each slice. (B) This process results in a final monolithic gel with different levels of photocuring.

(TIF)

Click here for additional data file.

Hyperechoic signal at print-layer boundaries.

B-mode images at (A) 12 MHz, (B) 30 MHz, & (C) 50 MHz of Phantom 1 with 200-μm layers showing the hyperechoic signal presenting at layer interfaces. B-mode images at (D) 12 MHz, (E) 30 MHz, & (F) 50 MHz of 50-μm layer Phantom 2.

(TIF)

Click here for additional data file.

Representative 2D shear wave images.

Images of US-based axial displacement estimates showing shear wave propagation (wave fronts identified with white arrows) at four time-points following an acoustic radiation force impulse in an anisotropic elasticity phantom (0° in Phantom 14).

(TIF)

Click here for additional data file.

Representative 2D Doppler images.

(A) Doppler data overlaid on B-mode images and (B) cut-out of the flow-velocity vector data from Fig 5C denoting the two imaging planes (distinguished by orange or purple dashed lines/arrows) shown through channels in Phantom 16 with opposite flow directions.

(TIF)

Click here for additional data file.

Representative 2D B-mode images with varying silica concentration.

B-mode images at 30 MHz of phantoms with 50-μm layer thickness and (A) only xanthan gum (0.833 mg/mL; Phantom 6), (B) xanthan gum (0.833 mg/mL) and 0.1 mg/mL silica particles (Phantom 7), and (C) xanthan gum (0.833 mg/mL) and 1 mg/mL silica particles (Phantom 8).

(TIF)

Click here for additional data file.

Percent differences over time of hydrogels stored in PBS at 4°C and 25°C when compared to designed CAD dimensions.

(DOCX)

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Results from US elasticity imaging.

(DOCX)

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15 May 2020

Submitted filename: Comments on Manuscript Submitted.docx

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21 Sep 2020

PONE-D-20-14537

Projection-based stereolithography for direct 3D printing of heterogeneous ultrasound phantoms

PLOS ONE

Dear Dr. Bouchard,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Both reviewers find the manuscript potentially valuable for ultrasound imaging research and development, especially for anisotropic tissues. However, both reviewers also pointed out missing performance analysis (accuracy and precision) of the proposed printing method given the readily available ground truth from the design models.

Please present how accurate, precise, reproducible and robust the proposed stereolithography method for printing complex tissue-mimicking phantoms for ultrasound studies in a quantitative way. In the present manuscript, no quantitative analysis is provided. In short, adding an in-depth performance analysis of the proposed method will significantly strengthen the paper.

As presented in the manuscript, the proposed method should be versatile as evidenced by 15 different types of phantoms manufactured, but the way they were presented made the manuscript less focused as Reviewer 1 suggested. Therefore, authors may consider to reorganize the manuscript. For instance, categorize phantoms according to tissue properties (backscattering (speed of sound, angle dependence, density), elasticity (purely elastic or even viscoelastic), and geometry (thin layer, bulk, hollow cylindrical or vasculature)) that can be assessed by current ultrasound imaging techniques. Then, elaborate the importance of these tissue properties in respective ultrasound clinical applications. Talk about challenges of meeting required tissue properties using existing ultrasound phantom-making methods in the literature. Lastly, summarize how your proposed method tackled those challenges and can guide potential readers realistic tissue-mimicking phantom design and fabrication.

Please address Reviewer 1's detailed comments as far as possible. Meanwhile, make study limitations clearer.

Please submit your revised manuscript by Nov 05 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Wei-Ning Lee

Academic Editor

PLOS ONE

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Reviewers' comments:

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1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The goal of the reported phantom work is relevant to quantitative ultrasound methods. Its main innovation is to demonstrate a single-session 3D printing approach for a variety of ultrasound applications that may simplify phantom development and allows control of backscatter and stiffness at the voxel level.

The presentation is not focused, however, rather several different phantom designs for different potential US applications are demonstrated but the rationale for these designs is not offered. Most appear to be intended for high frequency US imaging (still a small part of ultrasonography) but this is also not stated. It is argued that the proposed printing method has advantages over other phantom methods but these advantages are not clearly stated or demonstrated.

Perhaps it would help to focus the studies if measurements could be made to determine how accurately and precisely the intended phantom(s) specifications coded in the control software were rendered in the printed results. This seems to be the key question.

The manuscript is more in the form of a demonstration report or descriptive technical note rather than a succinct research paper. A number of fabrication factors that affect acoustic properties were examined but accuracy and precision of the measurements are not reported.

For production of a reference phantom or one mimicking tissue properties, there is a need to demonstrate the stability of phantom properties in terms of effects of room temperature, acoustic radiation force, humidity, time, etc. How reproducible are these properties for duplicate phantoms?

The authors argue that their 3D printed methods are more repeatable and reproducible that ordinary methods, one of the hallmarks of the QIBA effort. However, no data showing precision of the phantom properties is provided. What is the precision of their method for the acoustic properties that were measured? Was more than one phantom with the same technique printed and compared? What is the limit on spatial accuracy of the printing process?

