Diagnostic and interventional radiology最新文献

{"title":"Establishment of an inferior vena cava filter retrieval program: the effect on trauma and non-trauma patient populations.","authors":"Katelyn Gill, Hector Ferral, Alexandra H Fairchild, Bahri Üstünsöz, Dan F Laney Iv, John Hunt, Jonathan E Schoen, Alan Marr, Patrick Greiffenstein, Lance Stuke, Alison A Smith","doi":"10.4274/dir.2025.253409","DOIUrl":"10.4274/dir.2025.253409","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to compare the effect of establishing an inferior vena cava filter (IVCF) retrieval program (IVCFRP) on the IVCF retrieval rates in trauma and non-trauma patients.</p><p><strong>Methods: </strong>This was an institutional review board-approved retrospective study. IVCF retrieval in trauma and non-trauma patients was compared before and after the establishment of an IVCFRP in a single Level I Trauma Center. The IVCFRP at our institution was established in April 2020. All patients who underwent IVCF placement between January 2016 and March 2020 were compared with patients who had an IVCF placed between April 2020 and June 2024. A medical record review included the collection of demographic information, indication for IVCF insertion and retrieval, date of IVCF insertion and retrieval, IVCF retrieval rate, clinical outcomes, and complications. The patients were stratified into trauma and non-trauma groups. Univariate analyses were performed with a <i>P</i> value of <0.05 considered statistically significant.</p><p><strong>Results: </strong>A total of 164 patients underwent IVCF placement between January 2016 and June 2024. Fifty-two IVCFs were implanted before and 112 after the establishment of the IVCFRP. The overall rate of IVCF retrieval was significantly higher following the establishment of an IVCFRP (33.3% vs. 51%, <i>P</i> = 0.047). In non-trauma patients, the retrieval rate was significantly higher after the establishment of an IVCFRP (37.5% vs. 61.3%, <i>P</i> = 0.03). The retrieval rate in trauma patients (22.2% vs. 21.4%) was not significantly changed by the establishment of an IVCFRP. Clinical outcomes and complications were similar between groups.</p><p><strong>Conclusion: </strong>IVCF retrieval rates significantly improved after the establishment of an IVCFRP. This increase in IVCF retrieval rate was driven by an increase in filter retrievals in the non-trauma patient population. The rate of IVCF retrieval in trauma patients was not affected by the implementation of an IVCFRP. Special considerations and changes in practice may need to be established to improve IVCF retrieval rates in trauma patients.</p><p><strong>Clinical significance: </strong>Implementation of a structured IVCFRP significantly improved retrieval rates in non-trauma patients but did not yield similar results in trauma patients, highlighting the need for alternative strategies in this population.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"692-699"},"PeriodicalIF":2.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530627/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145184885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiomics-based differentiation of benign and malignant breast masses on contrast-enhanced mammography: a reproducible workflow using open-source tools.","authors":"Aykut Teymur, Sibel Kul, Ramazan Özgür Doğan, Hayati Türe, Temel Kayıkçıoğlu, Onur Bektaş, Sinan Erdemi, Cemal Aydoğan","doi":"10.4274/dir.2026.263222","DOIUrl":"10.4274/dir.2026.263222","url":null,"abstract":"<p><strong>Purpose: </strong>To differentiate benign and malignant breast masses by extracting radiomic features from low-energy and recombined contrast-enhanced mammography (CEM) images and to evaluate the diagnostic performance of multiple machine learning classifiers.</p><p><strong>Methods: </strong>In this retrospective, single-center study, 145 patients who underwent CEM between February 2019 and January 2022 were included. Radiomic features were extracted from manually segmented regions of interest on low-energy and recombined images using an open-source workflow (ITK-SNAP and PyRadiomics). The dataset was split at the patient level into a training set (75%) and an independent test set (25%); within the training set, feature selection and model optimization were performed using 10-fold cross-validation. Diagnostic performance [as measured by area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value] was reported on the held-out independent test set.</p><p><strong>Results: </strong>Ensemble learning demonstrated the best performance for both image types. The highest accuracy and AUC were 91.8% and 0.978 for recombined images and 89.7% and 0.968 for low-energy images, respectively. For recombined images, ensemble learning yielded the highest sensitivity (91.8%), whereas neural networks achieved the highest specificity (95.8%). For low-energy images, ensemble learning reached the highest sensitivity (98.0%), and decision trees achieved the highest specificity (91.7%).