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PubMed2026

Impact of Commercial Artificial Intelligence on Radiologist Reading Time for Pulmonary Nodule Evaluation at Chest CT.

Background Chest CT is a primary method for identifying pulmonary nodules, yet interpreting scans remains time-intensive and demanding. Currently, artificial intelligence (AI) is expected to reduce reading times, but the effect of AI on reporting times in this setting is unknown. Purpose To evaluate the impact of a commercial AI software on radiologists' reading time for pulmonary nodule assessment on chest CT scans within a real-world clinical setting. Materials and Methods This retrospective study included patients who underwent chest CT examinations at a tertiary medical center between September 2021 and May 2024. The study period was divided into pre- and post-AI phases. The primary outcome was radiology reporting time. The association between AI implementation and reporting time was evaluated using a multivariable parametric Weibull shared frailty survival model adjusted for reader function, examination type, patient location, and requesting specialty, with clustering at the radiologist level. Interaction analyses assessed heterogeneity across prespecified subgroups. An exploratory extrapolation estimated projected workforce and financial impact. Results This study included 19 433 patients (mean age, 62 years ± 14.2 [SD]; 21 814 men; 39 323 chest CT examinations, 19 190 pre-AI, and 20 133 post-AI). AI implementation was associated with faster report completion (adjusted hazard ratio, 1.17; 95% CI: 1.14, 1.21; P < .001). The adjusted median reporting time decreased from 21.3 minutes pre-AI to 18.2 minutes post-AI (14.6% reduction; P < .001). Heterogeneity was observed across reader function (P < .001), examination type (P = .048), and requesting specialty (P = .03). The largest relative reductions were observed for CT thorax electrocardiogram-gated examinations (-41.1%; P < .001) and thoracic radiologists (-25.0%; P < .001), whereas emergency department examinations showed increased median reporting time (7.1%; P < .001). At institutional scan volumes (approximately 20 000-22 000 chest CT examinations annually), exploratory modeling suggested an approximate reduction of 0.5 full-time equivalent radiologist workload. Conclusion Implementation of commercial AI-assisted pulmonary nodule assessment on chest CT scans reduced radiologist reporting time in a real-world clinical setting. © The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Iwasawa in this issue.

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PubMed2026

An AI-assisted Clinical Decision Support System for Green Classification of Cystocele on Dynamic Transperineal Ultrasound.

Green classification of cystocele on dynamic transperineal ultrasound (TPUS) remains operator-dependent because it requires manual frame selection and landmark-based assessment of the Valsalva maneuver. We developed a workflow-oriented AI-assisted clinical decision support system for automated urethrovesical junction localization and dynamic Green classification and prospectively evaluated its standalone and reader-support performance. This diagnostic accuracy and reader study included 881 patients from a tertiary referral hospital, comprising a retrospective development cohort (n = 688) and an independent prospective test cohort (n = 193). A nested subset of 67 prospective patients was used for a reader study involving two junior and two intermediate radiologists under unaided and AI-assisted conditions. In the complete prospective test cohort, Green-AttGRU achieved a macro-averaged AUC of 0.939 (95% CI, 0.897-0.971) and an overall accuracy of 0.902 (95% CI, 0.860-0.943). In the reader study, overall accuracy increased from 0.761 to 0.821 without AI to 0.851-0.881 with AI, while macro-F1 increased from 0.660 to 0.777 to 0.820-0.860. Overall inter-reader agreement increased from a Fleiss' κ of 0.453 to 0.786, and pooled median interpretation time decreased from 26.7 s to 9.9 s. These findings support the preliminary feasibility of the system as a workflow-oriented decision-support tool for dynamic TPUS interpretation.

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PubMed2026

Exploring the Diagnostic Utility of Ferumoxytol for Brachial Plexus MR Neurography.

