Insights into Imaging最新文献

{"title":"Performance of dual-layer spectral CT-based extracellular volume fraction to assess Ki-67 proliferation status in rectal cancer: comparison with diffusion kurtosis imaging.","authors":"Zhuofeng Liang, Danfeng Wang, Liyan Tang, Fengping Chen, Anni Pan, Xiaohua Du, Xiaomin Liu, Zhijie Huang, Xian Liu, Weicui Chen","doi":"10.1186/s13244-026-02376-4","DOIUrl":"10.1186/s13244-026-02376-4","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate and compare MRI-based diffusion kurtosis imaging (DKI), diffusion-weighted imaging (DWI), and dual-layer spectral CT (DLSCT)-derived extracellular volume (ECV) fraction for predicting the Ki-67 proliferation index in rectal cancer (RC).</p><p><strong>Materials and methods: </strong>This retrospective study included 117 patients with pathologically confirmed rectal adenocarcinoma who underwent preoperative MRI and DLSCT. Patients were divided into high (Ki-67 > 50%) and low (Ki-67 ≤ 50%) Ki-67 groups based on postoperative immunohistochemistry. Parameters from DKI (mean diffusivity (D_mean), mean kurtosis [K_mean]), DWI (apparent diffusion coefficient [ADC]), and ECV fraction were calculated and compared. Diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). Correlations with Ki-67 were evaluated using Spearman's coefficient.</p><p><strong>Results: </strong>The high Ki-67 group exhibited significantly higher K_mean and ECV fraction, and lower D_mean and ADC values (all p < 0.05). K_mean and ECV showed positive correlations with Ki-67, while ADC showed a negative correlation. ROC analysis demonstrated that ECV fraction provided the optimal diagnostic efficacy (AUC = 0.815), which was significantly better than ADC (AUC = 0.665), D_mean (AUC = 0.641), K_mean (AUC = 0.721), and combined DKI parameters (AUC = 0.744). DCA confirmed a favorable net benefit for the ECV fraction. Additionally, ECV was associated with key pathological and staging features, like T-stage, N-stage, extramural venous invasion, and other aggressive pathological features.</p><p><strong>Conclusion: </strong>DLSCT-derived ECV fraction demonstrated superior performance to diffusion-based MRI parameters for predicting the proliferation status of RC, providing a more comprehensive assessment of the tumor microenvironment.</p><p><strong>Key points: </strong>Question Noninvasive preoperative biomarkers are lacking to assess Ki-67 proliferation status and guide personalized treatment strategies for patients with rectal cancer. Findings Dual-layer spectral CT (DLSCT)-derived extracellular volume (ECV) fraction outperformed MRI diffusion parameters for Ki‑67 and correlated with T/N stage, differentiation, and extramural vascular invasion. Critical relevance statement This study validates Dual-layer spectral CT (DLSCT)-derived extracellular volume (ECV) fraction as a non‑invasive biomarker that outperforms MRI diffusion parameters for Ki‑67 assessment and correlates with tumor aggressiveness, advancing personalized treatment decision‑making in rectal cancer radiology.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13522283/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148839983","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":"A contrast-enhanced CMR-based risk score integrating microvascular obstruction and intramyocardial hemorrhage extent for prognostic evaluation.","authors":"Xing-Yu Gu, Ting-Xuan Yin, Ling-Yi Yu, Jin-Yu Zheng, Ming-Lei Li, Yan Zhou, Jun Pu, Jin-Yi Xiang, Jing-Ping Wu, Lian-Ming Wu","doi":"10.1186/s13244-026-02386-2","DOIUrl":"10.1186/s13244-026-02386-2","url":null,"abstract":"<p><strong>Objectives: </strong>This study aims to compare the prognostic value of the extent of microvascular obstruction (MVO) combined with intramyocardial hemorrhage (IMH) for major adverse cardiovascular events (MACE) in patients with STEMI.</p><p><strong>Materials and methods: </strong>We analyzed 568 STEMI patients in this retrospective multicenter study. Microvascular injury was visualized using late gadolinium enhancement for MVO, and T2* mapping and T2-weighted cardiovascular magnetic resonance imaging for IMH. The Youden index was used as the cutoff value to divide the study population into four groups. The Eitel CMR risk score, Glasgow CMR risk score, and GRACE (Global Registry of Acute Coronary Events) score were used as references to form Scores 1 and 2. Score 3 included LVEF ≤ 45%, MVO > 1.06% LV, IMH > 0.47% LV, and the GRACE score.