</p><p><strong>Conclusion: </strong>Radiomics analysis of CEM images can effectively differentiate between benign and malignant breast masses, potentially enhancing diagnostic accuracy in breast imaging.</p><p><strong>Clinical significance: </strong>A radiomics workflow based on recombined CEM images and open-source tools may complement conventional CEM interpretation, improve non-invasive lesion characterization, and support further research toward clinically validated decision-support applications.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"618-625"},"PeriodicalIF":2.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146164473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human-AI interaction and collaboration in radiology: from conceptual frameworks to responsible implementation.","authors":"Burak Kocak, Renato Cuocolo","doi":"10.4274/dir.2026.263780","DOIUrl":"10.4274/dir.2026.263780","url":null,"abstract":"<p><p>Artificial intelligence (AI) is entering routine radiology practice, but most studies evaluate algorithms in isolation rather than their interaction with radiologists in clinical workflows. This narrative review summarizes current knowledge on human-AI interaction in radiology and highlights practical risks and opportunities for clinical teams. First, simple conceptual models of human-AI collaboration are described, such as diagnostic complementarity, which explain when radiologists and AI can achieve synergistic performance exceeding that of either alone. Then, AI tool integration strategies along the imaging pathway are reviewed, from acquisition and triage to interpretation, reporting, and teaching, outlining common interaction models and physician-in-the-loop workflows. Cognitive and professional effects of AI integration are also discussed, including automation bias, algorithmic aversion, deskilling, workload management, and burnout, with specific vulnerabilities for trainees. Furthermore, key elements of responsible implementation are summarized, such as liability and oversight implications, continuous monitoring for performance drift, usable explanations, basic AI literacy, and co-design with radiology teams. Finally, emerging systems are introduced, including vision-language models and adaptive learning loops. This review aims to provide a clear and accessible overview to help the radiology community recognize where human-AI collaboration can add value, where it can cause harm, and which questions future studies must address.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"535-547"},"PeriodicalIF":2.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530499/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146046224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large-scale evaluation of multimodal large language models for pneumothorax detection.","authors":"Hamza Eren Güzel, Cemre Özenbaş, Ali Murat Koç","doi":"10.4274/dir.2026.263696","DOIUrl":"10.4274/dir.2026.263696","url":null,"abstract":"<p><strong>Purpose: </strong>Pneumothorax requires rapid recognition and accurate interpretation of chest X-rays (CXRs), particularly in acute settings where delays can have serious consequences. With the emergence of advanced image interpretation models capable of visual analysis, their diagnostic reliability in radiology practice remains to be determined. This study aimed to assess the diagnostic performance of three state-of-the-art systems in detecting pneumothorax using a large, well-annotated dataset.</p><p><strong>Methods: </strong>A total of 10,675 CXRs from the publicly available SIIM-ACR Pneumothorax Segmentation dataset were analyzed. Three multimodal models (GPT-4o, Gemini 2 Pro, and Claude 4 Sonnet) were evaluated using a uniform, image-based approach. Each model's binary outputs (presence: 1, absence: 0) were compared with reference results to determine accuracy, sensitivity, specificity, precision, and F1 scores. Additional subgroup analyses were conducted across pneumothorax size categories: small, medium, and large. Pairwise statistical comparisons were performed using McNemar's test. Sensitivity, specificity, and overall accuracy are reported with corresponding 95% confidence intervals.</p><p><strong>Results: </strong>The prevalence of pneumothorax in the dataset was 22.3% (n = 2,379). All models demonstrated high specificity (above 0.90) but consistently low sensitivity (0.16-0.36). The best overall performance was observed with Gemini 2, which achieved an accuracy of 0.79 and specificity of 0.95, whereas Claude 4 showed greater sensitivity (0.20-0.34) across lesion-size categories. Diagnostic performance improved with increasing pneumothorax size, but smaller lesions remained difficult to identify. Pairwise comparisons confirmed statistically significant differences among all evaluated systems (<i>P</i> < 0.050).</p><p><strong>Conclusion: </strong>In this large-scale evaluation, the tested models exhibited strong reliability in identifying normal examinations but limited ability to detect subtle or small pneumothoraxes. Despite high specificity, low sensitivity limits the use of current multimodal large language models as rule-out tools for pneumothorax. With continued refinement, these models may eventually support radiologists by improving workflow efficiency and diagnostic confidence.