Abstract Objective Diffusion tensor imaging (DTI) tractography of the physeal–metaphyseal complex (PMC) provides insights into skeletal maturation. Fractional anisotropy (FA) minimal and maximal thresholds of 0.15 and 1.0, respectively, are commonly used to reconstruct tracts; these values were developed for highly organized tissues and may exclude the less organized hypertrophic and transitional zones that drive growth. Whether lowering the FA thresholds better captures growth-sensitive features and correlates with annualized height velocity is unknown. Material and methods Forty-five healthy adolescents (20 boys; 12–17 years) underwent 3 T DTI of the distal femoral PMC. Deterministic tractography was performed using nine previously untested FA threshold combinations (FA_min: 0.05, 0.10, 0.15 paired with FA_max: 0.40, 0.50, 0.60) and a conventional threshold (0.15–1.0). Partial Pearson correlations between extracted metrics (tract FA, apparent diffusion coefficient [ADC], volume) and annualized height velocity were computed, controlling for Tanner stage. Results Tract ADC showed strong positive correlations with height velocity across all thresholds (r = 0.55–0.63). Tract FA showed consistent negative correlations (r = -0.38 to -0.45). Tract volume correlations were threshold-dependent: positive at lower FA_min thresholds (r = 0.33–0.37, at FA_min = 0.05) but attenuated or reversed at higher FA_min thresholds (r = -0.26, at 0.15–1.0). Conclusion Tract ADC and FA are robust metrics of growth plate activity, insensitive to FA threshold selection. Tract volume associations with height velocity are threshold-dependent, with lower FA_min thresholds capturing growth-sensitive PMC tissue and lower FA_max excluding inactive PMC tissues. These findings underscore the importance of standardized tractography parameters in growth plate DTI studies. Key Points Question How can we prevent conventional DTI FA thresholds from underestimating growth-sensitive tract volumes in the pediatric PMC? Findings Lower FA thresholds accurately capture tract volume correlations with height velocity, while tract ADC and FA correlate reliably across all thresholds. Relevance statement Optimizing FA thresholds in physeal-metaphyseal-complex DTI improves microstructural imaging correlations with height velocity, ensures reproducible data in pediatric skeletal growth studies, enhances noninvasive skeletal growth monitoring in adolescents, and potentially supplements traditional bone-age radiographs. Graphical Abstract
Most studies emphasize intratumoral diffusion-weighted imaging (DWI) metrics, but few studies have examined whether peritumoral DWI metrics can provide added value. We aimed to evaluate three-dimensional, multiscale, multimodel DWI parameters within intratumoral and peritumoral volumes of interest for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Seventy patients with HCC, including 42 with MVI, were prospectively enrolled. We calculated parameters from monoexponential, intravoxel incoherent motion, diffusion kurtosis imaging (DKI), stretched-exponential model (SEM), and continuous-time random-walk models within the tumor and in 3-mm (P3) and 5-mm (P5) peritumoral rims. Features showing differences on univariable analysis were further screened using logistic regression with variance inflation factor filtering to build combined models. Diagnostic performance was assessed by areas under the receiver operating characteristic curve (AUROC). Four intratumoral diffusion-coefficient–related metrics showed significant differences between groups. In the peritumoral regions, 12 parameters differed between groups, including diffusion-coefficient–related indices and heterogeneity-related metrics. Among single parameters, P3_DKI_Kapp achieved the best discrimination for MVI (AUROC = 0.713); P5_DKI_Kapp and Tumor_SEM_DDC were selected as independent imaging predictors. After integrating alpha-fetoprotein (AFP) and tumor size, the combined model (Cli-IntraPeriDWI) yielded the best performance (AUROC = 0.844). SHAP analysis indicated that higher AFP, larger tumor size, higher P5_DKI_Kapp, and lower Tumor_SEM_DDC were associated with increased MVI risk. Peritumoral DWI offers multiple biomarkers and outperforms intratumoral metrics for MVI prediction. An interpretable model integrating peritumoral and intratumoral DWI with clinical factors enables accurate, noninvasive preoperative MVI risk stratification in HCC. Question Can multiscale, multimodel peritumoral DWI metrics improve preoperative prediction of MVI in HCC compared with intratumoral DWI metrics? Findings Compared with intratumoral DWI, peritumoral DWI offered more potential imaging biomarkers and superior diagnostic capability for the preoperative diagnosis of MVI in HCC. Relevance statement By integrating intratumoral and peritumoral metrics with clinical risk factors, we developed a model achieving optimal performance and transparent decision interpretability for MVI assessment, supporting preoperative prognostic evaluation and individualized treatment planning in HCC.