</p><p><strong>Results: </strong>During a median follow-up of 3.1 years (IQR: 1.7-5.0 years), 108 patients (19%) experienced MACE. Event rates increased stepwise across groups (8.8% to 58.3%). The combination of MVO > 1.06% LV and IMH > 0.47% LV emerged as the strongest predictor of MACE (HR: 9.646, 95% CI: 6.327-14.705 [p < 0.001]). Score 3 (integrating GRACE score, LVEF, and quantitative MVO and IMH) demonstrated improved predictive performance for MACE compared to the GRACE score (AUC: 0.748), Score 1 (AUC: 0.825), and Score 2 (AUC: 0.802), achieving an AUC of 0.853.</p><p><strong>Conclusion: </strong>Our approach integrates quantitative information on MVO and IMH into a risk score that shows better prognostic value than established risk scores.</p><p><strong>Key points: </strong>Question Current prognostic tools for ST-elevation myocardial infarction patients lack quantitative combined assessment of microvascular obstruction and intramyocardial hemorrhage, limiting precise risk stratification after reperfusion. Findings A novel cardiac magnetic resonance score integrating quantitative microvascular obstruction and intramyocardial hemorrhage extent achieved 0.853 area under the curve for major adverse cardiovascular events. Critical Relevance Statement This study develops a quantitative cardiac magnetic resonance risk score by integrating microvascular obstruction and intramyocardial hemorrhage, offering improved prognostic value for major adverse cardiovascular events in ST-elevation myocardial infarction patients over established clinical scores.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13522271/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148839763","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":"Automated 3D chest CT muscle segmentation-derived model development and explanation in discrimination of normal, preserved ratio impaired spirometry, and COPD: a multicenter study.","authors":"Yi Wang, Weihao Zhai, Qian Zhou, Xiuxiu Zhou, Yueze Li, Taohu Zhou, Xin'ang Jiang, Qianxi Jin, Yanming Ge, Peng Dong, Ruoyao Wang, Shiyuan Liu, Li Fan","doi":"10.1186/s13244-026-02384-4","DOIUrl":"10.1186/s13244-026-02384-4","url":null,"abstract":"<p><strong>Objectives: </strong>To develop and validate an automated 3D chest CT muscle segmentation model using an exploratory normalization method to discriminate normal, preserved ratio impaired spirometry (PRISm), and chronic obstructive pulmonary disease (COPD) subjects.</p><p><strong>Materials and methods: </strong>In this retrospective study, we used TotalSegmentator to acquire 3D pectoral muscle (PM) and erector spinae muscle (ESM) volumes from chest CT, normalizing them to height and vertebral bone volume, respectively. 2D quantitative parameters were acquired and normalized. The support vector machine models were developed based on normalized 3D and 2D muscle parameters, respectively, with ten-fold cross-validation. Receiver operating characteristic curves were used to analyze the discriminative performance of models, and the SHapley Additive exPlanations algorithm was used to quantify the importance of each parameter.</p><p><strong>Results: </strong>1660 subjects (616 normal, 646 PRISm, 398 COPD) (median age, 66 years [IQR: 60-72 years]; 1014 males) were included and divided into training set (n = 1162), test set (n = 498). In the test set, the 3D model (macro-average AUC, 0.735; micro-average AUC, 0.733) outperformed the 2D model (macro-average AUC, 0.646; micro-average AUC, 0.665), and 3D ESM density was the most relevant muscle parameter. 3D muscle density showed a decreasing trend from normal to PRISm to COPD. In COPD, females exhibited decreased density (difference range: -14.48 to -7.79; p < 0.001), while males had a more significant decrease in volume, especially pectoralis major volume index (difference: -11.18; 95% CI -15.57, -5.08; p < 0.001).</p><p><strong>Conclusions: </strong>The 3D muscle parameter model demonstrated higher discriminative performance than the 2D model for discriminating normal, PRISm, and COPD subjects.</p><p><strong>Key points: </strong>Question The discriminative performance of 3D CT-based muscle quantification in subjects with impaired pulmonary function remains unclear. Findings 3D muscle analysis achieved superior discrimination of normal, PRISm, and COPD subjects, with density-related parameters showing consistent group differences, particularly ESM density. Critical relevance By comparison with conventional 2D assessment, 3D CT-based muscle quantification showed better discrimination of normal, PRISm, and COPD, which might advance the personalized precision and comprehensive assessment, including muscle alteration for subjects with impaired pulmonary function.