Literature DB >> 34354085

An annotated T2-weighted magnetic resonance image collection of testicular germ and non-germ cell tumors.

Anna Sarnelli1, Gian Carlo Parenti2, Giacomo Feliciani3, Lorenzo Mellini2, Emiliano Loi1, Filippo Piccinini1, Roberto Galeotti2.   

Abstract

Testicular cancer is a rare tumor with a worldwide incidence that has increased over the last few decades. The majority of these tumors are testicular non-germ (TNGCTs) and germ cell tumors (TGCTs); the latter divided into two broad classes - seminomatous (SGCTs) and non-seminomatous germ cell tumors (NSGCTs). Although ultrasonography (US) maintains a primary role in the diagnostic workup of scrotal pathology, magnetic resonance imaging (MRI) has emerged as the imaging modality recommended for challenging cases, providing additional information to clarify inconclusive/equivocal US. In this work we describe and publicly share a collection of 44 images of annotated T2-weighted MRI lesions from 42 patients. Given that testicular cancer is a rare tumor, we are confident that this collection can be used to validate statistical models and to further investigate TNGCT and TGCT peculiarities using medical imaging features.
© 2021. The Author(s).

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Year:  2021        PMID: 34354085      PMCID: PMC8342409          DOI: 10.1038/s41597-021-00990-z

Source DB:  PubMed          Journal:  Sci Data        ISSN: 2052-4463            Impact factor:   6.444


Background & Summary

Although testicular neoplasms are classified as rare tumors, their incidence has increased worldwide in recent years[1]. The malignancy is common among men aged 15–44 years in the U.S., with almost 9600 new cases diagnosed in 2019[2].These tumors are classified into two categories: (a) testicular non-germ cell tumors (TNGCTs) and (b) testicular germ cell tumors (TGCTs), the latter divided into two broad classes: (b1) seminomatous germ cell tumors (SGCTs) and (b2) non-seminomatous germ cell tumors (NSGCTs). It is worthy of note that TGCTs in young men represent the vast majority of testicular neoplasms (nearly 95%), with benign sex cord-stromal tumors accounting for the remaining 5%[3]. Treatment and prognosis may change on the basis of the above categorization[4]. Advances in treatments, including surgery, chemotherapy and radiation, have resulted in a substantial decrease in the mortality rate of patients with testicular cancer, especially when diagnosed in the early phases. Color-doppler and conventional ultrasonography (US) are still considered the gold standard for the diagnosis of scrotal pathology, but magnetic resonance imaging (MRI) has emerged as a supplemental imaging modality and is mainly recommended as a problem-solving tool for challenging cases[5]. The final goal of MRI investigations is to reduce the incidence of unnecessary surgery[6]. Previous studies have underlined the role of qualitative radiological assessment based on T1- and T2-weighted MR images, which helps to differentiate between SGCT and NSGCT[7,8]. Furthermore, quantitative diffusion-weighted imaging (DWI) has been shown to have similar accuracy in discriminating between SGCT and NSGCT. Given the low incidence of these tumors, our dataset could help radiologists to gain valuable experience in recognizing testicular malignancies by visual inspection. Indeed, the dataset is enhanced by orchiectomy-confirmed final diagnosis and a consensus-based MRI visual assessment performed by two expert radiologists. Furthermore, in the past decade, breakthroughs in artificial intelligence (AI) have accelerated the application of computer-based analysis in medical imaging to guide/support clinical decision-making. The present dataset was collected with the main objective of the extraction of quantitative features from digital images, which can provide information not possible from human interpretation alone[9,10]. In a recent publication, Feliciani et al.[11] developed two imaging feature-based models to differentiate TGCTs from TNGCTs and SGCTs from NSGCTs, proving that T2-weighted based radiomics is a promising tool for the diagnostic workup of testicular tumors. The publication of this dataset could provide the means for an independent validation of an AI-based model developed by other research center[12].