The short title is the same as the full title, although good alternatives are possible, e.g., “Stereolithography 3D printing of ultrasound phantoms.”

The number of references may be excessive as many do not directly support the methods in the manuscript.

Line 19. The abstract summarizes the work and its purpose although the key question that was answered is not stated.

Line 48. The insufficiency of current phantoms depends on the QIB, the tissue of interest and the intended application. Elastography and flow are not the only QIBs of interest. For example, quantitative backscatter, attenuation, structure function, form factor, etc., using reference phantom methods are quite robust in liver, muscle and other (admittedly) more homogeneous organs. These methods depend on cellular-level structures, which would require adding scattering material to the 3D printing as described here.

Line 53. It may help to clearly state what is the purpose of having complex phantoms that approximate anatomy, function and mechanical properties of real tissues. How would they be used for QIB development? How close is good enough? The data presented do not appear to actually address anthropomorphic organ-mimicking phantoms anyway. Clearly state what they add that cannot be accomplished with simpler QIB phantoms that permit isolation of tissue properties independently or in simpler combinations.

Line 58. The quote from Ref 10 is referring to precision of QIB measurements specifically in phantoms, which may be overestimated. It is not referring to precision in patients for which many confounders are present but not present in phantoms. How do more complex phantoms contribute to solving this problem?

Line 112. “single fabrication step” should probably be changed to “single fabrication session.”

Line 128. “degree necessary” requires more explanation. Perhaps the current limits on printed voxel size and US field of view should be summarized somewhere.

Line 149. What are the x and y dimensions of the stage? Is this the limiting factor for the size of the phantom? All of the phantoms in Fig 2 are very small compared to the fields of view of clinical transducers. In addition, the B-mode images of the phantoms were made at nominally 12-50 MHz, so perhaps it should be stated early in the manuscript that the intended use for the phantoms is for high frequency applications. Can a phantom be fabricated that would contain the entire 3D dimensions of the human transducer? If so, what printing time might be required for Phantom A, if it were made a more useful size of 10 cm L x 10 cm W x 10 cm H? The authors state a printing rate of 3 cm depth per hour (at what x and y dimension?). What is the duration of a complete session needed to fully print a phantom that would encompass the full US transducer 3D field of view?

Line 157. Is this discontinuity interface a discrete boundary or is there also a gradient? To the same point, is it possible to create density gradients or only discrete layers?

Line 180. Rehydration and “swelling” of the phantom material appear to introduce a potential repeatability problem. Do you have data to support it does not?

Table 1. What was the total printing time to produce each phantom? It would help the reader to understand the advantages you claim for the single-session 3D printing versus other methods.

Line 197. You reference phantoms 8, 15 and 16. I do not see phantom 16 in this manuscript. What are the different concentrations of silica? How did backscatter coefficient vary with concentration and at what frequencies? How does the presence of the silica affect printing process and needed light exposure time compared to no silica in the formula?

Line 228 and 406. Since these layers are essentially specular reflectors, it may be confusing to refer to backscatter in this context especially since the phantoms have silica scatterers added to the formula. Perhaps you can refer to the effect of exposure time as changing “reflectivity” of acoustic impedance of the layers. The methods for measurement of “backscatter” are not described and the few results are in arbitrary units. Were these measures of pixel “echogenicity” from the B-modes? Ordinarily this incorporates many poorly controlled variables including gain, transmit power, TGC, grey-level LUT, position in FOV, etc. Sound speed estimates were made with the A-line RF signal; was “backscatter” as well?

Line 333. At 30 MHz, the transit time measurement should be robust while the caliper thickness error for 10 mm might contribute significant uncertainty. What is the accuracy and precision of both measurements in a homogeneous material with known speed of sound and thickness (e.g., nylon, acrylic, etc.)? How many independent measures of thickness and time were made?

Lines 294 and 342. Although you reference your methods as previously published, it would still be valuable to include the important experimental details here, such as frequency.

Line 390. Mean +/- SD indicates that you made multiple independent measures of each property. How many for each?

Line 405. Since the sequential printing procedure for each layer produces acoustic interfaces (mis-matches), does this present a problem for phantom design making it difficult to make large homogeneous regions?

Line 498. The shear wave speed results show promise for constructing anisotropic phantoms, at least in two dimensions. Researchers in muscle, tendon and nerve with quantitative US will find this has interesting potential for this work.

Line 560. The conclusions are appropriate for the material presented although they are very general.

Fig 2C. The spherical inclusions are stated to be 5 mm in diameter. What does “0-5 mm” mean here?

Fig 4 A and B. What is the origin of the dramatic non-uniformities?

Ref 44 is incomplete and it is not clear what type of publication this is (patent, book, etc.).

Ref 52 and 53 appear to be (almost) duplicates, referring to the same publication.

Reviewer #2: The authors present interesting developments in the realization and characterization of 3D printed US phantoms. Several samples and designs were fabricated and analyzed, while varying manufacturing parameters. Overall a very nice work that should be of interest to our readers.

One question, that perhaps this reviewer missed, is did the authors measure the as-printed feature dimensions in comparison to their original CAD model? Some understanding of the geometric fidelity of this process, if available, might also add value for the generation of complex 3D phantom structures.