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13522301/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148839811","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":"Perceived communication quality of a standardized neuroradiology report following AI-based simplification: a randomized, blinded study.","authors":"Agreen Horr, Isabella Luisa Walther, Alexandra Bonietzki, Tim-Christian Piesch, Sönke Peters, Mehmet Mert Sarikaya, Svea Seehafer, Olav Jansen, Patrick Langguth, Schekeb Aludin","doi":"10.1186/s13244-026-02391-5","DOIUrl":"10.1186/s13244-026-02391-5","url":null,"abstract":"<p><strong>Objectives: </strong>Radiology reports are primarily written for professional communication and may be difficult for patients to understand. We investigated whether AI-based simplification of a single standardized neuroradiology report improves participant-rated communication quality compared with a conventional professional-language report.</p><p><strong>Materials and methods: </strong>In this prospective, randomized, blinded study, 100 adults received either an AI-simplified or a conventional report based on the same standardized neuroradiology case. Two board-certified radiologists reviewed the simplified version before evaluation. Participants rated clarity and structure, tone and trust, usability, and overall impression on structured 5-point scales. No objective comprehension test was performed. Group differences were assessed using Welch's t-tests, with effect sizes reported as Cohen's d; Mann-Whitney U-tests served as sensitivity analyses. Open-ended responses were analyzed qualitatively.</p><p><strong>Results: </strong>Participants rated the AI-simplified report more favorably across all domains (all p < 0.001). Effect sizes were large to very large, ranging from d = 1.31 for Tone and Trust to d = 2.10 for Overall Impression. Nonparametric sensitivity analyses confirmed all group differences. Qualitative responses likewise emphasized clearer explanations, simpler language, and improved structure.</p><p><strong>Conclusion: </strong>In this single standardized neuroradiology case, AI-based simplification improved participant-rated communication quality. Studies using multiple cases and outputs should determine whether such perceived improvements translate into objective comprehension, recall, decision-making, and clinically meaningful communication benefits.</p><p><strong>Key points: </strong>Question Can radiologist-reviewed AI simplification address the communication gap by improving perceived communication quality of a standardized neuroradiology report compared with a conventional professional-language report? Findings In this randomized study with concealed AI involvement, the AI-simplified report received higher ratings across all four participant-rated communication domains. Critical relevance statement In a standardized neuroradiology report, AI-based simplification improved perceived communication quality, supporting further evaluation of patient-facing report explanations as adjuncts to conventional reports with explicit quality-assurance criteria.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13522326/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148839960","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":"AI performance varies considerably across mammography devices: a multi-site and multi-vendor retrospective study.","authors":"Marcel Blum, Rudolf Morant, Alena Eichenberger, Alexander Geissler, Jonas Subelack, Justus Vogel, David Ehlig","doi":"10.1186/s13244-026-02383-5","DOIUrl":"10.1186/s13244-026-02383-5","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate an artificial intelligence (AI) algorithm on three different mammography devices and assess screening performance using general and device-specific thresholds.</p><p><strong>Materials and methods: </strong>This retrospective study analyzed 22,673 AI-assessed mammographies of women aged 50-69 collected in 2022-2023 from three mammography devices across six screening sites within a Swiss Mammography Screening Program. 