PURPOSE:The purpose of this study was to compare, across readers with varying experience, the characterisation of prostate MRI lesions as grade group (GG) ≥ 2 cancer, by using the PI-RADS version 2.1 (PI-RADSv2.1) score alone and by combining prostate specific antigen density (PSAd), the PI-RADSv2.1 score and the output of a radiomics-based algorithm (Q-CAD). MATERIALS AND METHODS:The MULTI database in which 21 readers (seven experienced seniors, seven less-experienced seniors, seven juniors) had assigned a PI-RADSv2.1 score to 240 prostate MRI lesions was retrospectively used. The lesions were outlined by two independent experts to compute their Q-CAD score. For each reader, four biopsy strategies were simulated. PI-RADS3 and PI-RADS4 strategies triggered biopsy in PI-RADSv2.1 ≥ 3 and PI-RADSv2.1 ≥ 4 lesions respectively. Combined3 and Combined4 strategies triggered biopsy when at least two of the following conditions were fulfilled: positive PI-RADSv2.1 score (≥ 3 for Combined3; ≥ 4 for Combined4), positive Q-CAD score (≥ 0.45 in peripheral zone; ≥ 0.79 in transition zone), PSAd ≥ 0.15 ng/mL/cm3. RESULTS:A total of 232 lesions were included. Using lesions' delineations by Expert 1 for the three readers' experience groups, the Combined3 strategy was significantly less sensitive for GG ≥ 2 cancers (87-88% vs. 91-96%; P = 0.026 to < 0.001), but significantly more specific (45%-55% vs. 15%-34%; P < 0.001) than the PI-RADS3 strategy. The Combined4 strategy was less sensitive than the PI-RADS4 strategy (84%-86% vs. 85%-91%) but the difference was significant only for less-experienced seniors (P = 0.023); it was significantly more specific (51%-63% vs. 27%-50%; P < 0.001) in all groups. The Combined4 strategy provided the highest net benefit for risk thresholds >12%-16%. Using lesions' delineations by Expert 2 yielded similar results. CONCLUSION:The combined strategies significantly increased specificity, at the cost of slightly reducing sensitivity for GG ≥ 2 cancers.
PURPOSE:The purpose of this study was to compare the image quality and lesion detection between ultra-low dose (ULD) chest-abdomen-pelvis computed tomography (CAP-CT) reconstructed with a deep-learning image reconstruction (DLR) algorithm, and standard-dose CT (STD-CT) in cancer follow-up. MATERIALS AND METHODS:A total of 106 patients undergoing CAP-CT for the follow-up of cancer were prospectively included. Each patient underwent both STD-CT and ULD-CT acquisitions. ULD-CT images were reconstructed using two DLR levels (Smooth/Smoother). Dosimetric indicators, objective image quality, subjective image quality, and lesion detection were compared. Agreement between protocols and readers was assessed using Gwet's AC1 or AC2 coefficients. RESULTS:ULD-CT significantly reduced radiation exposure, with a mean CTDIvol reduction of -71.5% and dose-length product reduction of -71.5% (P < 0.05). Minor but statistically significant differences in HU values were observed between STD-CT and ULD-CT across most tissues. For all organs or tissues, image noise was significantly higher with ULD-CT-Smooth than with STD-CT (P < 0.001), and with ULD-CT-Smoother than with STD-CT, except for dorsal vertebra (P = 0.39) and trachea (P = 0.26). For all organs or tissues, image noise was significantly lower with the Smoother DLR level than with Smooth DLR level (P < 0.001). Agreement between STD-CT and ULD-CT regarding lesion detection was almost perfect for thoracic, abdominal, and bone lesions. Detection of infracentimetric hepatic was lower with ULD-CT, whereas detection of larger lesions (≥ 10 mm) remained similar. Subjective image quality was lower with ULD-CT, with moderate inter-reader agreement, and lower diagnostic confidence than with STD-CT. One of the two readers considered that 19%-24% of ULD-CT examinations were uninterpretable. CONCLUSION:ULD-CT with DLR offers substantial radiation dose reduction but resulted in poorer image quality and lower detection of small low-contrast abdominal lesions compared with STD-CT. Although lesion detection remained equivalent for thoracic and skeletal lesions, the high proportion of suboptimal or uninterpretable examinations may limit routine use of ULD protocols in cancer follow-up.
