| Literature DB >> 30103786 |
Paul Russell Roberts1, Ashesh B Jani2, Satyaseelan Packianathan1, Ashley Albert1, Rahul Bhandari1, Srinivasan Vijayakumar3.
Abstract
For 2018, the American Cancer Society estimated that there would be approximately 1.7 million new diagnoses of cancer and about 609,640 cancer-related deaths in the United States. By 2030 these numbers are anticipated to exceed a staggering 21 million annual diagnoses and 13 million cancer-related deaths. The three primary therapeutic modalities for cancer treatments are surgery, chemotherapy, and radiation therapy. Individually or in combination, these treatment modalities have provided and continue to provide curative and palliative care to the myriad victims of cancer.Today, CT-based treatment planning is the primary means through which conventional photon radiation therapy is planned. Although CT remains the primary treatment planning modality, the field of radiation oncology is moving beyond the sole use of CT scans to define treatment targets and organs at risk. Complementary tissue scans, such as magnetic resonance imaging (MRI) and positron electron emission (PET) scans, have all improved a physician's ability to more specifically identify target tissues, and in some cases, international guidelines have even been issued. Moreover, efforts to combine PET and MR to define solid tumors for radiotherapy planning and treatment evaluation are also gaining traction.Keeping these advances in mind, we present brief overviews of other up-and-coming key imaging concepts that appear promising for initial treatment target definition or treatment response from radiation therapy.Entities:
Keywords: Imaging; Radiation therapy; Treatment planning; Treatment response
Mesh:
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Year: 2018 PMID: 30103786 PMCID: PMC6088418 DOI: 10.1186/s13014-018-1091-1
Source DB: PubMed Journal: Radiat Oncol ISSN: 1748-717X Impact factor: 3.481
Fig. 1Fluorescent images of mice (pseudocolor). a Given an intratumoral injection of NALP (50 μL, 100 μM in a mixture of DPBS buffer (pH 7.4, 10 mM) and DMSO (4/1, v/v). b Before injection of NALP (50 μL, 100 μM in a mixture of DPBS buffer (pH 7.4, 10 mM) and DMSO (4/1, v/v), the tumor was pretreated with Na3VO4 (50 μL, 5 mM in doubly distilled water). c Quantification of imaging data, intensity in A-0.5 h was defined as 1. The selected circle region showed the tumor. (Used with permission. Originally published by Liu, et al. 2017 in In vivo imaging of alkaline phosphatase in tumor-bearing mouse model by a promising near-infrared fluorescent probe)
Fig. 2Raman spectra of control (a) and Raman difference spectra of [XRT] minus [control] (b) and [AMF] minus [control] (c). Major bands of the mineral are marked with violet shading. Major bands of the matrix are marked with red shading. (Used with permission. Originally published by Tchanque-Fossuo, et al. 2013 in Raman spectroscopy demonstrates Amifostine induced preservation of bone mineralization patterns in the irradiated murine mandible)
Fig. 3RF ablation monitoring in vivo. Representative graph illustrating the correlation of thermal tissue damage (NADH staining) with dynamic changes in OAR (long distance) measured in vivo during open RF ablation. (Used with permission. Originally published by Tanis, et al. 2017 Real-time in vivo assessment of radiofrequency ablation of human colorectal livermetastases using diffuse reflectance spectroscopy)
Fig. 4Dermoscopy and en face view of BCC on D-OCT: (a) Dermoscopy of BCC with pink-white shiny background, focal ulceration, arborizing vessels. b En face D-OCT of BCC shows disarray of thin, irregular vessels that are variable in size compared with the normal facial vessels. In comparison with more aggressive tumors, such as melanoma, the vascular pattern appears confined to the tumor. (Used with permission. Originally published by Levine, et al. 2017 in Optical Coherence Tomography in the Diagnosis of Skin Cancer)
Fig. 5a A reconstructed single wavelength MSOT image of mouse M1 (example of a PDA-KPC tumour) at 800 nm. The dashed yellow line indicates the tumour. b The corresponding spectrally unmixed image, showing the distribution of Hb and HbO2 components in blue and red respectively. c The oxymap image, showing the distribution of the SaO2 values. The yellow scale bar at the lower-left in each of these images is 5 mm. The yellow arrows in images b and c indicates the centre of a region that lacks any spectral signature of blood. The background, Hb, HbO2 and oxymap colour bars reflect the magnitude of the photoacoustic signals, deoxy-haemoglobin, oxy-haemoglobin and SaO2, respectively, as calculated by the MSOT system. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) (Used with permission. Originally published by Shah, et al. 2017 in Value of combining dynamic contrast enhanced ultrasound and optoacoustic tomography for hypoxia imaging)
Summary of imaging modalities advantages, disadvantages, and potential applications
| MODALITY | Advantages | Disadvantages | Applications |
|---|---|---|---|
| Autofluorescence | Real-time imaging; | Shallow DOF; low specificity; high cost | Superficial tumor monitoring; pre-neoplastic evaluation; surgical margin assessment |
| Near-infrared fluorescent imaging | Real-time imaging; deep DOF; high signal-to-noise | Need of imaging device; dye administration time | Surgical guidance; real-time monitoring and modulation of EBRT dose |
| Nonspecific Fluorescent Contrast Agents | Low dye toxicity; rapid hepatic clearance of dye | Contraindicated with contrast allergy; low signal-to-noise; no intracellular dye accumulation | Staging; guidance of radiotherapy planning; imaging for treatment delivery |
| Targeted Contrast Agents | Use Ig-based therapies as ligand; deep DOF via NIRF imaging | Require external fluorophore; few agents currently available | Diagnosis; staging |
| Radiofrequency Spectroscopy | No fluorophore needed; real-time imaging; handheld devices now exist | Limited FOV; shallow DOF | Residual disease detection; improved diagnostic imaging in solid tumors |
| Raman Spectroscopy | Real-time imaging; determine tissue response to radiation | Shallow DOF; low signal-to-noise; thermally damage samples | Measuring treatment response; post-op residual disease detection |
| Elastic Scattering Spectroscopy | Handheld devices; no fluorophore needed; rapid image acquisition; strong optical signal | Signal interference; variable DOF | Radiation damage detection; radiotherapy response monitoring |
| High-frequency Ultrasound | Sub-millimeter resolution; no fluorophore needed; approved devices | No ionizing radiation; variable sensitivity and specificity; complex image analysis algorithms | Superficial tumor assessment; reduce morbidity of prostate radiotherapy |
| Contrast-enhanced ultrasound | Real-time, continuous imaging; compatible with targeted contrast agents; widely-available; inexpensive; relatively safe | Shallow DOF; short half-life of contrast; potential for microvascular collapse | Primary/ metastasis characterization; ablation guidance |
| Optical Coherence Tomography | Cellular-level resolution; real-time imaging; handheld; no fluorophore needed; automated image analysis | Shallow DOF; narrow FOV | Renal mass identification; prostate cancer margin assessment |
| Optoacoustic Imaging | Real-time imaging; high resolution; enhanced by contrast agents | Historically shallow DOF but now improved | Staging; post-op planning for residual disease |
| Confocal Microscopy | Micron-level resolution; real-time imaging; no fluorophore needed; enhanced with fluorophores; automated image analysis; digital staining | Shallow DOF; narrow FOV; high device cost; user training necessary for manual interpretation | Detection and planning of cutaneous tumors and soft-tissue sarcomas |