115 screen-detected and 15 1-year interval breast cancers were included in the analyses. A commercially available AI algorithm assessed each mammography with a numeric case score. Optimal thresholds were determined across all devices and for each device separately using the Youden-Index. Screening performance was assessed using sensitivity, specificity, balanced accuracy, and cancer detection rate (CDR).</p><p><strong>Results: </strong>Standard double-reading had a CDR of 5.07 (95% CI: 4.19-6.09). Using AI with a general threshold achieved a CDR of 4.81 (95% CI: 3.95-5.80), which was enhanced using device-specific thresholds to 4.90 (95% CI: 4.03-5.89). Workload for radiologists in consensus conferences was lowered by nearly one-third when using device-specific thresholds compared to a general threshold (p < 0.001). Nonetheless, AI screening performance for one of the mammography devices was poor even with device-specific thresholds.</p><p><strong>Conclusion: </strong>AI-based performance varied considerably among the three mammography devices, emphasizing the need for device-specific thresholds or even the withdrawal of AI use on certain devices. Awareness of different case distribution among radiologists should be raised to mitigate the risk of interpretation biases and reduced diagnostic accuracy. Lastly, training datasets must be representative not only of the target population but also of the different screening devices used in practice.</p><p><strong>Key points: </strong>Question AI performance may vary across mammography devices, raising uncertainty about device-independent thresholds. Findings AI scores differed considerably across devices, indicating the need for device-specific thresholds, but performance on one device remained poor. Critical relevance The performance of an AI algorithm in mammography screening depends on adequately defined decision thresholds, and radiologists must be aware that AI scores can vary across mammography devices to avoid interpretation biases and to maintain diagnostic accuracy.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13518669/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148827912","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":"Enhancing risk prediction for sudden cardiac death: quantitative late gadolinium enhancement analysis in hypertrophic cardiomyopathy.","authors":"Lili Wang, Hongbo Zhang, Guanyu Lu, Junjie Zhou, Zhihui Lu, Lanling Wang, Chen Zhang, Xiaohai Ma, Shuang Li, Lei Zhao","doi":"10.1186/s13244-026-02385-3","DOIUrl":"10.1186/s13244-026-02385-3","url":null,"abstract":"<p><strong>Objectives: </strong>To assess the prognostic value of multiple late gadolinium enhancement (LGE) quantification methods for sudden cardiac death (SCD) prediction in hypertrophic cardiomyopathy (HCM).</p><p><strong>Materials and methods: </strong>In this single-center retrospective study, 617 HCM patients who underwent cardiac magnetic resonance (CMR) examinations were consecutively enrolled. LGE was quantified using the n-standard deviation (SD) technique (with multiple thresholds) and the full width at half maximum method. \"Gray zone\" was defined as the myocardium with signal intensity between two predefined thresholds on LGE images. The primary outcome was SCD or aborted SCD.</p><p><strong>Results: </strong>Among 617 HCM patients, 424 (68.7%) were male, mean age was 49.1 ± 14.0 years, and LGE was identified in 438 (71.0%). During 67.9 ± 21.0 months of follow-up, 24 patients (3.9%) reached the primary endpoint. All dual-threshold gray zone measures and five single-threshold LGE quantifications (2-6 SDs) independently predicted SCD (HR range: 1.031-1.220, all adjusted p < 0.05). Gray zone (HR range: 1.091-1.220) showed stronger associations than single-threshold LGE measures (HR range: 1.031-1.046). Both approaches improved discrimination beyond the composite American Heart Association (AHA)/American College of Cardiology (ACC) model, with increased net reclassification improvement (0.321 and 0.397, respectively) and comparable C-statistics (0.794-0.871 vs 0.794-0.898, p = 0.155).</p><p><strong>Conclusion: </strong>While conventional single-threshold LGE quantification predicts SCD in HCM, dual-threshold gray-zone analysis demonstrates stronger associations. Both approaches provide incremental prognostic value beyond the AHA/ACC guideline-based risk model. These findings underscore the importance of standardizing LGE quantification to improve SCD risk stratification in patients with HCM.