Diffusion-weighted Imaging Research Articles

Fibrosis is a key pathological feature of autoimmune liver diseases (AILD). This study evaluates the diagnostic potential of apparent diffusion coefficient (ADC) values from diffusion-weighted imaging (DWI) for liver fibrosis staging, liver damage, and inflammation in AILD patients. This retrospective study analyzed the diagnostic performance of ADC values from DWI in 157 AILD patients. Liver biopsy served as the gold standard for fibrosis staging. The relationship between ADC values and liver function markers (AST, ALT) and inflammatory cytokines (IL-17, TNF-α) was assessed. To evaluate diagnostic accuracy, ADC values were compared across different fibrosis stages (S0 to S4) and inflammation grades (G0 to G4). ADC values decreased progressively with increasing fibrosis stages and inflammation grades. Notably, ADC values were significantly lower in S4 compared to S0, with an AUC of 0.91. Pearson correlation analysis revealed significant negative correlations between ADC and serum IL-17 (r = -0.39, p < 0.001), TNF-α (r = -0.43, p < 0.001), as well as liver function markers, ALT (r = -0.49, p < 0.001) and AST (r = -0.46, p < 0.001). ROC analysis showed optimal ADC cut-off values for distinguishing fibrosis stages: 1.47 × 10-³ mm²/s for ≥ S1 (AUC = 0.90), 1.35 × 10-³ mm²/s for ≥ S2 (AUC = 0.88), 1.24 × 10-³ mm²/s for ≥ S3 (AUC = 0.90), and 1.12 × 10-³ mm²/s for S4 (AUC = 0.91). This study highlights ADC values from DWI as a reliable non-invasive biomarker for assessing liver fibrosis and inflammation in AILD patients.

To evaluate the comparability and reproducibility of standardized visual versus region-of-interest (ROI)-based diffusion assessment and their prediction capacity for isocitrate dehydrogenase (IDH) mutation status in adult gliomas. Preoperative MRI scans, including diffusion-weighted imaging (DWI), of grade 2-4 adult-type diffuse gliomas (n = 303) were evaluated by three raters and repeated after one month. Visual assessment used the categorization of the Visually AcceSAble Rembrandt Images-feature 17 classes (facilitated, dubious, restricted). ROI-based assessment placed circular ROI on the visually perceived lowest apparent diffusion coefficient (ADC) areas (absolute/aADC) and contralateral normal-appearing white matter (normalized/nADC). Agreement and correlation analysis between visual and ROI-based assessments were performed. Logistic regression was conducted for IDH prediction in the subgroup of 99 non-necrotic and non-hemorrhagic cases, selected from the full cohort with available IDH status. ROI-based assessment demonstrated superior inter- and intra-rater agreement (intraclass correlation coefficient[Formula: see text]0.56 (95%-CI: 0.48-0.63)) than visual assessment (Kendall's W/Cohen's weighted kappa[Formula: see text]0.34 (95%-CI: 0.26-0.42)). Thresholds of 1,090 and 623 × 10-6 mm2/s for aADC, and 1.38 and 0.80 for nADC, distinguishing facilitated, dubious, and restricted diffusion, significantly correlated with visual assessments (P < .001). IDH classification accuracy of visual assessment was comparable to that of the ROI-based method using thresholds of aADC 1,048 × 10- 6 mm2/sn and nADC 1.38 (visual vs. aADC/nADC: 69% vs. 73%/70%). However, neither method achieved a balanced performance between specificity (99% vs. 81%/75%) and sensitivity (14% vs. 57%/61%). ROI-based diffusion assessment guided by visual input showed superior reproducibility than visual assessment alone. Although visual assessment demonstrated strong correlation with ADC thresholds and comparable overall IDH prediction accuracy, the two methods differ in clinical profile: visual assessment offered high specificity but low sensitivity, whereas ROI-based assessment improved sensitivity at the cost of reduced specificity.