Methods

Study population and eligibility criteria

A dataset of MR images from 42 patients with testicular cancer was analyzed. In compliance with current legislation, the research was carried out following approval of our institute’s Internal Review Board. We identified patients submitted to biopsy/orchiectomy from January 2006 to February 2019 and for whom a histological diagnosis of testicular cancer was subsequently confirmed by the Pathology Unit of Morgagni-Pierantoni Hospital, Forlì (Forlì Local Health Authority - Azienda USL della Romagna, Forlì), Italy. Patients for whom T2- and T1-weighted imaging was available in our imaging archive system (i.e. Carestream VuePACS, Carestream Health, Rochester, NY, USA) were selected. Exclusion criteria were as follows: (a) patients who underwent MRI after surgery or radiotherapy and/or chemotherapy; (b) poor quality of MR images due to movement artefacts; (c) lesion not visible on MRI; (d) metastatic tumor (Fig. 1). In clinical practice, MRI was performed as a second-level problem-solving technique when US results were equivocal/inconclusive, or to obtain detailed local staging of a testicular lesion previously identified by US.
Fig. 1

Flowchart of the patient recruiting process.

Flowchart of the patient recruiting process. Patient age ranged from 7 to 79 years (mean 39.3 ± 14.3 yrs). One patient had a bilateral classic seminoma and one had 2 different neoplasms, diagnosed years apart. We excluded 2 patients with testicular lymphoma and one with testicular localization of myeloma because of the uncertain origin of the primary tumor (potential metastatic origin of the tumor); another patient with classic seminoma was excluded due to poor image quality. Thus, the final dataset consisted of 42 patients.

Patient demographics

We analyzed MR studies of 44 testicular lesions (patient and lesion characteristics are summarized in Table 1). The time interval between MRI and final histologic diagnosis was 25 ± 15 days. Thirty-two of the 44 lesions were histologically classified as TGCTs, specifically 23 classic seminomas and 9 NSGCTs (7 mixed germ cell tumors and 2 embryonal cell carcinomas). Twelve of the 44 lesions were TNGCTs or other histological types, of which 7 Leydig cell tumors, 2 Sertoli cell tumors, 2 adenomatoid tumors and one epidermoid tumor. Laterality (left/right) and size were taken into consideration for each lesion. TGCTs were staged according to the 8 Edition of the American Joint Committee on Cancer (AJCC) Staging Manual[13].
Table 1

Patient demographics and lesion features.

Germ cell tumors
AGE (years)Average ± standard deviation36.8 ± 9
LATERALITYRight/Left19/13
SIZE (maximum diameter -cm)Average ± standard deviation3.2 ± 2.4
STAGING (T)pT1/pT2/pT3/pT417/13/2/0
Non germ cell tumors
AGE (years)Average ± standard deviation391 ± 18.6
LATERALITYRight/Left4/8
SIZE (maximum diameter - cm)Average ± standard deviation0.94 ± 0.46
Patient demographics and lesion features.

MRI T1- and T2-weighted sequence data

All MR T2- and T1-weighted sequences were acquired with the same 1.5 T Scanner (Achieva Philips, Philips Healthcare, Best, Netherlands) using a surface coil (Philips Sense Flex Medium coil). Sequences were acquired with the patients in a feet-first supine position. The surface coil was positioned over a towel covering the scrotum and the penis was dorsiflexed against the lower abdominal wall and taped in place to prevent motion. Peripheral venous access (19-gauge) was obtained in an antecubital fossa vein. The MRI imaging protocol included T1-weighted (T1w), T2-weighted (T2w) and, in some cases, also DWI sequences. Table 2 summarizes the acquisition settings of the scanner including pixel spacing, slice thickness, average echo time (TE), pulse repetition time (TR), and flip angle. Image stored pixel values (SV) are unsigned integers and can be converted through a DICOM reader into real world values (RV) through the Look-up Table Eq. (1):where Real World Value Slope corresponds to the DICOM tag (0040,9225) or (0028,1052) and Real World Value Intercept to (0040,9224) or (0028,1053), except for the datasets with ID 012, 016, 020, 024, 045.
Table 2

Scanner acquisition parameters.

Acquisition ParameterT1- weighted (mean ± SD)T2- weighted (mean ± SD)
Slice thickness3.2 ± 0.3 mm3.2 ± 0.4 mm
Repetition time5083 ± 48 ms4300 ± 1130 ms
Echo time123 ± 2 ms105 ± 19 ms
Flip angle90°/120°90°/120°
Resolution0.6 ± 0.1 mm0.5 ± 0.2 mm
Scanner acquisition parameters.

Manual segmentation of regions of interest

The patient’s testes and relative lesion were contoured on the T2w sequences (Fig. 2a,b) after joint consensus was reached by two expert radiologists. MIM Maestro (MIM Software Inc., Cleveland, OH, USA) was used for contouring.
Fig. 2

Examples of testicular lesions. (a) Testicular seminoma and (b) Germinal tumor. Axial and sagittal T2-weighted images, respectively. Testicles are contoured in cyan, whereas neoplasms are contoured in violet.