</p><p><strong>Key points: </strong>Question: The optimal LGE quantification approach for SCD risk stratification in HCM remains uncertain.</p><p><strong>Findings: </strong>Both single- and dual-threshold LGE quantification independently predict SCD in patients with HCM, while dual-threshold gray zone metrics demonstrate stronger prognostic associations. Critical Relevance: By systematically comparing multiple LGE quantification approaches, this study highlights the impact of methodological variability on SCD risk stratification in HCM, underscores the need for standardized LGE assessment, and informs clinical radiology practice.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13518643/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148827871","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":"Detection of residual fibroglandular tissue on breast MRI and associated factors in women treated with mastectomy and DIEP flap breast reconstruction.","authors":"Nieke N P M Smeins, Joep A F van Rooij, Esther M Heuts, Janneke B Houwers, Patty J Nelemans, Stefania M H Tuinder, Thiemo J A van Nijnatten","doi":"10.1186/s13244-026-02382-6","DOIUrl":"10.1186/s13244-026-02382-6","url":null,"abstract":"<p><strong>Objectives: </strong>This study investigates the frequency, extent and location of residual fibroglandular tissue (RFGT) on breast MRI after mastectomy and deep inferior epigastric perforator (DIEP) flap reconstruction. Possible risk factors for RFGT and the association with local breast malignancy after mastectomy (i.e. local recurrence or new primary tumour) are explored.</p><p><strong>Materials and methods: </strong>This retrospective, single-centre study included patients after mastectomy followed by DIEP flap reconstruction, who underwent breast MRI during follow-up between 2007 and 2022. Breast MRI exams were reassessed for the presence, diameter and location of RFGT. Relative risk was calculated to identify associated factors for RFGT. To investigate the possible association with malignancy after mastectomy, an explorative survival analysis was performed.</p><p><strong>Results: </strong>Seventy-three patients were included (mean age 45 years, range 21-68), of which 66 were diagnosed with breast cancer. RFGT was detected in twenty (27.4%) patients, with a mean diameter of 13.5 mm (range 6-31), most frequently located in the upper outer quadrant of the breast. Tumour grade 3 seemed to be associated with increased risk of RFGT (RR = 2.7, 95% CI: 1.1-6.6, p = 0.050). After a median follow-up time of 110.0 months (range 14-354), malignancy after mastectomy had occurred in thirteen patients; this risk was non-significantly higher in patients with RFGT (HR = 2.3, 95% CI: 0.769-6.827, p = 0.137).</p><p><strong>Conclusion: </strong>RFGT is frequently detected on breast MRI after mastectomy and DIEP flap reconstruction. A baseline postoperative breast MRI exam could possibly be relevant to detect RFGT. The potential association with higher risk of malignancies after mastectomy warrants further investigation.</p><p><strong>Key points: </strong>Question research on RFGT detection after autologous reconstruction remains limited; therefore, this study investigates RFGT extent, location, risk factors, and association with malignancy. Findings RFGT could be detected on breast MRI in 27.4% of patients after DIEP flap reconstruction and might potentially be associated with an increased post-mastectomy malignancy risk. Critical relevance RFGT can frequently be detected on breast MRI following mastectomy and DIEP flap reconstruction and might be relevant for oncological safety. Future research is needed to validate this and assess the value of a postoperative baseline breast MRI for RFGT detection.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13518751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148827894","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 angular trajectory of the vestibular aqueduct: evaluation using photon-counting CT.","authors":"Frederik Van den Kerkhof, Lukas Boomgaert, Lesley Cockmartin, Robert Hermans","doi":"10.1186/s13244-026-02372-8","DOIUrl":"10.1186/s13244-026-02372-8","url":null,"abstract":"<p><p>The angular trajectory of the vestibular aqueduct (ATVA) has been proposed as a radiographic marker for developmental endotypes of Menière's disease. Current ATVA measurements rely on software-based proxies because the proximal