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Reviewer #1: No

Reviewer #2: No

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14 Jul 2021

We would like to thank the editor as well as both reviewers for their detailed comments on our work. We have addressed all of the points included, and we believe that it has strengthened our manuscript. A few brief responses are in order to address the comments from the editor (editor's comment in quotations with our response immediately following):

1. "Please present how accurate, precise, reproducible and robust the proposed stereolithography method for printing complex tissue-mimicking phantoms for ultrasound studies in a quantitative way. In the present manuscript, no quantitative analysis is provided. In short, adding an in-depth performance analysis of the proposed method will significantly strengthen the paper."

We have now presented data regarding the accuracy, precision, stability, and reproducibility of our phantoms, as detailed in the reviewer reply.

2. "As presented in the manuscript, the proposed method should be versatile as evidenced by 15 different types of phantoms manufactured, but the way they were presented made the manuscript less focused as Reviewer 1 suggested. Therefore, authors may consider to reorganize the manuscript. For instance, categorize phantoms according to tissue properties (backscattering (speed of sound, angle dependence, density), elasticity (purely elastic or even viscoelastic), and geometry (thin layer, bulk, hollow cylindrical or vasculature)) that can be assessed by current ultrasound imaging techniques. Then, elaborate the importance of these tissue properties in respective ultrasound clinical applications. Talk about challenges of meeting required tissue properties using existing ultrasound phantom-making methods in the literature. Lastly, summarize how your proposed method tackled those challenges and can guide potential readers realistic tissue-mimicking phantom design and fabrication."

We would like to thank the editor for her suggestions; we have reorganized our manuscript in an order to improve clarity and focus. We have also expanded on the importance of the tissue properties we selected, the areas where current phantoms struggle to match our method, and how our method could aid other researchers in fabricating tissue-mimicking phantoms.

3. "Please address Reviewer 1's detailed comments as far as possible. Meanwhile, make study limitations clearer."

We have addressed all of reviewer 1's comments, and in doing so strengthened our work. Study limitations have also been addressed in the work.

Detailed replies to the specific comments from both reviewers can be found within the reviewer response document.

Submitted filename: Reviewer Response_FINAL.docx

Click here for additional data file.

14 Sep 2021

PONE-D-20-14537R1Projection-based stereolithography for direct 3D printing of heterogeneous ultrasound phantomsPLOS ONE

Dear Dr. Bouchard,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The authors have improved the manuscript significantly. As the second round reviewer pointed out, the study targeted at ultrasound imaging applications. The authors are advised to provide acoustic properties of the fabricated phantoms and discuss about fabrication reproducibility of the desired acoustic properties.

Please submit your revised manuscript by Oct 29 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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We look forward to receiving your revised manuscript.

Kind regards,

Wei-Ning Lee

Academic Editor

PLOS ONE

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Reviewer #3: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #3: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: N/A

**********

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Reviewer #3: Yes

**********

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Reviewer #3: Yes

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6. Review Comments to the Author

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Reviewer #3: This manuscript describes a 3D-printing technique of heterogeneous ultrasound phantoms based on stereolithography. The stiffness of the phantom can be controlled from 7 to >120 kPa. Blood-mimicking fluid flow can also be supported by this kind of phantom. This work is well written, and this kind of phantom could be useful if it can be well encapsulated. However, the author should provide more details on the ultrasound properties of the phantom.

General comments

1.This kind of phantom was mainly used in ultrasound imaging study, therefore, the ultrasound properties of the phantom, such as speed of sound and attenuation, should be presented.

2.The 2D imaging of Bmode, color Doppler, shear wave elastography should be provided in this study.

3.Typically, scatterer is important for ultrasound imaging, however, uniform scatterer distribution can not be seen in the figure 3 and figure 4, it should be discussed. In addition, some strong reflection like bubbles can been seen in figure 4, the author should also discuss it and explain how to avoid the the bubbles in phantom cooking.

4.Is this phantom water based? Should the phantom be used and stored in water? Did the author consider any preservative in this study?

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Reviewer #3: No

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13 Oct 2021

Editor comments:

The authors have improved the manuscript significantly. As the second round reviewer pointed out, the study targeted at ultrasound imaging applications. The authors are advised to provide acoustic properties of the fabricated phantoms and discuss about fabrication reproducibility of the desired acoustic properties.

We would like to thank the editor for their consideration of our work. We have made changes to the manuscript to better demonstrate the wide range of acoustic properties possible within our phantoms. We have additionally addressed all individual reviewer comments in our formal reviewer reply which is attached within the submission.

Submitted filename: ReveiwerReplyFinal.docx

Click here for additional data file.

17 Nov 2021

Projection-based stereolithography for direct 3D printing of heterogeneous ultrasound phantoms

PONE-D-20-14537R2

Dear Dr. Bouchard,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Wei-Ning Lee

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

1 Dec 2021

PONE-D-20-14537R2

Projection-based stereolithography for direct 3D printing of heterogeneous ultrasound phantoms

Dear Dr. Bouchard:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

Dr. Wei-Ning Lee

Academic Editor

PLOS ONE