PURPOSE:The purpose of this study was to evaluate the association between systemic low bone mineral density (BMD) and subchondral insufficiency fracture (SIF) of the knee in women, and to explore whether this association is modified by radial meniscal tears. MATERIALS AND METHODS:In this case-control study, women with and without MRI-confirmed SIF who had available dual-energy X-ray absorptiometry T-score measurements were included. Systemic BMD was categorized using T-scores. Multivariable logistic regression models with BMD as the exposure and SIF as the outcome, adjusting for age and body mass index were fitted. An exploratory stratified analysis to assess potential effect modification by meniscal radial tear status was also conducted. RESULTS:A total of 121 women with SIF (mean age, 69.1 ± 7.5 [standard deviation] years) and 124 controls (70.4 ± 8.3 [standard deviation] years) were analyzed. After adjustment, osteoporosis was associated with higher odds of SIF (odds ratio [OR], 2.29; 95% confidence interval [CI]: 1.03-5.09), whereas osteopenia (OR, 1.33; 95% CI: 0.69-2.55) showed no significant association. In exploratory stratified analysis to test for effect modification, there were no significant interactions between low BMD and radial root tears (P-interaction = 0.178). However, small strata likely limited the power to detect a significant effect modification, as evidenced by overlapping wide 95% CIs. CONCLUSION:Osteoporosis is associated with higher odds of SIF of the knee in women, while osteopenia is not.
PURPOSE:The purpose of this study was to evaluate the relationship between subchondral insufficiency fracture (SIF) of the knee and radial meniscal tears on magnetic resonance imaging (MRI) and to examine within the medial compartment the potential mediating role of meniscal extrusion in this relationship. MATERIALS AND METHODS:A retrospective matched case-control study of knee MRI examinations obtained from November 2021 to November 2024 was performed. MRIs were reviewed for SIF, meniscal tear morphology, and meniscal extrusion grade. Associations between radial tears and SIF (overall and medial compartment) were evaluated using conditional logistic regression adjusted for age, sex, and body mass index. Medial-compartment mediation was examined using a natural effects model with medial meniscal extrusion as the mediator. RESULTS:The cohort included 343 patients with SIF (65.4 ± 10.1 [standard deviation] years; 226 women) and 343 patients without SIF (66.4 ± 10.0 [standard deviation] years; 224 women). Compared with knees without radial tears, odds of SIF were higher in the presence of radial root tears (odds ratio [OR], 7.62; 95% confidence interval [CI]: 4.40-13.21) and radial non-root tears (OR, 5.26; 95% CI: 2.48-11.15), with similar findings in the medial compartment. In mediation analysis, medial radial root tears showed an indirect association with medial SIF through medial meniscal extrusion (OR, 1.46; 95% CI: 1.16-1.84), accounting for 16.6% of the total effect. CONCLUSION:Radial root and non-root tears are strongly associated with SIF on MRI, particularly in the medial compartment. Meniscal extrusion explained a small proportion of this association, suggesting that additional biomechanical pathways are likely in play.
