Updates on Imaging of Common Urogenital Neoplasms 2nd Edition

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 77

Special Issue Editor


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Guest Editor
Department of Clinical Radiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, University Campus, 451 10 Ioannina, Greece
Interests: urogenital neoplasms; diagnostic imaging
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Special Issue Information

Dear Colleagues,

This Special Issue is on the multimodal imaging of common urogenital neoplasms. Significant technological advances in imaging, including ultrasonography (US), computed tomography (CT), magnetic resonance imaging (MRI) and nuclear medicine have brought many diagnostic benefits to genitourinary oncology.   

We are pleased to invite you to submit papers outlining updates on imaging common urogenital neoplasms.

Accurate imaging in patients with suspected genitourinary cancers may lead to the early diagnosis of primary tumors, more accurate tumor staging and consequent adequate and more tailored treatment planning, evaluation of treatment efficacy, and the detection of recurrence. This Special Issue aims to highlight the role of the most commonly used cross-sectional imaging techniques, including US, CT, MRI and fluorodeoxyglucose (FDG)-positron emission tomography (PET)-CT, in the work-up of common urogenital malignancies.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: prostate carcinomas, urinary bladder carcinomas, renal cell carcinomas, testicular neoplasms, ovarian neoplasm, uterine neoplasms, and uterine cervix carcinomas.

I look forward to receiving your contributions.

Dr. Athina C Tsili
Guest Editor

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Keywords

  • urogenital neoplasms
  • renal cell carcinoma
  • prostatic neoplasms
  • urinary bladder neoplasms
  • testicular neoplasms
  • uterine neoplasms
  • ovarian neoplasms
  • ultrasonography
  • computed tomography
  • magnetic resonance imaging

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Published Papers (1 paper)

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Research

23 pages, 4556 KB  
Article
Radiomics-Based Detection of Germ Cell Neoplasia In Situ Using Volumetric ADC and FA Histogram Features: A Retrospective Study
by Maria-Veatriki Christodoulou, Ourania Pappa, Loukas Astrakas, Evangeli Lampri, Thanos Paliouras, Nikolaos Sofikitis, Maria I. Argyropoulou and Athina C. Tsili
Cancers 2025, 17(19), 3220; https://doi.org/10.3390/cancers17193220 - 2 Oct 2025
Abstract
Background/Objectives: Germ Cell Neoplasia In Situ (GCNIS) is considered the precursor lesion for the majority of testicular germ cell tumors (TGCTs). The aim of this study was to evaluate whether first-order radiomics features derived from volumetric diffusion tensor imaging (DTI) metrics—specifically apparent diffusion [...] Read more.
Background/Objectives: Germ Cell Neoplasia In Situ (GCNIS) is considered the precursor lesion for the majority of testicular germ cell tumors (TGCTs). The aim of this study was to evaluate whether first-order radiomics features derived from volumetric diffusion tensor imaging (DTI) metrics—specifically apparent diffusion coefficient (ADC) and fractional anisotropy (FA) histogram parameters—can detect GCNIS. Methods: This study included 15 men with TGCTs and 10 controls. All participants underwent scrotal MRI, including DTI. Volumetric ADC and FA histogram metrics were calculated for the following tissues: group 1, TGCT; group 2: testicular parenchyma adjacent to tumor, histologically positive for GCNIS; and group 3, normal testis. Non-parametric statistics were used to assess differences in ADC and FA histogram parameters among the three groups. Pearson’s correlation analysis was followed by ordinal regression analysis to identify key predictive histogram parameters. Results: Widespread distributional differences (p < 0.05) were observed for many ADC and FA variables, with both TGCTs and GCNIS showing significant divergence from normal testes. Among the ADC statistics, the 10th percentile and skewness (p = 0.042), range (p = 0.023), interquartile range (p = 0.021), total energy (p = 0.033), entropy and kurtosis (p = 0.027) proved the most significant predictors for tissue classification. FA_energy (p = 0.039) was the most significant fingerprint of the carcinogenesis among the FA metrics. These parameters correctly characterized 88.8% of TGCTs, 87.5% of GCNIS tissues and 100% of normal testes. Conclusion: Radiomics features derived from volumetric ADC and FA histograms have promising potential to differentiate TGCTs, GCNIS, and normal testicular tissue, aiding early detection and characterization of pre-cancerous lesions. Full article
(This article belongs to the Special Issue Updates on Imaging of Common Urogenital Neoplasms 2nd Edition)
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