This study aims to comprehensively assess microstructural abnormalities in both gray matter (GM) and white matter (WM) in patients with moyamoya disease (MMD) using neurite orientation dispersion and density imaging (NODDI). The analysis integrates GM-based and tract-based spatial statistics (GBSS and TBSS, respectively). Diffusion-weighted imaging was performed on 26 healthy controls and 15 patients with MMD. NODDI metrics-including the neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF)-as well as diffusion tensor imaging (DTI) parameters-fractional anisotropy and mean diffusivity (MD)-were estimated and compared using GBSS and TBSS approaches. The analysis revealed significant microstructural alterations in both GM and WM among patients with MMD. In GM, reduced ODI was observed in multiple regions, including areas associated with the default mode network, executive control network, visual cortex, auditory cortex, sensorimotor cortex, and insula. In WM, decreased NDI and increased ISOVF were identified, predominantly in the corpus callosum, corona radiata, and bilateral frontal and parietal lobes. Although both DTI and NODDI metrics showed similar spatial distribution patterns of WM changes, the alterations detected by NODDI were more widespread. This suggests that NODDI may provide superior sensitivity for identifying microstructural changes associated with MMD. The integration of NODDI with GBSS and TBSS enhances the detection of cerebral microstructural alterations in MMD. These findings highlight the potential of NODDI-based metrics as valuable imaging biomarkers for improving diagnostic accuracy in MMD.

Breast cancer imaging without gadolinium-based contrast agent: A review of current applications and future trends.

Assessment of glymphatic dysfunction in ulcerative colitis using DKI-ALPS: An innovative imaging biomarker.

Early and severe (ES) midline shift (MLS ≥ 10mm) simultaneously occurring within 24h after endovascular thrombectomy (EVT) is a life-threatening emergency that requires immediate intervention. This study aims to describe ES-MLS and develop a predictive model in patients with anterior circulation occlusion who have undergone EVT. This retrospective cohort study utilized data from a prospective registry. Functional outcome was defined as a modified Rankin Scale score of 0-2. Radiomic features extracted from pre-EVT diffusion-weighted imaging were subjected to LASSO regression with fourfold cross-validation. Clinical features were selected via multivariable regression and integrated into a nomogram, with performance evaluated through receiver operating characteristic curve analysis in both training and validation datasets. A total of 481 patients (median age 68 [IQR 58-76], 39.7% female) were included in this study, which consisted of a training dataset (n = 361) and a validation dataset (n = 120). In the ES-MLS group, 85.7% had died and none had a functional outcome at the 90-day follow-up. Recanalization, NIHSS score, and two radiomic features were identified as factors associated with ES-MLS in the nomogram. The predictive model exhibited an area under the curve (AUC) of 0.844 (95% confidence interval [CI], 0.803-0.880) in the training dataset and 0.823 (95% CI, 0.743-0.887) in the validation dataset. This is the initial structured overview of ES-MLS after EVT, featuring a model designed for personalized prediction of ES-MLS. The tool may enhance patient selection before EVT and refine the aggressive monitoring strategy after EVT.

To compare field-of-view optimized and constrained undistorted single-shot (FOCUS), multiplexed sensitivity-encoding (MUSE) and FOCUS-MUSE diffusion-weighted images (DWIs) in orbital imaging quality and staging performance for the patients with thyroid-associated ophthalmopathy (TAO). 67 TAOs underwent FOCUS, MUSE and FOCUS-MUSE DWIs. Qualitative (artifacts and geometric distortion, overall image quality, sharpness of boundaries) and quantitative parameters (geometric distortion ratio (GDR), signal-to-noise ratio (SNR), apparent diffusion coefficient (ADC) value, normalized ADC (nADC) value) were assessed. Additionally, nADC values of the extraocular muscles (EOMs) and mean nADC values were compared between active and inactive TAOs. Diagnostic performance was also evaluated. FOCUS-MUSE DWI exhibited significantly fewer artifacts and geometric distortion, superior overall image quality, enhanced sharpness of boundaries, higher SNR and lower GDR than MUSE and FOCUS DWIs (all p < 0.05). FOCUS-MUSE DWI showed significantly lower ADC values than MUSE (all p < 0.05) and FOCUS DWIs (all p < 0.05, except for that of superior EOM). The nADC values showed no significance among the three DWIs (all p > 0.05), except for that of the superior EOM. Furthermore, active TAOs showed higher nADC values than inactive TAOs in three DWIs (all p < 0.05). The mean nADC value of FOCUS-MUSE DWI (AUC, 0.890; sensitivity, 84.8%; specificity, 77.3%) performed better than that of MUSE (AUC, 0.713; sensitivity, 54.3%; specificity, 80.7%; p < 0.001) and FOCUS DWIs (AUC, 0.730; sensitivity, 47.8%; specificity, 90.9%; p < 0.001) in diagnosing active TAOs. FOCUS-MUSE DWI provides superior image quality and staging performance in assessing TAO than MUSE and FOCUS DWIs. We recommend its use for evaluating TAO patients in clinical practice. Field-of-view optimized and constrained undistorted single-shot multiplexed sensitivity-encoding DWI shows superior image quality and staging performance for thyroid-associated ophthalmopathy than other echo-planar imaging-based modified sequences. The superiority among different echo-planar imaging-based modified DWIs in thyroid-associated ophthalmopathy remains unclear. Field-of-view optimized and constrained undistorted single-shot multiplexed sensitivity-encoding (FOCUS-MUSE) DWI outperforms MUSE and FOCUS DWIs in imaging quality. Normalized apparent diffusion coefficient values derived from FOCUS-MUSE DWI improve staging performance of thyroid-associated ophthalmopathy.

