Academic Radiology最新文献

{"title":"Long-term Migration of Breast Biopsy Markers with and without Mitigating Strategies in an Animal Model","authors":"Matthew W. Urban PhD, Gina K. Hesley MD, Thomas R. Meier DVM, MBA, Benjamin G. Wood BS, Nathanial Bergan, Beiyun Chen MD, PhD, Gregory J. Michalak PhD, Blake A. Kassmeyer MS, David R. Holmes, III PhD, Nicholas B. Larson PhD, MS, Mara A. Piltin DO, Christine U. Lee MD, PhD","doi":"10.1016/j.acra.2026.07.023","DOIUrl":"10.1016/j.acra.2026.07.023","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>In the care of patients with breast cancer, it is now common for a radiologist to place biopsy markers in suspicious axillary lymph nodes that are biopsied so that the lymph nodes can be identified for later surgical excision. Migration of markers has been reported, but has only been sparingly evaluated. The objective of this study was to evaluate the migration of biopsy markers in a porcine model using longitudinal X-ray computed tomography (CT) imaging</div></div><div>In the care of patients with breast cancer, it is now common for a radiologist to place biopsy markers in suspicious axillary lymph nodes that are biopsied so that the lymph nodes can be identified for later surgical excision. Migration of markers has been reported, but has only been sparingly evaluated. The objective of this study was to evaluate the migration of biopsy markers in a porcine model using longitudinal X-ray computed tomography (CT) imaging</div><div><h3>Materials and Methods</h3><div>We report the evaluation of migration of a commercial biopsy marker (Tumark Professional Q) and a marker made of polymethyl methacrylate (PMMA) that is being developed for improved ultrasound imaging detection. We tested these markers alone as well as combined with adjacent hernia mesh and injections of ethanol to promote local inflammatory responses to mitigate migration. We imaged animals (N = 3) at monthly time points with CT to evaluate marker-to-lymph node spatial relationships.</div></div><div>We report the evaluation of migration of a commercial biopsy marker (Tumark Professional Q) and a marker made of polymethyl methacrylate (PMMA) that is being developed for improved ultrasound imaging detection. We tested these markers alone as well as combined with adjacent hernia mesh and injections of ethanol to promote local inflammatory responses to mitigate migration. We imaged animals (N = 3) at monthly time points with CT to evaluate marker-to-lymph node spatial relationships.</div><div><h3>Results</h3><div>We observed that migration was the largest with the PMMA marker (< 10 mm) and was mitigated with the mesh and ethanol perturbations. Histomorphometry analysis of the markers revealed that a rind around the markers was formed and increased with the inclusion of mesh and ethanol.</div></div><div>We observed that migration was the largest with the PMMA marker (< 10 mm) and was mitigated with the mesh and ethanol perturbations. Histomorphometry analysis of the markers revealed that a rind around the markers was formed and increased with the inclusion of mesh and ethanol.</div><div><h3>Conclusion</h3><div>This pilot study demonstrated that marker migration could be characterized over time and different perturbations modified the amount of migration. Future studies should incorporate randomization of marker placement and larger animal cohorts.</div></div><div>This pilot study demonstrated that marker migration could be characterized over t","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"33 10","pages":"Pages 4374-4384"},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13472199/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148632527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Leadership Ceiling in Global Radiology: A 2024–2026 High-Throughput Algorithmic Audit of Gender Representation in Senior Authorship","authors":"Tanche (Jimmy) Wang MD, MSc, FRCPC, DABR","doi":"10.1016/j.acra.2026.06.059","DOIUrl":"10.1016/j.acra.2026.06.059","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>To establish a 2026 global benchmark for senior authorship gender representation in high-impact imaging journals and identify structural barriers to digital metadata visibility.</div></div><div>To establish a 2026 global benchmark for senior authorship gender representation in high-impact imaging journals and identify structural barriers to digital metadata visibility.