Background Ferumoxytol has been described as an alternative contrast agent for vascular suppression in MR neurography (MRN), but its diagnostic utility in patients has yet to be evaluated. Purpose To evaluate the impact of ferumoxytol on vascular suppression, nerve conspicuity, and evaluation of nerve abnormalities at three-dimensional (3D) brachial plexus MRN, compared with noncontrast and gadolinium-enhanced MRN, in participants with suspected Parsonage-Turner syndrome (PTS) or thoracic outlet syndrome (TOS). Materials and Methods This prospective study included participants who underwent 3D MRN with and/or without gadolinium chelate for clinical suspicion of PTS or TOS and subsequently underwent 3D MRN with ferumoxytol (within 3 months of the clinical examination). Two musculoskeletal radiologists qualitatively evaluated 3D short-tau inversion-recovery fast spin-echo scans for the degree of vascular suppression, nerve conspicuity, and presence of nerve abnormalities. Wilcoxon signed-rank or McNemar tests were used for comparing noncontrast and gadolinium-enhanced scans with ferumoxytol-enhanced scans. Results This study included 18 participants (mean age, 42 years ± 15.2 [SD]; 10 men). Ferumoxytol-enhanced scans demonstrated improved vascular suppression compared with both noncontrast scans (both raters, P < .001) and gadolinium-enhanced scans (both P = .04). For rater 2, ferumoxytol-enhanced acquisitions demonstrated improved conspicuity of several nerve segments relative to the noncontrast scan, including segments of the suprascapular (P = .01), axillary (P = .02), and long thoracic nerves (P = .004). The distribution of scores for these nerve segments for rater 1 also favored ferumoxytol-enhanced versus noncontrast scans, but the differences were not statistically significant (all P ≥ .06). There was no evidence of a difference in nerve conspicuity between ferumoxytol-enhanced and gadolinium-enhanced scans (P ≥ .17 for all nerve segments) and also no evidence of discrepancies in abnormal nerve findings between the acquisitions (all P ≥ .48). Conclusion Ferumoxytol improved vascular suppression compared with noncontrast and gadolinium-enhanced 3D short-tau inversion-recovery fast spin-echo sequences in brachial plexus MRN, enhancing the conspicuity of several nerve branches versus noncontrast scans, with similar detection of abnormal nerve findings. © RSNA, 2026 Supplemental material is available for this article.

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PubMed2026

Performance of Photon-counting CT for Assessing Pretreatment Breast Cancer: Comparison with Mammography, MRI, and 18F-FDG PET/CT.

Background Photon-counting CT (PCCT) offers improved spatial resolution, contrast to noise ratio, and dose efficiency, but its clinical utility remains incompletely defined for breast cancer. Purpose To evaluate the feasibility of PCCT for pretreatment breast cancer assessment through comparisons with MRI, full-field digital mammography (FFDM), and fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/CT. Materials and Methods In this prospective study (March-May 2025), female participants with breast lesions categorized as Breast Imaging Reporting and Data System 4C or higher at US or FFDM underwent breast MRI and multiphasic contrast-enhanced PCCT. 18F-FDG PET/CT was performed in a subset with locally advanced disease. Four radiologists independently evaluated lesion morphologic characteristics, additional findings, and clinical TNM stage. Agreement was analyzed using intraclass correlation coefficients (ICCs) and κ statistics. The diagnostic performance for additional lesions and nodal metastasis was compared with the reference standard (pathologic examination). Results Among 126 participants (mean age, 58.1 years ± 12.3 [SD]), interreader agreement across PCCT, MRI, and FFDM was good to excellent. PCCT agreed with MRI for lesion characterization (κ = 0.57-0.96) and clinical T categorization (κ = 0.86-0.88), with highest agreement with pathologic size (ICC, 0.70-0.81). For 46 pathologically confirmed additional lesions, PCCT was more sensitive than FFDM (difference, 44% [95% CI: 19, 66]) and similar to MRI (difference, 7% [95% CI: -5, 21]). Additionally, 44% (95% CI: 27, 52) of microcalcifications were missed at PCCT versus FFDM. For pathologically confirmed nodal metastasis, PCCT was more sensitive (difference, 10% [95% CI: 1, 20]) and accurate (difference, 6% [95% CI: 1, 11]) than MRI. For clinical N category, PCCT agreed with PET/CT (κ = 0.82 [95% CI: 0.62, 0.96]; n = 19). Two distant metastases identified at PCCT were consistent with 18F-FDG PET/CT and pathologic findings. Conclusion PCCT demonstrated similar performance to MRI for lesion characterization and detection of additional lesions, with better performance for nodal metastasis evaluation; however, detection of microcalcifications was limited. © RSNA, 2026 Supplemental material is available for this article.

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PubMed2026

Artificial intelligence-supported double reading in European population breast cancer screening: A systematic review and meta-analysis of prospective programs.