Diffusion weighted imaging (DWI) is a key component of multiparametric (mp) prostate MRI. DWI using echo-planar techniques is susceptible to distortion at the recto-prostatic air-tissue interface. This study was to determine whether prone patient positioning reduces adjacent rectal air and DW image distortion when compared with standard-of-care supine positioning. This prospective study included consecutive patients undergoing mpMRI for suspected PCa between 2023 and 2024. Prostate segmentation was performed on DW and contrast-enhanced images. DWI distortion was measured quantitatively. Qualitative image quality of DWI and T2-weighted imaging (T2WI) was evaluated using PI-QUAL version 2; a separate 5-point clinically based Likert scale was employed to evaluate the volume of rectal air adjacent to the prostate. Fifty-two patients were enrolled. In total, 58% of patients expressed a preference for supine imaging versus 20% for prone imaging. Qualitative DWI image quality improved significantly in the prone position [median: 4 (3 to 4)] versus supine [3 (1 to 4)]; P < 0.001. In contrast, prone T2WI quality [1 (1 to 1)] was significantly inferior than supine T2WI [3 (3-4)]; P < 0.001. Quantitative measures of rectal air were significantly lower for prone [1.13cm3 (0.34-2.43)] compared with supine imaging [1.96cm3 (0.47 to 5.81); P = 0.005]. There was no significant difference in distortion between prone [3.21mm (2.42 to 3.82) and supine [2.95mm (2.25 to 4.21)] positioning across all patients (P = 0.80); however, in patients with >4cm3 of supine rectal air (n = 19), distortion was significantly reduced by prone imaging [3.49mm (2.84 to 4.03)] compared with supine [4.60mm (3.17 to 5.95)]; P = 0.02. The mean additional scanning time for the necessary prone imaging was 8 minutes 18 seconds. Prone positioning significantly reduces DWI distortion artefact when rectal air is present, but consistently results in degraded T2WI quality.

To evaluate and compare the performance of diffusion-weighted imaging (DWI) using compressed sensing (CS) and DWI using CS with model-based deep learning reconstruction (DL-DWI) in detecting and differentiating liver metastases from hepatic hemangiomas. We retrospectively analyzed data from 53 patients with metastases or hemangiomas (34 men and 19 women, mean age, 65.9years) who underwent abdominal DWI. Two radiologists evaluated liver contour and distortion, artifact, noise, overall image quality, and lesion conspicuity using a five-point scale. Signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) of the liver, as well as contras-to-noise ratio (CNR) and ADC of metastases (n = 59) and hemangiomas (n = 33) were assessed and statistically compared. A receiver operating characteristic (ROC) analysis was performed to assess the diagnostic performance of the two sequences for differentiating metastases and hemangiomas. DL-DWI provided significantly better conspicuity of metastasis than CS-DWI (p < 0.05 in both radiologists), whereas no significant difference was observed in the conspicuity of hemangioma between DL-DWI and CS-DWI. The SNR of liver parenchyma and the CNR of metastases and hemangiomas were higher in DL-DWI than in CS-DWI (p < 0.05). ADC values of liver parenchyma, metastases, and hemangiomas were lower in DL-DWI than in CS-DWI (p < 0.05). The ADC cutoff value for differentiating between metastases and hemangiomas was 1.693 × 10-3 mm2/s in DL-DWI and 1.411 × 10-3 mm2/s in CS-DWI. No significant differences were observed in the area under the ROC curve, sensitivity, and specificity between the two methods (p > 0.05). DL-DWI enhanced both qualitative and quantitative aspects of image quality in abdominal DWI. However, its diagnostic performance, including ADC cutoff values for differentiating between metastases and hemangiomas, is comparable to that of CS-DWI.