</div><div><h3>Materials and Methods</h3><div>An algorithmic audit analyzed 6454 publications from seven leading radiology journals compiled between January 2024 and February 2026. Senior author gender was inferred utilizing the validated gender-guesser name-inference engine. Pearson’s Chi-squared test compared gender distributions across journals. A dynamic, web-based dashboard was developed using a Python-Streamlit framework to facilitate continuous, live data exploration.</div></div><div>An algorithmic audit analyzed 6454 publications from seven leading radiology journals compiled between January 2024 and February 2026. Senior author gender was inferred utilizing the validated gender-guesser name-inference engine. Pearson’s Chi-squared test compared gender distributions across journals. A dynamic, web-based dashboard was developed using a Python-Streamlit framework to facilitate continuous, live data exploration.</div><div><h3>Results</h3><div>The global female senior authorship rate across successfully classified data was established at 17.70% (1144/3717). Significant variation was found by journal (<em>x</em><sup>2</sup>=34.19, <em>p</em> < 0.0001). The <em>Journal of the American College of Radiology</em> (JACR) demonstrated the highest representation (37.17%), while technical subspecialty journals showed lower parity. A profound \"Metadata Gap\" was identified, with 42.42% (2737/6454) of the total cohort lacking identifiable gender markers or sufficient name strings in professional publishing summaries to allow for algorithmic inference.</div></div><div>The global female senior authorship rate across successfully classified data was established at 17.70% (1144/3717). Significant variation was found by journal (<em>x</em><sup>2</sup>=34.19, <em>p</em> < 0.0001). The <em>Journal of the American College of Radiology</em> (JACR) demonstrated the highest representation (37.17%), while technical subspecialty journals showed lower parity. A profound \"Metadata Gap\" was identified, with 42.42% (2737/6454) of the total cohort lacking identifiable gender markers or sufficient name strings in professional publishing summaries to allow for algorithmic inference.</div><div><h3>Conclusion</h3><div>A profound gender gap persists in global senior research leadership within imaging specialties. Enhancing publishing metadata hygiene is an essential step for accurate institutional equity tracking. Informatics-driven auditing via live dashboards provides a scalable roadmap for modern departmental and institutional accountability.</div></div><div>A pr","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"33 10","pages":"Pages 4179-4185"},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148537711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-Phase Surrogate for True Non-Contrast Liver CT Using 190-keV Monoenergetic Imaging on Photon-Counting CT: Implications for Hepatic Steatosis Assessment","authors":"Takashi Ohtani BHSc, Masato Shimada PhD, Kaede Nishiyama BHSc, Hiroki Shimoyama MD, Midori Ueda MD, Sayuri Hakoda MD, Yukihiro Tomita MD, Kenji Takata PhD, Toshiki Tateishi PhD, Tetsuya Tsujikawa PhD","doi":"10.1016/j.acra.2026.06.064","DOIUrl":"10.1016/j.acra.2026.06.064","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>To evaluate whether 190-keV virtual monoenergetic imaging (VMI) using photon-counting detector CT (PCD-CT) can serve as a surrogate for true non-contrast (TNC) in hepatic steatosis quantification and to compare its attenuation agreement with virtual non-contrast (VNC).</div></div><div>To evaluate whether 190-keV virtual monoenergetic imaging (VMI) using photon-counting detector CT (PCD-CT) can serve as a surrogate for true non-contrast (TNC) in hepatic steatosis quantification and to compare its attenuation agreement with virtual non-contrast (VNC).</div><div><h3>Methods</h3><div>Forty-nine patients who underwent abdominal PCD-CT and MRI-proton density fat fraction (PDFF) within 2 months were retrospectively analyzed. VNC and 190-keV VMI were reconstructed from equilibrium-phase scans. Liver attenuation was measured on TNC, VNC, and 190-keV VMI in four hepatic segments. Pearson correlation and Bland–Altman analyses assessed agreement with TNC. Receiver operating characteristic analysis evaluated diagnostic performance for steatosis (MRI-PDFF ≥ 5%). Statistical analyses were performed using MedCalc (version 23.4) and GraphPad Prism (version 10.6.1). Statistical significance was defined as p < 0.05.