BACKGROUND: Most European population mammography screening programs rely on double reading with arbitration, a model that delivers mortality benefit but is increasingly challenged by radiologist workload, variable specificity, and interval cancers. Artificial intelligence (AI) is being evaluated to support or optimize these established European screening pathways. PURPOSE: To synthesize prospective or program-embedded evaluations of AI conducted within European-style population screening programs and to estimate exploratory program-level absolute risk differences (RDs) per 1000 examinations for cancer detection rate (CDR) and recall. MATERIALS AND METHODS: We performed a prespecified, focused evidence synthesis of three large studies embedded within routine population screening programs operating under European-relevant workflows: MASAI (randomized AI-supported risk triage within a national program), ScreenTrustCAD (prospective paired-reader evaluation with AI as an independent reader in a double-reading framework), and PRAIM (nationwide decision-referral implementation). Outcomes were harmonized as AI-control RDs per 1000 examinations. Random-effects pooling used Hartung-Knapp-Sidik-Jonkman models. For the paired-reader design, sensitivity analyses applied a Kish effective sample-size approach across plausible within-examination correlations (ρ = 0.3-0.8). Positive predictive value (PPV) and workflow/time outcomes were summarized descriptively. RESULTS: Across 597,419 examinations, the pooled CDR RD was +0.9 per 1000 (95% CI -0.0 to +1.8; I2 ≈ 12%), consistent with a modest directional increase with borderline statistical uncertainty. The pooled recall RD was -0.6 per 1000 (95% CI -3.1 to +2.1; I2 ≈ 41-43%), indicating no consistent recall increase across screening programs. Where reported, PPV was higher with AI-supported screening. Efficiency signals included 44.3% fewer total readings in MASAI and shorter reading times for AI-normal examinations in PRAIM; in PRAIM, a program-level safety-net mechanism recovered 204 cancers that would otherwise have been missed. CONCLUSION: In European population screening programs characterized by double reading and arbitration, prospective program-embedded evidence suggests that AI integration may yield a small absolute increase in cancer detection (≈1/1000) without a consistent increase in recall, alongside improved PPV and efficiency signals. These findings suggestAI primarily as a complementary reader within European screening workflows, with implementation requiring explicit quality assurance and monitoring of interval cancers and stage distribution.

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PubMed2026

Comparison of posterior cellular bonegraft options for single-level lumbar spinal fusion: a randomized trial.

BACKGROUND: Iliac bone autograft (IBG) is osteoinductive/osteogenic/osteoconductive but requires an additional harvesting procedure with known morbidities. Bone morphogenic protein (BMP) is osteoinductive and effective in obtaining fusion but is used off label for posterior fusion, has multiple side effects, and is expensive. Stem cell bone products, both auto- and allograft are attractive osteoinductive alternatives that avoid morbidity related to the graft donor site and may have a better safety profile than BMP. Morcelized allograft bone is osteoconductive but not osteoinductive or osteogenic. PURPOSE: Evaluate and compare the effectiveness of 6 types of viable or osteoinductive bone graft material in obtaining a solid posterior spinal fusion (PSF) for single level anterior/posterior lumbar spinal fusion. The bone grafts were IBG, BMP, autogenous stem cells (MSC) from concentrated bone marrow aspirate (BMA), allograft MSC from bone marrow, adipose tissue, or amniotic fluid, combined with inert cancellous allograft (Allo). STUDY DESIGN/SETTING: Prospective, single-blinded randomized study of 6 cohorts and inert historical control. PATIENT SAMPLE: Elective anterior-posterior lumbar spinal fusion of 175 patients. OUTCOME MEASURES: Assessments included pre and postoperative back and leg pain (VAS) scores, pain drawing, disability (ODI) scores, pain medication usage, and 1-year postoperative thin-cut CT scans (read by blinded radiologists). METHODS: Patients who were surgical candidates for a 1-level anterior/posterior lumbar fusion were randomized to 1 of 6 types of posterior bone graft alternatives: IBG, BMP, BMA, allograft MSC derived from bone marrow combined with morcelized Allo (cAlloBone), adipose derived MSC combined with morcelized Allo (cAlloFat), or amnion derived MSC combined with morcelized Allo (cAlloAm). Historical Allo patients served as a negative control group. Each group (n 27) had prospective outcomes and were followed for a minimum of 2 years. Fusion rate and outcomes were compared and referenced to Allo group. RESULTS: All but 5 patients had a solid ASF. The posterior fusion rates were 98% for IBG, 94% for BMP, 85% for BMA, 67% for cAlloBone, 64% for cAlloFat, 62% for cAlloAm, and 50% for Allo. Outcomes were significantly improved for all measures for all groups and there was no difference between groups except cAlloFat had slightly greater improvement in back pain in the 7-12 month follow-up period. BMP was the most expensive graft material; cellular allografts had a high-cost relative to fusion rate. CONCLUSIONS: For single level ASF/PSF, the PSF fusion rate was significantly greater for IBG and BMP followed by BMA. Various allograft MSC bone graft options resulted in lower fusion rates but may be greater than Allo. Outcomes were uniformly improved regardless of the type of graft used or the fusion status of the posterior fusion as long as the interbody fusion was solid. If bone graft cost savings is a consideration for PSF, then IBG has the greatest radiographic value, and Allo the greatest clinical value as long as the anterior interbody fusion is solid.

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