Background and Aims: To establish the role of imaging in the diagnosis, staging, treatment planning, and surveillance of musculoskeletal tumours in orthopaedic oncology. Methods: A thorough literature search was carried out into the applications of conventional radiography, ultrasonography (US), computed tomography (CT), magnetic resonance imaging (MRI), and nuclear medicine techniques. The strengths, limitations, and complementary contributions of each modality were reviewed in relation to diagnosis, staging, biopsy guidance, treatment response assessment, and surveillance. Results: A multidisciplinary approach—integrating clinicopathological assessment with multimodality imaging, maximises diagnostic accuracy and guides patient-specific management. Radiography remains the first-line investigation, offering initial lesion characterisation and narrowing the differential. US provides high-resolution evaluation of superficial soft tissue lesions and enables real-time image-guided biopsy. CT offers superior depiction of cortical integrity, osseous destruction, and matrix mineralisation, with advanced dual-energy techniques improving material characterisation and reducing metal artefacts. MRI is the gold standard for local staging, with advanced sequences such as diffusion-weighted imaging, dynamic contrast-enhanced MRI, and chemical shift imaging enhancing lesion characterisation and treatment response assessment. Established and emerging nuclear medicine techniques provide complementary functional information, enabling early detection of metastases and metabolic treatment response evaluation. Conclusion: This review outlines the strengths, limitations, and complementary contributions of these modalities in optimising the diagnostic and treatment pathways for orthopaedic oncology patients. It therefore highlights how imaging in orthopaedic oncology is inherently multimodal, with each modality contributing unique and complementary diagnostic insights.

Objective The tumor microenvironment (TME), composed of non-tumor elements such as stromal matrix and immune cells, plays a critical role in tumor progression, metastasis, and treatment response. This study aimed to investigate the association between MRI-based intratumoral and peritumoral radiomic features and the TME components, including extracellular matrix (ECM) and immune cells, in patients with invasive breast cancer. Methods In this prospective study, 121 women with histologically confirmed invasive breast cancer underwent pre-treatment multiparametric 3T breast MRI, including T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced T1-weighted sequences (NCT06095414, registered at ClinicalTrials.gov). The dataset was randomly divided into training and testing cohorts in a 7:3 ratio. A total of 16180 radiomic features were extracted from both intratumoral and peritumoral regions. Three-dimensional volume histology with quantitative immunohistochemical staining of ECM and immune cells served as the reference standard for TME assessment. Predictive models were developed using least absolute shrinkage and selection operator regression and evaluated using area under the receiver-operating characteristic curve (AUC). Model performance was compared between intratumoral-only and combined intratumoral–peritumoral features across five MRI sequences. Results Models incorporating both intratumoral and peritumoral features significantly outperformed those using intratumoral features alone in predicting TME components (P &amp;lt; 0.01). Among the five sequences, initial and delayed postcontrast T1-weighted images yielded the highest AUCs. For ECM abundance, the AUCs (95% CI) were 0.82 (0.78–0.87) and 0.82 (0.78–0.88) on initial and delayed imaging, respectively. For immune cell abundance, the AUCs were 0.82 (0.77–0.87) and 0.83 (0.78–0.88). Most of the top predictive features were first-order and texture features associated with tissue heterogeneity. Combined models more accurately captured ECM-rich and immunosuppressive TME profiles, characterized by elevated regulatory T cells and reduced cytotoxic T cells, which were associated with poor prognosis. Conclusion MRI-based radiomic features from both intratumoral and peritumoral regions are significantly associated with TME components in invasive breast cancer. Contrast-enhanced T1-weighted sequences provided the most robust performance. These findings highlight the potential of MRI-based radiomics as a powerful noninvasive biomarker for characterizing the TME and informing personalized therapeutic strategies, including immunotherapy and ECM-targeted treatments.

Predicting long-term clinical outcomes based on early acute ischemic stroke (AIS) information would be useful for many reasons, including patient counseling and clinical trial execution. This study investigates how different regions in brain imaging, including noninfarcted areas, contribute to the accuracy of predicting 90-day stroke outcomes by using deep learning (DL). We developed and validated DL models in 449 patients with AIS, by using MRI DWI scans from 1-7 days poststroke and 90-day mRS outcome data. These models were trained on various inputs: infarct volumes, full-brain images, infarct masks, intensity-preserved infarct masks, and images in which the infarct region is removed, which we call lesion-neutralized images. Performance was assessed by using accuracy of predicting the specific mRS score, accuracy within ±1 mRS category, mean absolute error (MAE), and the area under the curve (AUC) to predict unfavorable outcome (mRS > 2). The model trained by using only infarct volume size reported the highest (worst) MAE of 1.51 points (95% CI, 1.40-1.61; P < .001), while the model trained with full-brain images achieved the lowest MAE of 1.07 points (95% CI, 0.99-1.16). Models with intermediate amounts of imaging information each improved on the volume-only predictions but did not reach the performance of the full brain images; infarct masks, intensity-preserved infarct masks, and lesion-neutralized images demonstrated MAEs of 1.25 (95% CI, 1.15-1.34; P = .002), 1.21 (95% CI, 1.11-1.30; P = .008), and 1.35 (95% CI, 1.24-1.45; P < .001), respectively. Similar results were seen for other prediction tasks, including AUC to predict unfavorable outcomes, ranging from 0.68 (95% CI, 0.63-0.73) for infarct volume to 0.86 (95% CI, 0.82-0.89) for full brain inputs. While the best performance came from by using the full brain imaging volume, we demonstrate that the infarct location, its signal characteristics, and importantly, the noninfarcted regions all contribute to the predictions. The noninfarcted areas may be a proxy for overall brain health and resilience, containing important information about potential outcomes.