</p><p><strong>Clinical significance: </strong>Automated systems capable of high specificity but low sensitivity should not be relied upon to exclude pneumothorax. However, they may serve as valuable assistants for confirming positive findings and prioritizing urgent cases in busy clinical workflows.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"585-590"},"PeriodicalIF":2.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530647/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146164501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microvascular dysfunction in patients with transthyretin cardiac amyloidosis evaluated by 13N-ammonia positron emission tomography-computed tomography: is it an early marker of the disease?","authors":"Aristóteles Neto, Caio Cafezeiro, Bruno Bueno, Cristhian Espinoza Romero, Vitor Emer Rosa, Viviane Hotta, Camila de Godoi Carneiro, Carlos Rochitte, Vagner Madrini, Jose Soares, William Chalela, Marcos Lima, Carlos Buchpiguel, Edward Miller, Fabio Fernandes","doi":"10.4274/dir.2026.263687","DOIUrl":"10.4274/dir.2026.263687","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate coronary microvascular function using 13N-ammonia positron emission tomography/ computed tomography in individuals with pathogenic <i>transthyretin (TTR)</i> gene mutations, with and without cardiac involvement. This study is the first to assess coronary flow reserve (CFR) in this population before overt cardiac amyloidosis (CA) is detectable by conventional imaging.</p><p><strong>Methods: </strong>We evaluated microvascular impairment by measuring CFR in 20 patients with and 20 patients without cardiac involvement due to TTR amyloidosis (ATTR), all presumed to be free from epicardial coronary artery disease and carrying <i>TTR</i> gene mutations.</p><p><strong>Results: </strong>The study revealed a significantly reduced mean global CFR in the cardiac involvement group (1.849 ± 0.379 vs. 2.952 ± 0.7, <i>P</i> < 0.001). Global CFR inversely correlated with age, functional class, troponin, and B-type natriuretic peptide while positively correlating with the 6-minute walk test distance, mean blood pressure, and global longitudinal strain. Receiver operating characteristic curve analysis identified an optimal cutoff value of global CFR < 2.58, yielding a sensitivity of 100% and a specificity of 75% for detecting cardiac involvement.</p><p><strong>Conclusion: </strong>In patients with ATTR CA, coronary microvascular dysfunction emerges as a clinically relevant marker of cardiac involvement, even in the absence of structural abnormalities or obstructive coronary disease.</p><p><strong>Clinical significance: </strong>CFR assessment may aid in diagnostic suspicion, risk stratification, and understanding of angina symptoms in this population.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"669-674"},"PeriodicalIF":2.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530596/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146112632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential radiation dose reduction in computed tomography with deep learning reconstruction: a retrospective monocentric study.","authors":"Lucas Graber, Melike Zeynep Akış, François Séverac, Luc Mertz, Serhat Akış, Catherine Roy, Mickaël Ohana","doi":"10.4274/dir.2025.253513","DOIUrl":"10.4274/dir.2025.253513","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate whether deep learning reconstruction (DLR) can reduce the radiation dose in routine clinical computed tomography (CT) scans compared with iterative reconstruction (IR) while maintaining or improving image quality. The study assesses DLR's consistency and effectiveness across four distinct CT protocols-chest, head, chest-abdomen-pelvis (CAP) oncology, and lower limb CT angiography (CTA)-representing a wide range of clinical applications.</p><p><strong>Methods: </strong>Our study is retrospective and monocentric. It involves a total population of 13,060 patients who underwent a CT scan using either a DLR algorithm (CT-DLR) or an IR algorithm (CT-IR) in one of four different CT acquisition protocols. Image quality was evaluated qualitatively and quantitatively by measuring standardized signal-to-noise ratio and contrast-to-noise ratio values. Assessment was performed on a subsample of 200 patients (25 per protocol per group).</p><p><strong>Results: </strong>The overall reduction in radiation dose for the CT-DLR group compared with the CT-IR group was approximately 20%. By protocol, dose reductions were 22% for chest CT, 21% for CAP oncology, 20% for lower limb CTA, and 19% for head CT. The CT-DLR group exhibited superior subjective and objective image quality to the CT-IR group.</p><p><strong>Conclusion: </strong>DLR algorithms allow for a significant reduction in radiation dose while achieving higher image quality compared with IR algorithms.