</div></div><div>Forty-nine patients who underwent abdominal PCD-CT and MRI-proton density fat fraction (PDFF) within 2 months were retrospectively analyzed. VNC and 190-keV VMI were reconstructed from equilibrium-phase scans. Liver attenuation was measured on TNC, VNC, and 190-keV VMI in four hepatic segments. Pearson correlation and Bland–Altman analyses assessed agreement with TNC. Receiver operating characteristic analysis evaluated diagnostic performance for steatosis (MRI-PDFF ≥ 5%). Statistical analyses were performed using MedCalc (version 23.4) and GraphPad Prism (version 10.6.1). Statistical significance was defined as p < 0.05.</div><div><h3>Results</h3><div>The study included 49 patients (30 men, 19 women; mean age, 66.7 ± 11.2 years). In whole-liver analysis, 190-keV VMI correlated strongly with TNC (<em>r</em>=0.921, <em>p</em><0.001), comparable to VNC (<em>r</em>=0.925). In the anterior segment, VNC showed a larger positive bias relative to TNC (+5.5 HU), whereas 190-keV VMI showed a smaller bias (+2.2 HU) that more accurately reproduced the regional attenuation pattern. For detecting steatosis in the anterior segment, a significant difference in area under the curve was observed between TNC and VNC (0.921 vs 0.817, <em>p</em>=0.018), whereas no significant difference was found between TNC and 190-keV VMI (0.921 vs 0.869, <em>p</em>=0.149).</div></div><div>The study included 49 patients (30 men, 19 women; mean age, 66.7 ± 11.2 years). In whole-liver analysis, 190-keV VMI correlated strongly with TNC (<em>r</em>=0.921, <em>p</em><0.001), comparable to VNC (<em>r</em>=0.925). In the anterior segment, VNC showed a larger positive bias relative to TNC (+5.5 HU), whereas 190-keV VMI showed","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"33 10","pages":"Pages 4265-4275"},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148537774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Perineural Invasion and Prognosis in Intrahepatic Mass-Forming Cholangiocarcinoma Using DKI and Gadoxetic Acid-Enhanced MRI-Based Texture Analysis","authors":"Qin-Yang Wu MM, Yan Shan MD, Xing-Yi Wang MM, Yi-Jun Pan MD, Chen Xu MD, Cai-Xia Fu MSc, Robert Grimm PhD, Peng-Ju Xu MD","doi":"10.1016/j.acra.2026.06.055","DOIUrl":"10.1016/j.acra.2026.06.055","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>Perineural invasion (PNI) is a critical pathological feature predictive of early recurrence and poor survival in intrahepatic mass-forming cholangiocarcinoma (IMCC), yet it remains undetectable preoperatively. This study aimed to develop a multiparametric MRI-based texture model incorporating diffusion kurtosis imaging (DKI) and gadoxetic acid-enhanced sequences for noninvasive prediction of PNI and stratification of disease-free survival (DFS).</div></div><div>Perineural invasion (PNI) is a critical pathological feature predictive of early recurrence and poor survival in intrahepatic mass-forming cholangiocarcinoma (IMCC), yet it remains undetectable preoperatively. This study aimed to develop a multiparametric MRI-based texture model incorporating diffusion kurtosis imaging (DKI) and gadoxetic acid-enhanced sequences for noninvasive prediction of PNI and stratification of disease-free survival (DFS).</div><div><h3>Materials and Methods</h3><div>A prospective study was conducted including 99 pathologically confirmed IMCC patients (31 PNI-positive, 68 PNI-negative). All patients underwent 1.5 T MRI with T1-weighted, gadoxetic acid-enhanced (arterial, portal, transitional, hepatobiliary phases), DWI, and DKI sequences. Texture and histogram features were extracted from enhanced phases and parametric maps. A radiomics signature and a clinical-radiomics model were developed using logistic regression. A prognostic index for DFS was constructed using Cox regression.</div></div><div>A prospective study was conducted including 99 pathologically confirmed IMCC patients (31 PNI-positive, 68 PNI-negative). All patients underwent 1.5 T MRI with T1-weighted, gadoxetic acid-enhanced (arterial, portal, transitional, hepatobiliary phases), DWI, and DKI sequences. Texture and histogram features were extracted from enhanced phases and parametric maps. A radiomics signature and a clinical-radiomics model were developed using logistic regression. A prognostic index for DFS was constructed using Cox regression.