ObjectiveTo evaluate the efficiency of diffusion weighted imaging (DWI), the mean apparent diffusion coefficient (ADCmean) and the minimum apparent diffusion coefficient (ADCmin) values with different b-values (800 s/mm² and 1000 s/mm²) in the diagnosis and staging of endometrial carcinoma (EC).MethodsPreoperative DWI images of 412 patients with EC and 134 patients with benign endometrial lesions were analyzed retrospectively. The performance of DWI images, ADCmean and ADCmin values with different b-values (800 s/mm² and 1000 s/mm²) for the diagnosis and staging (deep myometrial invasion, cervical stromal invasion and lymph node metastasis) of EC was assessed by using receiver operating characteristic curve (ROC). The comparison between AUCs was performed using the DeLong test, and a P value < 0.05 was considered statistically significant.ResultsThe area under the curves (AUCs) of DWI protocol with b = 1000 s/mm2 for qualitative assessment of EC diagnosis and staging (0.850, 0.837, 0.906, and 0.820 for diagnosis, deep myometrial invasion, cervical stromal invasion and lymph node metastasis, respectively) were higher than those of b = 800 s/mm2 (0.821, 0.795, 0.860 and 0.814, respectively) (all p < 0.05). The AUCs for the quantitative assessment of EC diagnosis and staging with ADCmean and ADCmin values with b = 1000 s/mm2 were higher than those of b = 800 s/mm2 (all p < 0.05).ConclusionsDWI images, ADCmean and ADCmin values with b = 1000 s/mm2 had higher performance than those of b = 800 s/mm2 in the assessment of EC diagnosis and staging. This study highlights the potential of using b = 1000 s/mm² as an optimized protocol for EC assessment in clinical practice.

Introduction Stroke-related damage to structural pathways and functional connections disrupts neural network communication, contributing to behavioral deficits. A critical next step is to determine whether observed relationships between connectivity and behavior align with established neurobiological frameworks. This involves investigating structural-functional relationships as structural connectivity provides the scaffold for functional communication. Prior work primarily explored structural-functional relationships at rest, particularly between structural measures and cortico-cortical functional connectivity. However, because stroke impacts both cortical and muscular systems, incorporating task-based functional connectivity measurements that reflect synchronous activity between cortex and muscle may offer additional insight. Therefore, in this study, we examined relationships between structural injury and integrity measures with task-based functional connectivity between electrodes overlying sensorimotor cortical regions and affected upper-extremity musculature (referred to as corticomuscular coherence; CMC). Methods Individuals with early subacute stroke admitted to an inpatient rehabilitation facility completed simultaneous electroencephalography (EEG) and electromyography (EMG) recordings during a grip task. Corticospinal tract (CST) injury and integrity were computed from structural and diffusion-weighted imaging. CMC measurements involving electrodes overlying ipsilesional motor areas and affected upper-extremity musculature were computed in frequency bands relevant to neural injury (delta, 1–3 Hz) and motor function (low beta, 13–19 Hz; high beta, 20–30 Hz). Correlational analyses were performed to ascertain relationships between structural and coherence measurements. To account for inter-individual heterogeneity, analyses were repeated for CST injury and integrity subgroups. Results Of the 30 individuals enrolled, EEG data from 21 individuals who were able to complete the grip task were analyzed (10 females; 67.9 ± 9.8 years; 11.3 ± 4.1 days post-stroke). No significant structure-function associations were observed across the group. However, in the mild-moderate CST injury subgroup ( n = 11), greater injury correlated with higher coherence between electrodes overlying the supplementary motor area and affected extensor digitorum (high beta: ρ = 0.83, p = 0.001). Similarly, in the subgroup depicting higher CST integrity ( n = 9), CST integrity positively related to coherence between electrodes overlying the ipsilesional primary motor cortex and affected biceps (low beta: r = 0.94, p = 0.0001). Discussion Findings exclusive to CST injury/integrity subgroups underscore the complexity of structure-function relationships in stroke. Associations between CMC measures in motor-relevant frequency bands with measures reflecting CST microstructure suggest that post-stroke structural injury modulates task-based corticomuscular connectivity. The identification of specific cortical regions and muscles depicts varying adaptive and/or compensatory neuroplastic-like mechanisms, providing mechanistic insights that could inform targeted rehabilitation strategies to optimize post-stroke recovery.