PURPOSE:The purpose of this study was to evaluate the diagnostic performance of dual-energy computed tomography (DECT) effective atomic number (Zeff) mapping for detecting radiolucent common bile duct (CBD) stones and to develop and externally validate a simple, combined imaging-biochemical score. MATERIALS AND METHODS:This retrospective multicenter study included consecutive adults who underwent magnetic resonance cholangiopancreatography (MRCP) due to suspected choledocholithiasis after a negative conventional abdominal dual-layer DECT performed within 21 days. In the derivation cohort, Zeff and electron-density maps were independently reviewed by two radiologists, with consensus adjudication for interreader disagreements, using MRCP as the reference standard for CBD stones. Variables associated with MRCP-confirmed stones were entered into a multivariable logistic regression to derive a simplified score (i.e., ZBG score) based on Zeff map positivity, conjugated bilirubin or gamma-glutamyl transferase serum levels, which was then validated in an external validation cohort. RESULTS:The derivation cohort included 100 patients (mean age, 65.8 ± 19.3 [standard deviation] years; 54 men), of whom 19 had radiolucent CBD stones. The validation cohort included 101 patients (mean age, 60.2 ± 19.4 [standard deviation] years; 49 men), of whom 17 had radiolucent CBD stones. Consensus Zeff mapping yielded 63% sensitivity (95% confidence interval [CI]: 38-84), 86% specificity (95% CI: 77-93), and 82% (95% CI: 73-89) accuracy for the diagnosis of radiolucent CBD stones. Zeff map positivity (odds ratio [OR], 18.69; 95% CI: 4.22-82.68; P < 0.001) and conjugated bilirubin ≥ 50 µmol/L and/or γ-glutamyl transferase > 500 IU/L (OR, 20.67; 95% CI: 3.39-126.09; P = 0.001) were two variables that were independently associated with CBD stones. These two variables were combined into the ZBG score, with 1 point assigned to each item. The resulting ZBG score (range: 0-2) showed an area under the curve of 0.870 (95% CI: 0.801-0.939) in the derivation cohort and 0.877 (95% CI: 0.791-0.963) in the validation cohort for the diagnosis of radiolucent CBD stones. CONCLUSION:For patients with suspected CBD stones and negative conventional CT results, a simple score combining DECT Zeff mapping and routine cholestatic biomarkers provides accurate risk stratification for radiolucent CBD stones.
PURPOSE:The purpose of this study was to develop an artificial intelligence (AI) tool to assist recognition of three major interstitial lung disease (ILD) patterns on high-resolution computed tomography (HRCT) and to evaluate its added value in supporting decision-making for non-specialist radiologists. MATERIAL AND METHODS:This retrospective, multicenter study included 1097 HRCT examinations. Of these, 989 (90.15%) were used for development and 108 (9.85%) for external testing. A two-stage architecture inspired by domain-specific pretraining was employed. The encoder of a three-dimensional ILD segmentation model was kept to extract 7168 disease-specific features per HRCT, which were combined with age and sex in a deep learning model to predict three radiological patterns (usual interstitial pneumonia, non-specific interstitial pneumonia and fibrotic bronchiolocentric interstitial pneumonia) as diagnosed in multidisciplinary discussions (MDD). The external test dataset was interpreted by seven thoracic radiologists to establish a second reference (majority's vote) and by eight radiology residents with and without AI assistance. Accuracy, sensitivity and specificity were calculated for each pattern. RESULTS:The AI system achieved 77.8% accuracy on the external test dataset using MMD as a reference standard, within the range of thoracic experts (median, 75.6%; range: 61.1-81.5). AI assistance improved residents' median accuracy (+14.8% of absolute increase) and reduced reading time by 20.7% (P < 0.001). Six out of eight residents assisted by AI (75%) performed worse than AI alone. CONCLUSION:AI can accurately classify major ILD patterns and help less-experienced readers improve their performance. However, the level of improvement was inconsistent, and non-specialists rarely equaled the performance of AI alone.
