The Role of Neck Imaging Reporting and Data System (NI-RADS) in the Management of Head and Neck Cancers DOI Creative Commons
Daniele Vertulli, Marco Parillo, Carlo Augusto Mallio

и другие.

Bioengineering, Год журнала: 2025, Номер 12(4), С. 398 - 398

Опубликована: Апрель 8, 2025

This review evaluates the current evidence on use of Neck Imaging Reporting and Data System (NI-RADS) for surveillance early detection recurrent head neck cancers. NI-RADS offers a standardized, structured framework specifically tailored post-treatment imaging, aiding radiologists in differentiating between residual tumors, scar tissue, post-surgical changes. demonstrated strong diagnostic performance across multiple studies, with high sensitivity specificity reported detecting tumors at primary sites. Despite these strengths, limitations persist, including frequency indeterminate results variability di-agnostic concordance imaging modalities (computed tomography, magnetic resonance (MRI), positron emission tomography(PET)). The also highlights NI-RADS’s reproducibility, showing inter- intra-reader agreements different techniques, although some modality-specific differences were observed. While it demonstrates good reproducibility modalities, attention is required to address findings variations. Future studies should focus integrating advanced characteristics, such as diffusion-weighted PET/MRI fusion further enhance accuracy. Continuous efforts refine protocols interpretations will ensure more consistent recurrences, ultimately improving clinical outcomes cancer management.

Язык: Английский

Using GPT-4o for CAD-RADS feature extraction and categorization with free-text coronary CT Angiography reports (Preprint) DOI

Youmei Chen,

Jie Sun,

Mengshi Dong

и другие.

Опубликована: Янв. 8, 2025

BACKGROUND Despite the Coronary Artery Reporting and Data System (CAD-RADS) providing a standardized approach, radiologists continue to favor free-text reports. This preference creates significant challenges for data extraction analysis in longitudinal studies, potentially limiting large-scale research quality assessment initiatives. OBJECTIVE To evaluate ability of GPT-4o model convert real-world coronary CT angiography (CCTA) reports into structured automatically identify CAD-RADS categories P Categories. METHODS retrospective study analyzed CCTA from January 2024 July 2024. A subset 25 was used prompt engineering instruct LLMs extracting categories, Categories, presence myocardial bridges non-calcified plaques. Reports were processed using API custom Python scripts. The ground truth established by radiologist based on 2.0 guidelines. Model performance assessed accuracy, sensitivity, specificity, F1 score. Intra-rater reliability Cohen's Kappa coefficient. RESULTS Among 999 patients (median age 66 years, range 58-74; 650 males), categorization showed accuracy 0.98-1.00, sensitivity 0.95-1.00, specificity score 0.96-1.00. Categories demonstrated 0.97-1.00, 0.90-1.00, 0.91-0.99. Myocardial bridge detection achieved 0.98 calcified plaque accuracy. values all classifications exceeded 0.98. CONCLUSIONS efficiently accurately converts data, excelling classification, burden assessment,

Язык: Английский

Процитировано

0
The radiologist as an independent “third party” to the patient and clinicians in the era of generative AI DOI Creative Commons
Anna Colarieti, Francesco Sardanelli

La radiologia medica, Год журнала: 2025, Номер unknown

Опубликована: Фев. 26, 2025

Язык: Английский

Процитировано

0
The Role of Neck Imaging Reporting and Data System (NI-RADS) in the Management of Head and Neck Cancers DOI Creative Commons
Daniele Vertulli, Marco Parillo, Carlo Augusto Mallio

и другие.

Bioengineering, Год журнала: 2025, Номер 12(4), С. 398 - 398

Опубликована: Апрель 8, 2025

This review evaluates the current evidence on use of Neck Imaging Reporting and Data System (NI-RADS) for surveillance early detection recurrent head neck cancers. NI-RADS offers a standardized, structured framework specifically tailored post-treatment imaging, aiding radiologists in differentiating between residual tumors, scar tissue, post-surgical changes. demonstrated strong diagnostic performance across multiple studies, with high sensitivity specificity reported detecting tumors at primary sites. Despite these strengths, limitations persist, including frequency indeterminate results variability di-agnostic concordance imaging modalities (computed tomography, magnetic resonance (MRI), positron emission tomography(PET)). The also highlights NI-RADS’s reproducibility, showing inter- intra-reader agreements different techniques, although some modality-specific differences were observed. While it demonstrates good reproducibility modalities, attention is required to address findings variations. Future studies should focus integrating advanced characteristics, such as diffusion-weighted PET/MRI fusion further enhance accuracy. Continuous efforts refine protocols interpretations will ensure more consistent recurrences, ultimately improving clinical outcomes cancer management.

Язык: Английский

Процитировано

0