Besides their crucial role in cerebral connectivity, brain hubs are regions vulnerable to the energy deficit associated with various brain disorders. Changes in sodium homeostasis of cortical regions have been observed in focal epilepsy and may reflect energy failure. We investigated whether nodal structural connectivity is differently affected within the hub and non-hub regions by ionic perturbations associated with focal epilepsy. Our hypothesis was that the metabolic demands of hub regions may be associated with a distinct ionic profile detectable by sodium MRI and that this profile is altered in focal epilepsy. We included 39 patients with drug-resistant focal epilepsy and 21 age- and gender-matched healthy controls. Anatomical, diffusion-weighted, and sodium imaging was performed using a 7 Tesla MRI scanner. Patients underwent pre-surgical work-up, including stereo-electroencephalographic recordings for defining the epileptogenic regions. Anatomical parcellation and multimodal coregistration allowed the use of parcels as nodes of whole-brain structural connectomes, linking structural connectivity measures to epileptogenicity and sodium parameters. Sodium parameters in patients were z-scored concerning homologous parcels in controls to allow comparison across regions of interest. Hub regions had higher total sodium concentration (TSC) than non-hub regions in both patients and controls, and this difference was not observed for sodium signal fraction (f, a proxy of intracellular sodium homeostasis). Compared to controls, patients showed increased TSC in both epileptogenic and non-epileptogenic zones, and this increase in TSC was consistent in both hub and non-hub regions. On the contrary, f was increased only within the epileptogenic zones and was not affected by the hubness of a region. Our results also confirm the whole brain increase in TSC and the local increase of the f value within epileptogenic zones previously observed in focal epilepsy patients. Therefore, we propose that sodium imaging can probe distinct tissue properties: TSC appears sensitive to microstructural alterations, while f could reflect homeostatic disruptions specific to epileptogenic regions.

To intra-individually compare the diagnostic performance of hepatobiliary phase (HBP)-abbreviated MRI (AMRI) and contrast-enhanced CT (CE-CT) in postoperative surveillance of colorectal liver metastases (CRLMs). This multicenter prospective study enrolled 462 patients with colorectal cancer who underwent paired CE-CT and HBP-AMRI every six months over a 24-month surveillance period. The HBP-AMRI protocol comprised T2-weighted imaging, diffusion-weighted imaging, and HBP at 10min post-injection, with total acquisition optimized to 5min. Lesion detection rates for all and subcentimeter lesions, and patient-level sensitivity, specificity, and accuracy were compared between CE-CT and HBP-AMRI by McNemar χ2 test. Receiver operating characteristic (ROC) curves were constructed across all surveillance intervals. HBP-AMRI demonstrated ​significantly higher detection rates​ than CE-CT across all surveillance rounds for all and subcentimeter lesions (all P < 0.05). The pooled 24-month data demonstrated HBP-AMRI significantly outperformed CE-CT in specificity (overall: 94.35% vs. 86.92%; P < 0.001), and accuracy (overall: 94.04% vs. 86.23%; P < 0.001). A consistent trend was observed across each individual surveillance round. The pooled 24-month analysis revealed HBP-AMRI had significantly higher sensitivity than CE-CT (overall: 90.35% vs. 78.07%; P = 0.023). HBP-AMRI maintained a superior negative predictive value (NPV) compared with CE-CT (overall: 99.14% vs. 97.91%), and higher positive predictive value (PPV) compared with CE-CT (overall: 57.54% vs. 33.59%) across all surveillance rounds. HBP-AMRI with a 5-minute streamlined workflow substantially outperforms CE-CT in lesion detection rate and patient-level diagnostic performance of CRLMs. HBP-AMRI can provide an efficient and safe alternative modality with longitudinal reliability for postoperative surveillance of CRLM in colorectal cancer patients.