</div><div><h3>Results</h3><div>The radiomics signature combining AP_Contrast and DKI_K_Mean predicted PNI with an AUC of 0.766 (optimism-corrected AUC: 0.757). The clinical-radiomics model incorporating the target sign further improved the AUC to 0.837 (optimism-corrected AUC: 0.819), and decision curve analysis confirmed its clinical net benefit. A prognostic index based on microvascular invasion, TP_E.Kurtosis, and DKI_D_Std stratified DFS with an AUC of 0.742, distinguishing high- and low-risk groups with mean DFS of 10.7 vs 21.6 months (log-rank <em>P</em> = .001).</div></div><div>The radiomics signature combining AP_Contrast and DKI_K_Mean predicted PNI with an AUC of 0.766 (optimism-corrected AUC: 0.757). The clinical-radiomics model incorporating the target sign further improved the AUC to 0.837 (optimism-corrected AUC: 0.819), and decision curve analysis confirmed its clinical net benefit. A prognostic index ","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"33 10","pages":"Pages 4303-4314"},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148474056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Endovascular Treatment Of Unruptured Giant Intracranial Aneurysms With The Pipeline Embolization Device: A Multicenter Cohort Study","authors":"Jinbiao Yao MD, Yangyang Zhou MD, Hongqi Zhang MD, Tianxiao Li MD, Jianmin Liu MD, Donglei Song MD, Yuanli Zhao MD, Sheng Guan MD, Aisha Maimaitili MD, Yunyan Wang MD, Wenfeng Feng MD, Yang Wang MD, Jieqing Wan MD, Guohua Mao MD, Huaizhang Shi MD, Ying Zhang MD","doi":"10.1016/j.acra.2026.04.005","DOIUrl":"10.1016/j.acra.2026.04.005","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>To analyze the complications and mid-to-long-term results of Pipeline embolization device (PED, Covidien/Medtronic) treatment for giant intracranial aneurysms (GIAs), and identify predictors of outcomes.</div></div><div>To analyze the complications and mid-to-long-term results of Pipeline embolization device (PED, Covidien/Medtronic) treatment for giant intracranial aneurysms (GIAs), and identify predictors of outcomes.</div><div><h3>Materials and Methods</h3><div>We retrospectively analyzed the data from the PLUS registry and identified all patients with GIAs for further evaluation.</div></div><div>We retrospectively analyzed the data from the PLUS registry and identified all patients with GIAs for further evaluation.</div><div><h3>Results</h3><div>A total of 137 patients (137 GIAs) were included in this study. Of these, 118 (86.1%) were saccular, and 13 (9.5%) were located in the posterior circulation. PED-assisted coiling was performed in 96 patients (70.1%), and 20 patients (14.6%) received overlapping PED deployment. Early postoperative complications occurred in 15 patients (10.9%). The median duration of clinical follow-up was 15.0 months (IQR, 12.0–24.0). The overall complication rate was 13.1% (18/137), including 12 ischemic events and 6 hemorrhagic events. The mortality rate was 2.2% (3/137). At the final follow-up, 123 of 130 patients (94.6%) were functioning independently. Multivariable logistic regression analysis identified posterior circulation aneurysms [OR, 6.01, 95% CI: 1.40–25.78; <em>P</em>=0.016], PED deployment adjustment [OR, 4.96, 95% CI: 1.35–18.25; <em>P</em>=0.016] and diabetes [OR, 10.34, 95% CI: 1.02–104.42; <em>P</em>=0.048] as factors independently associated with overall complications. Angiographic follow-up was available for 97 patients (70.8%), with a median follow-up duration of 7.0 months (IQR, 5.0–9.0). The complete occlusion rate was 75.3% (73/97).</div></div><div>A total of 137 patients (137 GIAs) were included in this study. Of these, 118 (86.1%) were saccular, and 13 (9.5%) were located in the posterior circulation. PED-assisted coiling was performed in 96 patients (70.1%), and 20 patients (14.6%) received overlapping PED deployment. Early postoperative complications occurred in 15 patients (10.9%). The median duration of clinical follow-up was 15.0 months (IQR, 12.0–24.0). The overall complication rate was 13.1% (18/137), including 12 ischemic events and 6 hemorrhagic events. The mortality rate was 2.2% (3/137). At the final follow-up, 123 of 130 patients (94.6%) were functioning independently. Multivariable logistic regression analysis identified posterior circulation aneurysms [OR, 6.01, 95% CI: 1.40–25.78; <em>P</em>=0.016], PED deployment adjustment [OR, 4.96, 95% CI: 1.35–18.25; <em>P</em>=0.016] and diabetes [OR, 10.34, 95% CI: 1.02–104.42; <em>P</em>=0.048] as factors independently associated with overall complications. Angiographic follow-up was available ","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"33 10","pages":"Pages 