PURPOSE:The purpose of this study was to assess the feasibility of color K-edge imaging enabled by spectral photon-counting CT (SPCCT) for simultaneous ventilation-perfusion evaluation using xenon and a gadolinium-based agent within healthy rabbit lungs. MATERIALS AND METHODS:In this animal study, a clinical SPCCT prototype was used to perform lung imaging in five New Zealand white rabbits. A phantom study was performed to assess gadolinium quantification accuracy and cross-contamination. Animals underwent controlled mechanical ventilation with xenon gas wash-in and received an intravenous injection of a gadolinium-based ultrasmall rigid platform (USRP) (dose, 2.3 mL·kg-1; injection rate, 3 mL·s-1; concentration, 0.29 mmol Gd.mL-1). Material decomposition yielded specific xenon and gadolinium K-edge images. Xenon maps were validated against dynamic specific ventilation maps using Pearson correlation test and linear regression analysis. Regional lung distribution was analyzed using Kruskal-Wallis test. RESULTS:Five rabbits (mean weight, 2.9 ± 0.06 [standard deviation] kg) were evaluated. In phantoms, measured gadolinium concentrations showed a perfect linear correlation with prepared concentrations (R2 = 1). In vivo, normalized steady-state xenon maps demonstrated a strong correlation with specific ventilation maps, with a pooled Pearson correlation coefficient of 0.88 and a pooled R2 of 0.78. Simultaneous imaging revealed a homogeneous xenon distribution with a median value across rabbits of 60.2% (first quartile [Q1], 59.3%; third quartile [Q3], 67.9%), with no significant regional differences. The median gadolinium perfusion across rabbits was 6.1% (Q1, 3.0%; Q3, 7.1%), with a significant dorsal-ventral gradient (P < 0.05) where the median value increased from 0.2% (Q1, -0.2%; Q3, 1.3%) in ventral regions to 6.9% (Q1, 3.8%; Q3, 10.6%) in dorsal regions. CONCLUSION:Color K-edge xenon/gadolinium-enhanced lung imaging using SPCCT is feasible in healthy animals, enabling the simultaneous specific and quantitative imaging of lung gas and blood volume.
PURPOSE:The purpose of this study was to assess occupational radiation exposure and radiation protection practices among physicians performing interventional radiology and cardiology procedures in France. MATERIALS AND METHODS:This retrospective multicenter study included 138 radiologists and 106 cardiologists from 17 French centers between 2019 and 2021. Data regarding passive dosimetry monitoring, radiation protection training, and availability and use of collective and personal protective equipment were collected. Whole-body, extremity, and eye lens dosimetry results were analyzed according to specialty and activity. Only physicians reporting systematic or frequent dosimeter use were included in the quantitative dosimetry analysis. RESULTS:Whole-body dosimeters were available for all physicians, whereas extremity and eye lens dosimeters were less often available, particularly in radiology (67% and 27%, respectively). Systematic or frequent dosimeter use was lower for extremity and eye lens monitoring than for whole-body monitoring. Median annual whole-body effective doses remained low in both radiology and cardiology (0.36 and 0.61 mSv/year, respectively), and no physician exceeded the 6 mSv/year threshold corresponding to category B workers. Extremity and eye lens exposures were substantially higher, particularly in vascular radiology and coronary/valvular cardiology. Four out of 244 physicians (1.6%) exceeded the annual eye lens dose limit of 20 mSv/year. Despite broad availability of eye protection equipment, non-use remained frequent among radiologists (35%). Radiation protection training remained heterogeneous across specialties and activities. CONCLUSION:Occupational radiation exposure remained globally low for whole-body exposure but remained substantial for extremities and especially the eye lens. Persistent shortcomings in dosimeter compliance and eye protection use emphasize the need to reinforce radiation protection practices in high-exposure interventional specialties.