Access to prostate MRI remains limited due to resource constraints and the need for expert interpretation. To develop machine learning (ML) models that enable risk-based triage for prostate MRI (ProMT-ML) in the evaluation of prostate cancer. Retrospective and prospective. A total of 11,879 retrospective MRI scans for suspected prostate cancer from a multi-hospital health system, divided into training (N = 9504) and test (N = 2375) sets. A total of 4551 records for prospective validation. 1.5T and 3T/Turbo-spin echo T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE). Prostate Imaging Reporting and Data System (PI-RADS) scores were retrieved from MRI reports. The Boruta algorithm was used to select final input features from candidate features. Two models were developed using supervised ML to estimate the likelihood of an abnormal MRI, defined as PI-RADS ≥ 3: Model A (with prostate volume) and Model B (without prostate volume). Models were compared to PSA. Prostate biopsy pathology was assessed to evaluate potential clinical impact. Area under the receiver operating characteristic curve (AUC) was the primary performance metric. A total of 5580 (46.9%) subjects had a PI-RADS score ≥ 3. After feature selection, Model A included age, PSA, body mass index, and prostate volume, while Model B included age, PSA, body mass index, and systolic blood pressure. Both models A (AUC 0.711) and B (AUC 0.616) significantly outperformed PSA (AUC 0.593). Compared to PSA threshold > 4 ng/mL, Model A demonstrated significantly improved specificity (28.3% vs. 21.9%) and no significant difference in sensitivity (89.0% vs. 86.7%). Among false negatives (Model A: 8.0% (62/776); Model B: 16.8% (130/776)), most (Model A: 87%; Model B: 69%) had benign or clinically insignificant disease on biopsy. On prospective validation, both versions of ProMT-ML significantly outperformed PSA. ProMT-ML provides personalized risk estimates of abnormal prostate MRI and can support triage of this test. Stage 4.

To test the non-inferiority of extended abdominopelvic ultrasound examination compared with contrast-enhanced computed tomography (CT) and whole-body diffusion-weighted magnetic resonance imaging (WB-DWI/MRI) in discriminating preoperatively between resectable and non-resectable disease based on the European Society for Medical Oncology (ESMO) and European Society of Gynecological Oncology (ESGO)-defined criteria in patients with tubo-ovarian carcinoma. The Imaging Study on Advanced ovArian Cancer was a prospective multicenter observational study conducted in five European gynecological oncology centers. All centers had ESGO accreditation to perform advanced ovarian cancer surgery, and ultrasound examinations were performed by a European Federation of Societies for Ultrasound in Medicine and Biology level-III examiner in a standardized manner. Included in the analysis were patients enrolled between 2020 and 2022 with suspected or histologically proven primary tubo-ovarian (including peritoneal) carcinoma who, for the purposes of the study, underwent ultrasound and CT imaging, as well as WB-DWI/MRI if available, prior to surgery. The index tests, which included the preoperative imaging modalities as well as intraoperative exploration at the start of surgery, supplemented by biopsy or follow-up imaging for extra-abdominal locations, evaluated the presence of disease at eight anatomical sites that, if infiltrated, would indicate non-resectability of the tumor according to the ESMO-ESGO criteria. Surgical outcome, described by the surgeons at the end of the procedure, was used as the reference standard and non-resectability was defined as the presence of residual disease > 1 cm or when debulking surgery was not feasible. The area under the receiver-operating-characteristics curve (AUC) and F1 score were used to assess the performance of the preoperative imaging methods and surgical exploration in discriminating between patients with resectable and those with non-resectable disease, based on the ESMO-ESGO criteria. We also calculated the percentage agreement between imaging findings and surgical exploration findings at the start of surgery, supplemented when applicable by biopsy or follow-up imaging for extra-abdominal locations, regarding the presence of tumor infiltration at each of the eight anatomical sites associated with non-resectability. Of 279 patients enrolled during the study period, 242 were included in the final analysis. In the subgroup of 167 patients who underwent surgery and had been examined by all three imaging methods, the AUC of the three imaging modalities and surgical exploration for discriminating between resectable and non-resectable disease based on the ESMO-ESGO criteria was 0.835 (95% CI, 0.756-0.915) for ultrasound, for CT it was 0.754 (95% CI, 0.664-0.843), for WB-DWI/MRI it was 0.720 (95% CI, 0.626-0.814) and for surgical exploration it was 0.952 (95% CI, 0.915-0.988). Ultrasound was not inferior to CT or WB-DWI/MRI, based on the AUC and F1 score, in discriminating between patients with resectable and those with non-resectable tubo-ovarian carcinoma. At surgical exploration, at least one non-resectability criterion was present in 32.2% cases. The criteria observed most frequently at surgical exploration were small-bowel involvement (23.6% of cases), diffuse deep infiltration of the root of the small-bowel mesentery (18.2% of cases) and hepatic hilum involvement (5.4% of cases). The percentage agreement between ultrasound and surgical exploration in assessing the presence of disease in at least one of the eight anatomical sites that, if infiltrated, would indicate non-resectability of tumor, was 83.9%, surpassing the percentage agreement with surgical exploration of both CT (77.7%) and WB-DWI/MRI (75.8%). When performed by an experienced examiner, ultrasound is not inferior to either CT or WB-DWI/MRI in discriminating between resectable and non-resectable disease in patients with tubo-ovarian carcinoma, based on evaluation of the presence of the disease in at least one of eight anatomical sites that, if infiltrated, would indicate non-resectability of the tumor. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Abstract Background Diffusion-weighted imaging (DWI) is a widely used magnetic resonance imaging method for non-invasive assessment of tissue structure. However, conventional Diffusion-weighted imaging (C-DWI) often suffers from low spatial resolution and artifacts. This systematic review evaluates the technical and clinical benefits of Reduced Field-of-View Diffusion-weighted magnetic resonance imaging (rFOV DWI) in comparison to C-DWI techniques. Objective The aim of the present review was to systematically evaluate the technical advances, diagnostic accuracy, and clinical applications of rFOV DWI compared with C-DWI techniques. Study design and methods A systematic review was performed according to PRISMA guidelines. Databases including ScienceDirect, Springer, Elsevier, PubMed/Medline, Wiley Online Library, and Scopus were searched. Eleven eligible studies were identified and reviewed for imaging efficacy, artifact reduction, spatial resolution, and diagnostic utility. Results rFOV DWI significantly improves image clarity by reducing susceptibility and motion artifacts. It enables higher spatial resolution and more accurate visualization of small anatomical structures. Compared to C-DWI, rFOV DWI shows enhanced diagnostic precision, which supports early disease detection and more informed clinical decisions. Conclusion rFOV DWI represents a notable advancement in imaging, offering improved quality and clinical utility. Its enhanced performance supports its integration into routine diagnostic workflows and highlights its potential for broader application as MRI technologies evolve.