4528-4536"},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147788254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of CT Acquisition Parameters on RetinaNet-Based Lung Nodule Detection: A Physics-Guided Validation Study Across Dose, Slice Thickness, and Reconstruction Kernel","authors":"Daniel Soliman MS","doi":"10.1016/j.acra.2026.06.056","DOIUrl":"10.1016/j.acra.2026.06.056","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>Computed tomography acquisition parameters, including dose level, slice thickness, and reconstruction kernel, vary substantially across clinical sites, yet artificial intelligence (AI)-assisted lung nodule detection systems are rarely evaluated against this variability. We propose and demonstrate a physics-guided framework for evaluating detection model sensitivity to systematic acquisition parameter variation.</div></div><div>Computed tomography acquisition parameters, including dose level, slice thickness, and reconstruction kernel, vary substantially across clinical sites, yet artificial intelligence (AI)-assisted lung nodule detection systems are rarely evaluated against this variability. We propose and demonstrate a physics-guided framework for evaluating detection model sensitivity to systematic acquisition parameter variation.</div><div><h3>Materials and Methods</h3><div>154 cases from the LIDC-IDRI dataset were evaluated using a Medical Open Network for AI (MONAI) RetinaNet model pretrained on LUNA16 (fold 0, no fine-tuning) across six imaging conditions: baseline, 25% dose reduction, 50% dose reduction, 3 mm slice thickness, 5 mm slice thickness, and soft kernel reconstruction. Dose reduction was simulated via image-domain Gaussian noise; slice thickness via z-axis moving average. Detection sensitivity was computed at confidence threshold 0.5 with a 15 mm matching criterion.</div></div><div>154 cases from the LIDC-IDRI dataset were evaluated using a Medical Open Network for AI (MONAI) RetinaNet model pretrained on LUNA16 (fold 0, no fine-tuning) across six imaging conditions: baseline, 25% dose reduction, 50% dose reduction, 3 mm slice thickness, 5 mm slice thickness, and soft kernel reconstruction. Dose reduction was simulated via image-domain Gaussian noise; slice thickness via z-axis moving average. Detection sensitivity was computed at confidence threshold 0.5 with a 15 mm matching criterion.</div><div><h3>Results</h3><div>Baseline sensitivity was 84.8% (95% CI: 80.2–89.8%). Soft kernel and 5 mm slice thickness produced the largest decreases: 74.3% (−10.5 pp, <em>p <</em> 0.05) and 71.6% (−13.2 pp, <em>p <</em> 0.05), respectively. Dose reduction caused moderate asymmetric degradation: 76.0% at 25% dose (−8.8 pp, <em>p <</em> 0.05) and 80.0% at 50% dose (−4.8 pp, <em>p <</em> 0.05). 3 mm slice thickness produced a small but significant reduction (−2.4 pp, <em>p</em> = 0.009). Reductions were most pronounced in the 3–6 mm range and consistent across confidence thresholds.</div></div><div>Baseline sensitivity was 84.8% (95% CI: 80.2–89.8%). Soft kernel and 5 mm slice thickness produced the largest decreases: 74.3% (−10.5 pp, <em>p <</em> 0.05) and 71.6% (−13.2 pp, <em>p <</em> 0.05), respectively. Dose reduction caused moderate asymmetric degradation: 76.0% at 25% dose (−8.8 pp, <em>p <</em> 0.05) and 80.0% at 50% dose (−4.8 pp, <em>p <</em> 0.05). 3 mm slice thickness ","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"33 10","pages":"Pages 4625-4633"},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148581127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multimodal Imaging of Tau Pathology and Network Connectivity Dynamics Across the Alzheimer’s Continuum: A Pilot Study Using Second-Generation Tracer [18F]MK6240","authors":"Sirong Piao MD, Jie Wang MD, PhD, Kun He MD, Na Wang MD, Xueling Liu MD, Liqin Yang PhD, Fang Xie MD, PhD, Yuxin Li MD, PhD, Yifang Bao MD, PhD","doi":"10.1016/j.acra.2026.06.040","DOIUrl":"10.1016/j.acra.2026.06.040","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>Alzheimer’s disease (AD) progression involves distinct spatiotemporal changes in functional connectivity (FC) within anterior-temporal (AT) and posterior-medial (PM) networks. This study characterizes FC alterations between medial temporal lobe (MTL) subregions and AT/PM networks across the AD continuum and examines their associations with tau/Aβ pathology and atrophy using second-generation tau-PET.