</p><p><strong>Clinical significance: </strong>This large-scale study confirms that DLR can significantly reduce the radiation dose in routine CT imaging while maintaining or enhancing diagnostic image quality. Its consistent performance across multiple protocols supports broader clinical adoption. Notably, the greatest dose reductions were observed in high-use protocols such as chest and CAP CT, underscoring DLR's potential to improve both individual patient care and long-term population-level radiation safety.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"565-573"},"PeriodicalIF":2.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530545/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145676256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The hematoma measurement accuracy of dual-energy computed tomography angiography in spontaneous intracerebral hemorrhage.","authors":"Baoteng Zhang, Qingjing Huang, Feijian Wu, Suying Wu, Jianfang Huang, Zhihua Lu","doi":"10.4274/dir.2026.263859","DOIUrl":"10.4274/dir.2026.263859","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;To investigate the accuracy of hematoma volume (V), surface area (S), and surface regularity (SR) measured on dual-energy computed tomography angiography (DECTA), using non-contrast computed tomography (NCCT) as the reference standard.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A total of 129 patients with spontaneous intracerebral hemorrhage (sICH) who underwent both NCCT and DECTA scans were retrospectively studied. Patients were stratified by V: Group 1 (&lt; 30 mL), Group 2 (30-60 mL), and Group 3 (&gt; 60 mL); and by morphology: regular, irregular, and lobular. DECTA data were post-processed to generate conventional computed tomography angiography (CTA) and 60 keV virtual monoenergetic imaging (VMI). These, along with NCCT images, were imported into 3D Slicer software to obtain V and S; SR was subsequently calculated. Deviation percentages (ΔV, ΔS, ΔSR) of conventional CTA and 60 keV VMI relative to NCCT were calculated. We assessed correlations using simple linear regression, compared different modalities with unpaired t-tests or Mann-Whitney U tests, evaluated agreement via Bland-Altman analysis, and compared deviation percentages across groups using one-way analysis of variance or Kruskal-Wallis H tests. Inter-reader consistency was assessed using the intraclass correlation coefficient (ICC).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The average V was 28.86±24.15 mL. All ICCs were excellent (0.991-0.999). Strong correlations were found for V and S between conventional CTA/60 keV VMI and NCCT (r: 0.987-0.996). Bland-Altman analysis for V showed mean biases of 0.21 mL (conventional CTA) and -0.04 mL (60 keV VMI) against NCCT, with 95% limits of agreement of -4.72 to 5.14 mL and -4.51 to 4.43 mL, respectively. However, SR values from both conventional CTA and 60 keV VMI were significantly lower than those from NCCT (all &lt;i&gt;P&lt;/i&gt; &lt; 0.001). In volume-based stratification, no significant differences in ΔS (conventional CTA) or ΔV, ΔS, and ΔSR (60 keV VMI) were found among groups (all &lt;i&gt;P&lt;/i&gt; ≥ 0.410). For conventional CTA, ΔV was significantly smaller in Group 3 (&gt; 60 mL) than in Group 1 (3.07% vs. 5.57%, adjusted &lt;i&gt;P&lt;/i&gt; = 0.047), whereas ΔSR was larger (13.26% vs. 9.88%, adjusted &lt;i&gt;P&lt;/i&gt; = 0.040). Morphology-based stratification revealed no significant differences in ΔV, ΔS, or ΔSR across groups for either modality (all &lt;i&gt;P&lt;/i&gt; values ≥ 0.085).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Hematoma volume measurements from DECTA show good agreement with NCCT measurements, suggesting potential utility for follow-up assessment in certain clinical scenarios. However, DECTA-derived SR measurements are significantly lower than those from NCCT. Volume measurement accuracy of conventional CTA was higher for large hematomas (&gt; 60 mL).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Clinical significance: &lt;/strong&gt;Accurate hematoma measurement is crucial for prognosis and management in sICH. This study indicates that V measurements from DECTA are comparable to those from NCCT in certain cl","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"725-732"},"PeriodicalIF":2.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530441/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148137087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-parametric magnetic resonance imaging-based radiomics for differentiation of skull base osteomyelitis from locally advanced nasopharyngeal carcinoma: a multi-center external validation study.","authors":"Fırat Atak, Hanife Avcı, Yeliz Pekçevik, Ayça Karaosmanoğlu","doi":"10.4274/dir.2025.253574","DOIUrl":"10.4274/dir.2025.253574","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;Skull base osteomyelitis (SBO) and nasopharyngeal carcinoma (NPca) are challenging to differentiate due to overlapping clinical and radiological features. This study aimed to develop and validate a multi-parametric magnetic resonance imaging (MRI)-based radiomics model with high sensitivity, enabling reliable diagnosis of SBO in adult patients presenting with equivocal imaging findings.