To analyze the patient population diagnosed with transient global amnesia (TGA) concerning their demographic structure, clinical data and results of additional tests performed. Transient global amnesia is a neurological disorder characterized by the sudden onset of temporary memory disturbances, resolving within 24 hours and not accompanied by other focal neurologic symptoms. The pathomechanism of TGA remains unknown. The prognosis is very favorable. Laboratory tests, electroencephalograms or radiologic imaging scans are typically normal. They are usually necessary to exclude alternative diagnoses. The study was a retrospective analysis of 18795 patients hospitalized in the Clinical Provincial Hospital from 1 January 2017 to 30 April 2024. Patients with TGA were identified by searching digital data according to the ICD-10 classification. Each patient met Caplan's criteria (in Walrow and Hodges approach). The analysis considered demographic characteristics: age, gender, comorbidities, preceding factors, the time of illness onset, the results of additional tests [magnetic resonance imaging (MRI) and electroencephalogram (EEG)] and their timing. The study group included 113 patients. Hypertension and lipid disorders were most frequently noted comorbidities. Most common preceding factors were systolic blood pressure above 160 mmHg, (38%), sudden stress-inducing event (13.3%), severe pain (12.4%), physical activity (8.9%). Transient global amnesia episodes occurred most frequently during daytime, between 11 a.m. and 5 p.m. (61 patients, 54%) and 2 patients (1.77%) developed symptoms during nighttime. Magnetic resonance imaging was performed in 83 patients (73.45%). On MRI diffusion weighted imaging (DWI), hippocampal hyperintense areas were found in 15 patients (18.07%). Physical activity and atrial fibrillation were significantly higher in patients with DWI lesions. Electroencephalogram was performed in 102 patients (90.27%). Forty-seven (42%) of them showed abundant and dominant beta rhythm. Approximately one third (n = 39) had no EEG abnormalities. Epileptiform discharges were detected in two cases (1.77%). Abnormal EEG records were significantly higher in patients with present DWI lesions. Transient global amnesia episodes often occur during daily activity, and the main preceding event was an increase in systolic blood pressure above 160 mmHg. Magnetic resonance imaging and EEG tests support the diagnosis. The sensitivity of MRI is higher when performed between 24-96 hours after symptom onset.