Examples of testicular lesions. (a) Testicular seminoma and (b) Germinal tumor. Axial and sagittal T2-weighted images, respectively. Testicles are contoured in cyan, whereas neoplasms are contoured in violet.

Assessment of visual features

During the contouring session, several visual features were also analyzed and are reported in Table 3. The visual features were selected following the indications reported in the work by Tsili et al.[7]. The 6 visual properties are as follows: (1) HOMO: this refers to signal homogeneity; (2) LOW SI: relative intensity of the lesion compared to normal testicular parenchyma on T2w sequences; 3) NECRO/HEMO: presence of necrotic or hemorrhagic areas; (4) CAPSULE: refers to the presence of capsule; (5) SEPTA and (6) CE: both refer to the presence and contrast uptake of bandwise regions in T2w sequences.
Table 3

Patient clinical data and visual features of the lesions.

IDAGESTAGEHOMOLOW SINECRO/HEMOCAPSULESEPTACE
NON GERMINOMAS (TNGCTs)
T01051nd000000
T01633nd000000
T01822nd011100
T01930nd010100
T02040nd100100
T02263nd010100
T02367nd110000
T02735nd010100
T03046nd110000
T0397nd110000
T04158nd010100
T04412nd000100
Ratio 1 vs total (%)336785800
GERMINOMAS - NON SEMINOMAS (NSGCTs)
T01737pT1a010011
T02426pT2001000
T02524pT2011000
T02841pT3011000
T03132pT1011100
T03626pT1001000
T03826pT2001000
T04032pT2011100
T04846pT2001000
Ratio 1 vs total (%)05589221111
SEMINOMAS (SGCTs)
T00137pT2011011
T00243pT1b011011
T00454pT2011011
T005x38pT1b010011
T005y38pT1a111100
T00631pT1a010000
T00736pT1a111011
T00837pT2110000
T00939pT1b110011
T01160pT3010011
T01226pT1a010011
T01336pT1a110100
T01550pT2011011
T02144pT2001011
T02931pT1a110011
T03230pT1a010011
T03335pT1a010000
T03444pT2011011
T03523pT1b110011
T03740pT2010000
T04235pT1b010011
T04549pT1a011110
T04743pT2010000
Ratio 1 vs total (%)309539137065

TNGCTs stage is marked as not defined (nd). The presence of a certain characteristic in the lesions is labelled by (1) HOMO: refers to signal homogeneity; (2) LOW SI: relative intensity of the lesion compared to normal testicular parenchyma on T2w sequences; (3) NECRO/HEMO: presence of necrotic or hemorrhagic areas; (4) CAPSULE: refers to the presence of capsule; (5) SEPTA and (6) CE: both refer to the presence and contrast uptake of bandwise regions in T2w sequences.

Patient clinical data and visual features of the lesions. TNGCTs stage is marked as not defined (nd). The presence of a certain characteristic in the lesions is labelled by (1) HOMO: refers to signal homogeneity; (2) LOW SI: relative intensity of the lesion compared to normal testicular parenchyma on T2w sequences; (3) NECRO/HEMO: presence of necrotic or hemorrhagic areas; (4) CAPSULE: refers to the presence of capsule; (5) SEPTA and (6) CE: both refer to the presence and contrast uptake of bandwise regions in T2w sequences.

De-identification of imaging data

All of the images in the dataset were cropped to preserve only the patient’s anatomical details related to the region of interest. Furthermore, in compliance with the current legislation on privacy, we de-identified and coded each patient with an unique ID.

Tumor surgery and clinical endpoint evaluation

Radical inguinal orchiectomy with removal of the tumor-bearing testis and the spermatic cord up to the inner inguinal ring is the gold standard for diagnosis and local treatment of patients with testicular malignancies. Furthermore, a biopsy is performed on a frozen section of the histological material if the diagnosis of testicular cancer is still not certain. These procedures determine the definitive histopathological classifications reported in our dataset. Further details on orchiectomy can be found in the work by Ghoreifi et al.[14].