Recent evidence highlights the limited specificity of diffusion tensor imaging (DTI) along perivascular spaces (ALPS) as a noninvasive glymphatic biomarker because microstructural tract degeneration and crossing-fiber geometry confound it. We aimed to reassess the interpretation of the DTI-ALPS index in people with focal epilepsy. Seventy-nine people with drug-resistant focal epilepsy (PWFE) underwent comprehensive presurgical work-up and 3-T magnetic resonance imaging (MRI). Etiologies included MRI-negative epilepsy, malformations of cortical development, temporal lobe epilepsy, and low-grade epilepsy-associated tumors. DTI preprocessing was conducted using QSIPrep with automated region-of-interest (ROI) placement. Linear regression models and Wilcoxon signed-rank tests were used to assess group differences and associations with clinical variables. Twenty-five age- and sex-matched healthy controls were included for comparison. Seventy-nine patients (28.6 years ± 11.3 [mean ± standard deviation]; 47 men, 32 women) and 25 healthy controls (mean age, 26.7 years ± 4.2; 11 men, 14 women) were evaluated. DTI-ALPS findings were more abnormal in lesions in proximity to the ROI (p = 0.014), implicating local white matter disruption as a modifier, which was further corroborated by reduced postoperative values. No associations were identified with disease duration, sex, or normalized gray-or white matter volumes. Our results demonstrate a distance-dependent correlation of DTI-ALPS values to the seizure onset zone in focal epilepsy, whilst no significant associations to disease duration or normalized brain volumes were found. Together, these findings suggest that local disruption of fiber tracts may act as important modifiers of this measure and warrant caution in the interpretation of the DTI-ALPS index. Question Microstructural changes may significantly confound the interpretation of the DTI-ALPS index as a surrogate parameter for glymphatic system dysfunction in epilepsy. Findings No significant differences in the DTI-ALPS index were observed comparing PWFE with healthy controls; however, lesion proximity and post-operative status significantly alter the metric. Relevance statement Local white-matter disruption and microstructural architecture may significantly alter the DTI-ALPS index; therefore, caution is warranted when interpreting the index as a glymphatic biomarker in focal epilepsy.
The diaphragm is central to respiratory mechanics and may be impaired in various diseases. Parametric magnetic resonance imaging (MRI) assessment is limited by time-consuming manual segmentation. We developed and validated fully automated diaphragm segmentation on two-dimensional (2D)-cine and three-dimensional (3D) thoracic MRI. In this single-center study, eligible adults without known diaphragmatic disorders underwent 2D-cine MRI, 3D MRI, or both. Two U-Net models (2D/3D) were trained using expert manual contours as ground truth. Performance was evaluated with normalized surface Dice (NSD) with 3-voxel tolerance and average surface distance (ASSD). In the main cohort, five blinded radiologists rated segmentation usability and image quality. An additional separate pathology cohort was assessed by two blinded readers using the same scale. Overall, 59 individuals contributed 70 MRI acquisitions: 29 women, 30 men; aged 49.3 ± 18.8 years (mean ± standard deviation). Inference required 5 s (2D) and 30 s (3D) versus 10 min and 4.5 h for manual annotation. Segmentation accuracy was high: NSD 0.95 ± 0.08 (2D) and 0.92 ± 0.06 (3D), with ASSD 1.97 ± 2.29 mm (2D) and 1.88 ± 1.97 mm (3D). In the main cohort, segmentations were rated clinically usable in 87.5
Cross-border care, teleradiology, and international referral pathways increasingly require radiology report translation, but isolated mistranslations may alter clinical meaning. We evaluated German-to-English machine translation of radiology reports and correction-based localization of text requiring review. In this retrospective study, 310 de-identified German radiology reports from June and July 2025 were translated into English with DeepL. Eight radiologists assigned 5-point quality scores and corrected perceived errors. Thirty reports were reviewed by all eight readers, and 280 reports were assigned for single-reader evaluation, yielding 520 evaluations. Automated metrics and large language model judges were tested for report-level identification of translations requiring review; a correction-based segment-level edit-prediction model was evaluated on held-out shared reports. Most translations were rated good or excellent (339/520, 65.2