vestibular aqueduct is often below the spatial resolution of conventional CT. Photon-counting CT (PCCT) may allow direct visualization of the proximal trajectory and enable patient-specific ATVA measurement. In this retrospective study, PCCT temporal bone scans from 64 patients (128 ears) were analyzed, and ATVA was measured directly by two independent readers, alongside additional VA morphometric parameters. The mean ATVA (106.9° ± 11.7°) was consistent with previously reported values, suggesting that PCCT can approximate established measurements without relying on geometric proxies. However, reproducibility was poor: interobserver agreement for ATVA was low (ICC = 0.24), and intra-observer agreement varied markedly between readers (ICC = 0.80 vs. 0.27). This variability can be related to subjective line placement, the curved anatomy of the VA, and the need to integrate information across multiple image slices. In contrast, midpoint VA diameter measurements, particularly in the Pöschl plane, demonstrated moderate to good reproducibility. Methodological standardization, such as the use of individualized oblique reconstructions or minimum intensity projections, may improve the reliability of ATVA measurements. Alternatively, other surrogate markers, such as the retrolabyrinthine bone thickness, may provide superior reproducibility while maintaining clinical relevance for endotype differentiation. Overall, despite enabling direct visualization, the current PCCT-based ATVA assessment is limited by poor reproducibility and requires methodological refinement for routine clinical implementation. KEY POINTS: •Question Photon-counting CT can directly assess the angular trajectory of the vestibular aqueduct for Menière's disease endotyping, avoiding software-based proxies used as conventional CT cannot resolve its proximal anatomy. •Findings Photon-counting CT showed a mean ATVA of 106,9°, comparable to values previously reported in the literature, but with poor inter-reader agreement. •Critical relevance statement Photon-counting CT enables direct patient-specific assessment of the angular trajectory of the vestibular aqueduct and may support clinically meaningful endotype categorization in Menière's disease.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13507003/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148818286","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":"Technical challenges in establishing local native T1 reference ranges in cardiac MRI: a critical review.","authors":"Maheran Che Ha, Khairil Amir Sayuti, Yusri Mohammed, Mardhiyati Mohd Yunus, Nurisya Mohd Shah, Mohd Mustafa Awang Kechik, Mohammad Johari Ibahim, Muhammad Khalis Abdul Karim","doi":"10.1186/s13244-026-02370-w","DOIUrl":"10.1186/s13244-026-02370-w","url":null,"abstract":"<p><p>Establishing local reference ranges for native T1 in healthy myocardium is critical in cardiac magnetic resonance imaging (CMR) for the accurate detection of myocardial fibrosis and other tissue abnormalities. However, native T1 measurements vary widely and are sensitive to technical factors such as the magnetic field strength, static magnetic field (B0) and radiofrequency (B1) homogeneities, differences in MRI scanners across various vendors, imaging protocols, and specific acquisition parameters employed. These variabilities have consequently hindered the direct comparison of T1 values across different studies and centers. This review aims to evaluate the main technical challenges and methodological inconsistencies that impact the establishment of local native T1 reference ranges in CMR, and review proposals for mitigation, harmonization, and standardization strategies designed to enhance comparability across CMR platforms. A comprehensive literature search was conducted focusing on myocardial native T1 mapping using the modified Look-Locker inversion recovery (MOLLI) technique and its variants, as well as on alternative T1 mapping sequences like ShMOLLI, SASHA, SMART1Map, and SAPPHIRE. Reported native T1 values in healthy myocardium were found to be inconsistent across studies, driven by differences in the magnetic field strength, static magnetic field (B0), and radiofrequency (B1) homogeneities, and vendor-specific hardware and software configurations. Standardization of T1 mapping protocols, including standardized imaging parameters and vendor-specific reference adjustment, is therefore necessary to improve