</div></div><div>Alzheimer’s disease (AD) progression involves distinct spatiotemporal changes in functional connectivity (FC) within anterior-temporal (AT) and posterior-medial (PM) networks. This study characterizes FC alterations between medial temporal lobe (MTL) subregions and AT/PM networks across the AD continuum and examines their associations with tau/Aβ pathology and atrophy using second-generation tau-PET.</div><div><h3>Materials and Methods</h3><div>Eighty-four participants, including 26 cognitively unimpaired Aβ negative(CU Aβ-), 19 cognitively unimpaired Aβ positive (CU Aβ+), 19 mild cognitive impairment Aβ positive(MCI Aβ+), 20 AD Aβ positive(AD Aβ+) underwent 3 T MRI, resting-state fMRI, [¹⁸F]florbetapir (Aβ), and [¹⁸F]MK6240 (tau) PET. MTL subregions were segmented via ASHS-T1, while AT/PM networks were defined using Harvard-Oxford Atlas. Group differences in FC, Aβ/tau standard uptake value ratio(SUVR), and gray matter volume (GMV) were assessed. Network SUVR values, GMV and intra-FC correlation analyses and correlation coefficient matrix plots were calculated.</div></div><div>Eighty-four participants, including 26 cognitively unimpaired Aβ negative(CU Aβ-), 19 cognitively unimpaired Aβ positive (CU Aβ+), 19 mild cognitive impairment Aβ positive(MCI Aβ+), 20 AD Aβ positive(AD Aβ+) underwent 3 T MRI, resting-state fMRI, [¹⁸F]florbetapir (Aβ), and [¹⁸F]MK6240 (tau) PET. MTL subregions were segmented via ASHS-T1, while AT/PM networks were defined using Harvard-Oxford Atlas. Group differences in FC, Aβ/tau standard uptake value ratio(SUVR), and gray matter volume (GMV) were assessed. Network SUVR values, GMV and intra-FC correlation analyses and correlation coefficient matrix plots were calculated.</div><div><h3>Results</h3><div>Compared to CU Aβ-, CU Aβ+ exhibited increased intra-/inter-network FC (peak in anterior MTL: p < 0.001), while MCI/AD groups showed progressive FC declines. Posterior network FC reduction was pronounced in AD (p < 0.01). Left BA35 connectivity increased in CU Aβ+, whereas AD demonstrated FC reductions in bilateral posterior cingulate/hippocampus. Network-level A/T/N-FC correlations were integrated in CU Aβ+ but modular in AD, with strong tau-GMV anticorrelation.</div></div><div>Compared to CU Aβ-, CU Aβ+ exhibited increased intra-/inter-network FC (peak in anterior MTL: p < 0.001), while MCI/AD groups showed progressive FC declines. Posterior network FC reduction was pronounced in AD (p < 0.01). Left BA35 connectivity increased in CU Aβ+, whereas AD demonstr","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"33 10","pages":"Pages 4593-4605"},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148537727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extracellular Volume Fraction Imaging for Hepatic Fibrosis: CT and MRI Implementation and Evidence","authors":"Jialin Qi MM,&nbsp;Yubo Chi MM,&nbsp;Weiling Xu MD,&nbsp;Jingyu Wang MM","doi":"10.1016/j.acra.2026.06.002","DOIUrl":"10.1016/j.acra.2026.06.002","url":null,"abstract":"<div><div>Accurate diagnosis and staging of liver fibrosis are essential for prognostic stratification and treatment planning in chronic liver disease. However, conventional approaches for diagnosing and monitoring fibrosis, such as biopsy, elastography and serum-based scores, are limited by invasiveness, sampling variability, or performance in early-stage disease. Extracellular volume fraction (ECV) has emerged as a promising non-invasive quantitative imaging biomarker for assessing extracellular space expansion associated with hepatic fibrotic remodeling. In this review, we summarize current preclinical and clinical data on computed tomography (CT-) and magnetic resonance imaging (MRI)-derived ECV in liver fibrosis and related chronic liver diseases, with a focus on calculation methods, biologic interpretation, and correlations with histopathology and selected clinical outcomes. We also discuss major sources of heterogeneity, key interpretive limitations, and the evidence gaps that must be addressed before hepatic ECV can be more broadly integrated as a complementary component of multiparametric liver imaging.