Data Records

We created a public figshare collection called “2021_FelicianiGiacomo_Collection1”[15] containing: Original MRI images: T1-weighted (T1w) and T2-weighted (T2w) MRI images in DICOM format referring to the scrotal region of patients with testicular tumors. Contouring RadioTherapy Structure Set (RTSS): Manual contouring in DICOM format, performed by the expert radiologists who analyzed the testis and associated lesion. Summary of patient characteristics: Excel Table reporting the demographic, clinical and visual characteristics of patients. The collection is publicly available at: 10.6084/m9.figshare.c.5277818.v1.

Technical Validation

All MRI data were collected as part of routine patient healthcare and thus quality assurance was performed by Azienda USL della Romagna, where the data were collected.
Measurement(s)sex cord-gonadal stromal tumor
Technology Type(s)magnetic resonance imaging
Sample Characteristic - OrganismHomo sapiens
  13 in total

Review 1.  MRI of the scrotum: Recommendations of the ESUR Scrotal and Penile Imaging Working Group.

Authors:  Athina C Tsili; Michele Bertolotto; Ahmet Tuncay Turgut; Vikram Dogra; Simon Freeman; Laurence Rocher; Jane Belfield; Michal Studniarek; Alexandra Ntorkou; Lorenzo E Derchi; Raymond Oyen; Parvati Ramchandani; Mustafa Secil; Jonathan Richenberg
Journal:  Eur Radiol       Date:  2017-07-11       Impact factor: 5.315

Review 2.  Sonographically indeterminate scrotal masses: how MRI helps in characterization.

Authors:  Athina C Tsili; Michele Bertolotto; Laurence Rocher; Ahmet Tuncay Turgut; Vikram Dogra; Mustafa Seçil; Simon Freeman; Jane Belfield; Michal Studniarek; Alexandra Ntorkou; Lorenzo E Derchi; Raymond Oyen; Parvati Ramchandani; Subramaniyan Ramanathan; Jonathan Richenberg
Journal:  Diagn Interv Radiol       Date:  2018-07       Impact factor: 2.630

3.  Global trends in testicular cancer incidence and mortality.

Authors:  Alexandre Rosen; Gautam Jayram; Michael Drazer; Scott E Eggener
Journal:  Eur Urol       Date:  2011-05-17       Impact factor: 20.096

4.  The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more "personalized" approach to cancer staging.

Authors:  Mahul B Amin; Frederick L Greene; Stephen B Edge; Carolyn C Compton; Jeffrey E Gershenwald; Robert K Brookland; Laura Meyer; Donna M Gress; David R Byrd; David P Winchester
Journal:  CA Cancer J Clin       Date:  2017-01-17       Impact factor: 508.702

Review 5.  Germ cell tumors of the gonads: a selective review emphasizing problems in differential diagnosis, newly appreciated, and controversial issues.

Authors:  Thomas M Ulbright
Journal:  Mod Pathol       Date:  2005-02       Impact factor: 7.842

Review 6.  Management of Primary Testicular Tumor.

Authors:  Alireza Ghoreifi; Hooman Djaladat
Journal:  Urol Clin North Am       Date:  2019-08       Impact factor: 2.241

Review 7.  Radiomics: the facts and the challenges of image analysis.

Authors:  Stefania Rizzo; Francesca Botta; Sara Raimondi; Daniela Origgi; Cristiana Fanciullo; Alessio Giuseppe Morganti; Massimo Bellomi
Journal:  Eur Radiol Exp       Date:  2018-11-14

8.  T2-Weighted Image-Based Radiomics Signature for Discriminating Between Seminomas and Nonseminoma.

Authors:  Peipei Zhang; Zhaoyan Feng; Wei Cai; Huijuan You; Chanyuan Fan; Wenzhi Lv; Xiangde Min; Liang Wang
Journal:  Front Oncol       Date:  2019-11-28       Impact factor: 6.244

9.  The potential role of MR based radiomic biomarkers in the characterization of focal testicular lesions.

Authors:  Giacomo Feliciani; Lorenzo Mellini; Aldo Carnevale; Anna Sarnelli; Enrico Menghi; Filippo Piccinini; Emanuela Scarpi; Emiliano Loi; Roberto Galeotti; Melchiore Giganti; Gian Carlo Parenti
Journal:  Sci Rep       Date:  2021-02-10       Impact factor: 4.379

Review 10.  Imaging of the scrotum: beyond sonography.

Authors:  Gian Carlo Parenti; Francesco Feletti; Aldo Carnevale; Licia Uccelli; Melchiore Giganti
Journal:  Insights Imaging       Date:  2018-02-15
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