the comparability and reliability of myocardial T1 values across CMR centers. In addition, a robust quality assurance (QA) program and effective quality control (QC) measures are pivotal in ensuring the reliability and consistency of the measurements. KEY POINTS: Question How do technical factors and scanner-specific variabilities hinder the establishment of reliable local native T1 reference ranges for accurate myocardial tissue characterization? Findings Standardization of acquisition parameters, vendor-specific benchmarks, and robust quality assurance programs effectively minimize inter-scanner variability, ensuring reliable and comparable native myocardial T1 measurements across centers. Critical relevance statement This review identifies technical drivers of T1 variability and proposes a standardization framework, enabling clinicians to establish accurate local reference ranges and improve diagnostic comparability across diverse platforms in clinical radiology practice.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13504065/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148812958","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":"Super-resolution MRI and 2.5D deep learning for intratumoral-peritumoral radiomics in preoperative prediction of rectal cancer perineural invasion.","authors":"Yuhang Wang, Dandan Dong, Shengming Shi, Yupeng Wu, Apekshya Singh, Jiayi Xie, Qiuyang Chen, Jianwei Zhu, Xiaofu Li","doi":"10.1186/s13244-026-02365-7","DOIUrl":"10.1186/s13244-026-02365-7","url":null,"abstract":"<p><strong>Objectives: </strong>Preoperative prediction of perineural invasion (PNI) in rectal cancer (RC) is challenging due to limited MRI resolution and the neglect of extramural microenvironmental features. We developed a noninvasive framework integrating super-resolution MRI, 2.5D deep learning (DL), and intratumoral-peritumoral radiomics for preoperative PNI prediction.</p><p><strong>Materials and methods: </strong>A dual-center cohort of 312 RC patients with pathologically confirmed PNI status was analyzed. Preoperative MRI underwent 4× super-resolution reconstruction using a generative adversarial network (GAN) to enhance tissue definition. Radiomic features were extracted from the tumor and peritumoral regions (1-5 mm). For the 2.5D DL model, the largest tumor cross-section and adjacent axial slices served as multichannel inputs to a ResNet101 backbone using transfer learning. Slice-level features were aggregated to patient-level predictions via multi-instance learning (MIL). Feature selection employed univariate analysis, Pearson correlation, mRMR, and LASSO regression. Model performance was validated via 5-fold cross-validation and an external testing cohort.</p><p><strong>Results: </strong>The combined model, integrating MIL features, intratumoral radiomics, the optimal (2-mm) peritumoral radiomics, and clinical variables, achieved an area under the curve (AUC) of 0.912 (95% CI: 0.850-0.974) on internal validation and 0.868 (95% CI: 0.783-0.952) on external testing. Gradient-weighted class activation mapping (Grad-CAM) highlighted the tumor-neural interface, and tumor length was an independent predictor of PNI (OR = 1.062, p = 0.032).</p><p><strong>Conclusion: </strong>We propose a hybrid radiomic-DL framework leveraging super-resolution MRI and 2.5D spatial context to enhance preoperative prediction of PNI in RC. The model shows potential for risk stratification to support personalized neoadjuvant therapy decisions, with external testing suggesting promising generalizability.</p><p><strong>Key points: </strong>Question How can super-resolution MRI and 2.5D deep learning address the limitations of conventional imaging in predicting preoperative rectal cancer perineural invasion? Findings The integrated framework achieved an external testing AUC of 0.868, demonstrating superior performance compared to standalone radiomics and deep learning models. Critical relevance statement This study demonstrates a noninvasive framework integrating super-resolution MRI and 2.5D deep learning with intratumoral-peritumoral radiomics, offering a novel approach for preoperative rectal cancer perineural invasion prediction and potential assistance in personalized neoadjuvant therapy decisions.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13499786/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148792702","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}