</div></div><div>Accurate diagnosis and staging of liver fibrosis are essential for prognostic stratification and treatment planning in chronic liver disease. However, conventional approaches for diagnosing and monitoring fibrosis, such as biopsy, elastography and serum-based scores, are limited by invasiveness, sampling variability, or performance in early-stage disease. Extracellular volume fraction (ECV) has emerged as a promising non-invasive quantitative imaging biomarker for assessing extracellular space expansion associated with hepatic fibrotic remodeling. In this review, we summarize current preclinical and clinical data on computed tomography (CT-) and magnetic resonance imaging (MRI)-derived ECV in liver fibrosis and related chronic liver diseases, with a focus on calculation methods, biologic interpretation, and correlations with histopathology and selected clinical outcomes. We also discuss major sources of heterogeneity, key interpretive limitations, and the evidence gaps that must be addressed before hepatic ECV can be more broadly integrated as a complementary component of multiparametric liver imaging.</div>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"33 10","pages":"Pages 4235-4245"},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148876529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National Trends in NIH Funding and Clinician-Scientist Participation Across Diagnostic Radiology, Interventional Radiology, and Radiation Oncology (2012–2025)","authors":"Ajay Malhotra MD, MMM, FACR,&nbsp;Keervani Kandala MS,&nbsp;Paul Timothy Gomez BS,&nbsp;Raj Moily MBBS, PhD, MBA,&nbsp;Dhairya A. Lakhani MD,&nbsp;Marco Colasurdo MD,&nbsp;Dheeraj Gandhi MD, FRCR,&nbsp;Cristopher Whitlow MD, PhD, MHA,&nbsp;Max Wintermark MD, MBA,&nbsp;Seyedmehdi Payabvash MD,&nbsp;Ajay Gupta MD MS","doi":"10.1016/j.acra.2026.07.035","DOIUrl":"10.1016/j.acra.2026.07.035","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Rationale and Objectives&lt;/h3&gt;&lt;div&gt;To identify trends in National Institutes of Health (NIH) funding to clinician-scientists in radiology relative to overall funding in the field, and funding in radiology sub-specialties.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;To identify trends in National Institutes of Health (NIH) funding to clinician-scientists in radiology relative to overall funding in the field, and funding in radiology sub-specialties.&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Materials and Methods&lt;/h3&gt;&lt;div&gt;Data was obtained from the NIH Research Portfolio Online Reporting Tools Expenditure and Results (RePORTER) database for NIH grants issued from 2012 to 2025 principal investigators (PIs) under “Radiation-Diagnostic/Oncology”. This was cross-linked with data from the Centers for Medicare and Medicaid Services (CMS) to identify clinician-scientists in diagnostic and interventional radiology, and radiation oncology. Grants were attributed to the specialties of all clinician PIs, including Contact PIs and multiple PIs (MPIs). Number of physicians, sex, new grants awarded, grant mechanisms and funding amounts were analyzed for the three sub-specialties.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;Data was obtained from the NIH Research Portfolio Online Reporting Tools Expenditure and Results (RePORTER) database for NIH grants issued from 2012 to 2025 principal investigators (PIs) under “Radiation-Diagnostic/Oncology”. This was cross-linked with data from the Centers for Medicare and Medicaid Services (CMS) to identify clinician-scientists in diagnostic and interventional radiology, and radiation oncology. Grants were attributed to the specialties of all clinician PIs, including Contact PIs and multiple PIs (MPIs). Number of physicians, sex, new grants awarded, grant mechanisms and funding amounts were analyzed for the three sub-specialties.&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Among 14,105 unique NIH-funded projects in the Radiation–Diagnostic/Oncology category, 437 of 3434 investigators (12.7%) across all PI roles were clinicians. Female representation among funded diagnostic radiologists increased from 11 of 64 (17.2%) in 2012 to 30 of 108 (27.8%) in 2025. Diagnostic radiologists comprised 64 of 96 funded clinicians (66.7%) in 2012 and 108 of 230 (47.0%) in 2025, and led radiation oncology in both investigator count and funding in every year. Diagnostic radiology funding rose from $39.9 million in 2012 to $87.9 million in 2025, while radiation oncology funding rose from $14.3 million to $67.3 million. Among 42 new K-series awards, radiation oncology received 28 (66.7%).