Development and Validation of an Ultrasound Imaging Algorithm for Structured Reporting in Testicular Pathology

<b>Background/Objectives</b>: Testicular ultrasound (US) imaging is a critical modality for diagnosing a variety of testicular pathologies, including malignancies. This study aimed to develop and validate a standardized diagnostic algorithm to enhance diagnostic accuracy and consistency in evaluating testicular lesions, particularly for distinguishing between benign and malignant conditions. <b>Methods</b>: The algorithm was applied retrospectively to 110 testicular imaging cases, including 90 abnormal and 20 normal cases, analyzed by three radiologists with varying experience levels. Key diagnostic features, including lesion morphology, vascularity, and echotexture, were evaluated to guide the differentiation process. <b>Results</b>: demonstrated high diagnostic accuracy, with sensitivity reaching 100% for detecting abnormal cases and specificity ranging between 80% and 95%. In distinguishing benign from malignant lesions, the algorithm achieved an area under the curve (AUC) of up to 0.917, with specificities exceeding 93%. Notably, strong inter-rater agreement was observed, underscoring the algorithm's reliability across different expertise levels. While the algorithm significantly improved standardization and diagnostic performance, some variability in sensitivity for less experienced evaluators highlights the need for further refinement. <b>Conclusions</b>: This study shows that the proposed diagnostic algorithm is an effective tool for testicular US, facilitating accurate and reproducible assessments, which are crucial for early detection and optimal management of testicular pathologies.

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Publication Details

Journal
Diagnostics
Published
2025-04-09
DOI
https://doi.org/10.3390/diagnostics15080951
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
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article

Development and Validation of an Ultrasound Imaging Algorithm for Structured Reporting in Testicular Pathology

Diana Gherman, Alexis Negrea, Anca Ciurea, Irene Boll et al.
1 citations
Diagnostics
Artificial Intelligence in Healthcare and Education
0.65
article

Development and Validation of an Ultrasound Imaging Algorithm for Structured Reporting in Testicular Pathology

Diana Gherman, Alexis Negrea, Anca Ciurea, Irene Boll, Bianca Boca, Manash Kumar Bora, Roxana Maria Pintican, Sorin Dudea
article en
1 citations

Abstract

<b>Background/Objectives</b>: Testicular ultrasound (US) imaging is a critical modality for diagnosing a variety of testicular pathologies, including malignancies. This study aimed to develop and validate a standardized diagnostic algorithm to enhance diagnostic accuracy and consistency in evaluating testicular lesions, particularly for distinguishing between benign and malignant conditions. <b>Methods</b>: The algorithm was applied retrospectively to 110 testicular imaging cases, including 90 abnormal and 20 normal cases, analyzed by three radiologists with varying experience levels. Key diagnostic features, including lesion morphology, vascularity, and echotexture, were evaluated to guide the differentiation process. <b>Results</b>: demonstrated high diagnostic accuracy, with sensitivity reaching 100% for detecting abnormal cases and specificity ranging between 80% and 95%. In distinguishing benign from malignant lesions, the algorithm achieved an area under the curve (AUC) of up to 0.917, with specificities exceeding 93%. Notably, strong inter-rater agreement was observed, underscoring the algorithm's reliability across different expertise levels. While the algorithm significantly improved standardization and diagnostic performance, some variability in sensitivity for less experienced evaluators highlights the need for further refinement. <b>Conclusions</b>: This study shows that the proposed diagnostic algorithm is an effective tool for testicular US, facilitating accurate and reproducible assessments, which are crucial for early detection and optimal management of testicular pathologies.

DiagnosticsVol. 15(8)
Iuliu Hațieganu University of Medicine and Pharmacy (RO), Clinical Emergency Hospital Bucharest (RO), Institute of Oncology Prof. Dr. Ion Chiricuta (RO)
Openalex Percentile: Top 26%
Artificial Intelligence in Healthcare and Education
0.65
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