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This was a retrospective, multicenter study using institutional data. The training cohort, comprising 63 adult patients from two classes (31 SBO, 32 NPca) with MRI data, was used for model development and optimization. An external test set (n = 30; 12 SBO, 18 NPca) obtained from two different clinical centers was used for model performance analysis and generalizability. Lesion segmentation was performed using a manual volumetric technique on three axial MRI sequences (pre-contrast T1-weighted, fat-suppressed T2-weighted, and post-contrast fat-suppressed T1-weighted). Hand-crafted radiomic features (n = 2,553) were extracted using the Pyradiomics library. A multi-step process was used to select the final features, including reproducibility analysis using an intraclass correlation coefficient threshold of 0.9, pairwise Spearman correlation analysis with a threshold of 0.8 to reduce redundancy, and least absolute shrinkage and selection operator regression. The final set of five features were used to train six machine learning models. The models were internally validated using 5-fold cross-validation, and performance was confirmed using the unseen external test set. Traditional statistical tests, including the Mann-Whitney U test and chi-squared test, were used to compare baseline characteristics, with a P value of &lt;0.05 considered significant.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Among the evaluated classifiers, the random forest model demonstrated the best diagnostic performance, yielding the highest area under the curve (AUC) value in the 5-fold cross-validation analysis. In the external test set, the semantic model demonstrated the best diagnostic performance, achieving an AUC of 0.940 [95% confidence interval (CI): 0.857-1.00], followed by the radiomics model (AUC: 0.903, 95% CI: 0.784-1). The apparent diffusion coefficient (ADC)-based model demonstrated limited discriminative ability (AUC: 0.694, 95% CI: 0.497-0.892). The difference between the semantic and radiomics models did not reach statistical significance (&lt;i&gt;P&lt;/i&gt; = 0.644), whereas both significantly outperformed the ADC model (&lt;i&gt;P&lt;/i&gt; &lt; 0.05).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Radiomics achieved high and consistent performance in distinguishing SBO from advanced NPca. Although expert-based semantic assessment performed slightly better, radiomics provides an objective alternative. ADC-based methods showed limited generalizability due to inter-center variability.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Clinical significance: &lt;/strong&gt;Our study confirms the importance of ex","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"574-584"},"PeriodicalIF":2.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145676181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Letter to the Editor: comments on the diagnostic value of ADC texture analysis in PI-RADS 5 lesions.","authors":"Esat Kaba","doi":"10.4274/dir.2025.253811","DOIUrl":"10.4274/dir.2025.253811","url":null,"abstract":"","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"531-532"},"PeriodicalIF":2.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530675/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146112462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Post-cryoablation magnetic resonance imaging features of desmoid tumors: a pictorial essay.","authors":"Leonor G Savarese, Nicolas Papalexis, Marco Miceli, Michela Carta, Giancarlo Facchini","doi":"10.4274/dir.2025.253499","DOIUrl":"10.4274/dir.2025.253499","url":null,"abstract":"<p><p>Desmoid tumors (DTs) are rare, locally aggressive soft tissue neoplasms with highly variable clinical behavior. Although benign, their infiltrative nature can lead to considerable morbidity. DTs present a major challenge due to their unpredictable behavior and potential for misdiagnosis. Recently, there has been a large shift in the treatment strategy for DTs, and the number of cases being followed up with imaging has increased. Cryoablation has emerged as a minimally invasive treatment option, yet post-procedural imaging features remain poorly characterized. This study illustrates the magnetic resonance imaging (MRI) evolution of DTs following percutaneous cryoablation, emphasizing key patterns across pre-treatment, intra-procedural, and follow-up studies. The available MRI follow-up ranged from 6 to 30 months. Through a pictorial approach, we aimed to provide radiologists with practical insights to avoid misinterpretation of expected post-treatment changes as recurrence and to improve clinical management.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"709-714"},"PeriodicalIF":2.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530442/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145700058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}