PURPOSE:The purpose of this study was to develop a machine learning-based algorithm based on a combination of magnetic resonance imaging (MRI) and color-Doppler ultrasound (CDUS) to characterize lacrimal gland lesions. MATERIALS AND METHODS:All patients with a lacrimal gland lesion who underwent MRI examination and CDUS between 2014 and 2025 were retrospectively included. Thirty-four imaging features were systematically assessed. A machine learning algorithm was trained with repeated nested cross-validation (RNCV) using random forest classifiers. Shapley additive explanations values were used to assess feature contributions. Simplified models using top 5 and top 10 best features were also developed. Diagnostic performance of the models was assessed using area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (PR AUC), balanced accuracy, precision, sensitivity, specificity, Brier score, Matthew's correlation coefficient and F1-score. RESULTS:One hundred patients (mean age, 49.6 years ± 17.8 [standard deviation] years) with 130 lesions (101 non-epithelial (NEL) and 29 epithelial (EL); 45 malignant) were included. The random forest binary machine learning model yielded 75.9% sensitivity (95% confidence interval [CI]: 39-100), 86.0% specificity (95% CI: 62.4-100), and an AUC of 0.883 (95% CI: 0.692-1.0) for differentiating between malignant and benign lesions and 73.2% sensitivity (95% CI: 33.5-100), 92.9% specificity (95% CI: 69.9-100), and an AUC of 0.93 (95% CI: 0.683-1) for differentiating between EL and NEL. In multiclass analysis (benign NEL, benign EL, malignant NEL and malignant EL), the random forest yielded a macro-averaged AUC of 0.857 (95% CI: 0.722-0.972) for the all-features model. A 5-top features signature comprising apparent diffusion coefficient and resistance index values, echogenicity, age and lesion type (infiltrative vs. well-delineated mass), yielded an AUC of 0.785 (95% CI: 0.641-0.941) to distinguish between the four classes. CONCLUSION:A combination of MRI and CDUS features demonstrated high diagnostic performance for characterizing lacrimal gland lesions. A simplified 5-feature signature showed similar diagnostic performance compared to the all-features model and warrants prospective multicenter validation for clinical application.
Osteoid osteoma is a common benign bone tumor that typically involves the diaphysis of long bones, though it can also occur in epiphyseal or intracapsular locations, which can make diagnosis difficult. Imaging relies on identifying a nidus, of variable appearance, associated with reactive sclerosis and bone marrow or soft-tissue edema. While radiographs are often the first step, they lack sensitivity. Computed tomography, and especially ultra-high-resolution computed tomography, is essential for nidus detection, and magnetic resonance imaging, particularly dynamic contrast-enhanced images, provides complementary diagnostic value. Treatment emphasizes the effectiveness of minimally invasive techniques, which are safe, cost-effective, and associated with minimal functional impairment. Unlike most review articles that focus on specific aspects of diagnostic imaging or interventional radiology techniques, this article provides a comprehensive overview of osteoid osteoma, covering both conventional imaging findings and current advances in imaging and interventional radiology.
Breast cryoablation has emerged as a minimally invasive alternative to lumpectomy for selected patients with small, biologically favorable breast cancers. Its appeal lies in the combination of focal tumor destruction, outpatient treatment under local anesthesia, low procedural burden, and potentially improved cosmetic and functional outcomes. However, cryoablation should not be viewed as a simple technical substitute for surgery: its oncologic credibility depends on appropriate tumor selection, accurate imaging-based staging, adequate ablative margins, and coherent integration with adjuvant therapy and follow-up. This review summarizes the current evidence on breast cryoablation, focusing on biological rationale, validation studies with surgical confirmation, prospective non-excision cohorts, practical indications, and post-ablation imaging surveillance. Surgical-validation studies show that cryoablation can achieve high rates of complete tumor destruction, but mainly in a narrow subgroup of small, ultrasound-visible, hormone receptor-positive, HER2-negative invasive ductal carcinomas, particularly those measuring 15-20 mm or less. These studies also show that failure often reflects occult multifocality or underestimation of microscopic disease extent rather than failure to destroy the index lesion itself. Prospective non-excision studies, particularly ICE3 and FROST, have moved the field beyond feasibility alone. In highly selected older women with low-risk tumors, ICE3 reported a low 5-year ipsilateral breast tumor recurrence rate of 4.3%, while FROST showed similarly encouraging local control, with a 5-year ipsilateral breast tumor recurrence rate of 3.6%, and underscored the importance of structured post-ablation verification. These results also reflect technical progress, as single-probe liquid nitrogen platforms have simplified and standardized treatment delivery compared with earlier multi-probe approaches. Current evidence therefore supports cryoablation only within a narrow clinical setting. Broader adoption will require standardized patient selection, harmonised adjuvant strategies, robust imaging follow-up, and comparative trials against surgery or endocrine therapy-based approaches.