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;Among 14,105 unique NIH-funded projects in the Radiation–Diagnostic/Oncology category, 437 of 3434 investigators (12.7%) across all PI roles were clinicians. Female representation among funded diagnostic radiologists increased from 11 of 64 (17.2%) in 2012 to 30 of 108 (27.8%) in 2025. Diagnostic radiologists comprised 64 of 96 funded clinicians (66.7%) in 2012 and 108 of 230 (47.0%) in 2025, and led radiation oncology in both inves","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"33 10","pages":"Pages 4189-4197"},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148707920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated Analysis of Carotid Plaque Components in CT Angiography: Performance and Prognosis in Symptomatic Carotid Stenosis Patients","authors":"Min Jie Zhao MD,&nbsp;Xiao Qing Cheng MD, PhD,&nbsp;Peng Peng Xu MD,&nbsp;Hao Tang MD,&nbsp;Peng Bo Jiang MD,&nbsp;Xin Zhang MD,&nbsp;Ling Ni MD,&nbsp;Lu Si Ying Xu MSc,&nbsp;Hui Min Pang BS,&nbsp;Jin Jing Tang BS,&nbsp;Qi Ji Jin BS,&nbsp;Chang Sheng Zhou MSc,&nbsp;Ya Liu MSc,&nbsp;Rui Liu MD,&nbsp;Hong Gao MD,&nbsp;Xiao Huan Cao MD,&nbsp;Bing Zhang MD,&nbsp;Di Jia Wu MD,&nbsp;Wu Sheng Zhu MD, PhD,&nbsp;Long Jiang Zhang MD, PhD","doi":"10.1016/j.acra.2026.06.066","DOIUrl":"10.1016/j.acra.2026.06.066","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Rationale and Objectives&lt;/h3&gt;&lt;div&gt;To develop and validate the performance and prognostic value of a deep-learning (DL) model for carotid plaque component quantification on CTA.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;To develop and validate the performance and prognostic value of a deep-learning (DL) model for carotid plaque component quantification on CTA.&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Materials and Methods&lt;/h3&gt;&lt;div&gt;A multicenter retrospective study was conducted in three stages: Stage 1: Model development and concordance analysis: A DL model was developed for plaque detection and segmentation using 2164 CTA scans (Cohort 1). DL-radiologist measurement agreement was assessed using ICC and Spearman's test (Cohort 2). Stage 2: Diagnostic validation: Performance was validated against 1) 118 co-registered CTA-OCT image pairs (Cohort 3) and 2) 146 patients with paired HR-MRI and CTA (Cohort 4). Stage 3: Prognosis validation: In 610 symptomatic patients (Cohort 5), multivariable Cox regression assessed the association between lipid core burden (LCB) and recurrent cerebrovascular events, and the incremental predictive value of LCB was quantified by ΔAUC and NRI.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;A multicenter retrospective study was conducted in three stages: Stage 1: Model development and concordance analysis: A DL model was developed for plaque detection and segmentation using 2164 CTA scans (Cohort 1). DL-radiologist measurement agreement was assessed using ICC and Spearman's test (Cohort 2). Stage 2: Diagnostic validation: Performance was validated against 1) 118 co-registered CTA-OCT image pairs (Cohort 3) and 2) 146 patients with paired HR-MRI and CTA (Cohort 4). Stage 3: Prognosis validation: In 610 symptomatic patients (Cohort 5), multivariable Cox regression assessed the association between lipid core burden (LCB) and recurrent cerebrovascular events, and the incremental predictive value of LCB was quantified by ΔAUC and NRI.&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;The DL model achieved a detection sensitivity of 0.85 with an average of 1.08 false positives per case. It demonstrated good-to-excellent agreement with radiologist assessments. In Stage 2, DL-driven lipid core component is associated with high-risk plaques identified by OCT and HR-MRI. In Stage 3, in a median 2-year follow-up, LCB independently predicted recurrent cerebrovascular events (HR: 1.08, 95% Cl: 1.03–1.13, &lt;em&gt;P&lt;/em&gt;&lt;0.001). The incorporation of LCB provided incremental risk stratification beyond clinical and CTA-driven anatomical factors (ΔAUC +0.09, NRI: 0.22, &lt;em&gt;P&lt;/em&gt;=0.001).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;The DL model achieved a detection sensitivity of 0.85 with an average of 1.08 false positives per case. It demonstrated good-to-excellent agreement with radiologist assessments. In Stage 2, DL-driven lipid core component is associated with high-risk plaques identified by OCT and HR-MRI. In Stage 3, in a median 2-year follow-up, LCB independently predicted recurrent cerebrovascular events (HR: 1.08, 95% Cl: 1.03–1.13, &lt;em&gt;P&lt;/em&gt;&lt;0.","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"33 10","pages":"Pages 4681-4693"},"PeriodicalIF":4.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148551333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}