Prostate Magnetic Resonance Imaging Using the Prostate Imaging for Recurrence Reporting (PI-RR) Scoring System to Detect Recurrent Prostate Cancer: A Systematic Review and Meta-analysis.

BACKGROUND AND OBJECTIVE: Prostate Imaging for Recurrence Reporting (PI-RR) was introduced in 2021 to standardize the interpretation and reporting of multiparametric magnetic resonance imaging (MRI) for prostate cancer following whole-gland treatment. The system scores image on a scale from 1 to 5 and has shown promising results in single-center studies. The aim of our systematic review and meta-analysis was to assess the diagnostic performance of the PI-RR system in predicting the likelihood of local recurrence after whole-gland treatment. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for diagnostic test accuracy were followed. Relevant databases were searched up to December 2023. Primary studies met the eligibility criteria if they reported MRI diagnostic performance in prostate cancer recurrence using PI-RR. Diagnostic performance for MRI was assessed using two different cutoff points (≥3 or ≥4 for positivity according to the PI-RR system). A meta-analysis with a random-effects model was used to estimate pooled sensitivity and specificity values. KEY FINDINGS AND LIMITATIONS: Sixteen articles were identified for full-text reading, of which six were considered eligible, involving a total of 467 patients. Using a cutoff of PI-RR ≥3 (4 studies) for recurrent disease, the sensitivity was 77.8% (95% confidence interval [CI] 69.9-84.1%) and the specificity was 80.2% (95% CI 58.2-92.2%). Using a cutoff of PI-RR ≥4 (4 studies), the sensitivity was 61.9% (95% CI 35.6-82.7%) and the specificity was 86.6% (95% CI 75.1-93.3%). Overall, the inter-rater agreement varied from fair to excellent. CONCLUSIONS AND CLINICAL IMPLICATIONS: PI-RR is accurate in detecting local recurrence after whole-gland treatment for prostate cancer and shows fair-to-good to excellent inter-reader agreement. Overall, a PI-RR cutoff of ≥3 showed high sensitivity and specificity. PATIENT SUMMARY: We reviewed studies that reported on how good MRI scans using a scoring system called PI-RR were in detecting recurrence of prostate cancer. We found that this system shows good performance, with fair to excellent agreement between different radiologists.

Radiomic Prediction of CCND1 Expression Levels and Prognosis in Low-grade Glioma Based on Magnetic Resonance Imaging.

OJECTIVES: Low-grade glioma (LGG) is associated with increased mortality owing to recrudescence and the tendency for malignant transformation. Therefore, it is imperative to discover novel prognostic biomarkers as existing traditional prognostic biomarkers of glioma, including clinicopathological features and imaging examinations, are unable to meet the clinical demand for precision medicine. Accordingly, we aimed to evaluate the prognostic value of cyclin D1 (CCND1) expression levels and construct radiomic models to predict these levels in patients with LGG MATERIALS AND METHODS: A total of 412 LGG cases from The Cancer Genome Atlas (TCGA) were used for gene-based prognostic analysis. Using magnetic resonance imaging (MRI) images stored in The Cancer Imaging Archive with genomic data from TCGA, 149 cases were selected for radiomics feature extraction and model construction. After feature extraction, the radiomic signature was constructed using logistic regression (LR) and support vector machine (SVM) analyses. RESULTS: CCND1 was identified as a prognosis-related gene with differential expression in tumor and normal samples and plays a role in regulating both the cell cycle and immune response. Landmark analysis revealed that high-expression levels of CCND1 were beneficial for survival (P < 0.05) in advanced LGG. Four optimal radiomics features were selected to construct radiomics models. The performance of LR and SVM achieved areas under the curve of 0.703 and 0.705, as well as 0.724 and 0.726 in the training and validation sets, respectively. CONCLUSION: Elevated levels of CCND1 expression could impact the prognosis of patients with LGG. MRI-based radiomics, especially the AUC values, can serve as a novel tool for predicting CCND1 expression and understanding the correlation between elevated CCND1 expression and prognosis. AVAILABILITY OF DATA AND MATERIALS: The datasets analyzed during the current study are available in the TCGA, TCIA, UCSC XENA and GTEx repository, https://portal.gdc.cancer.gov/, https://www.cancerimagingarchive.net/, https://xenabrowser.net/datapages/, https://www.gtexportal.org/home/.

Convergent Neuroimaging and Molecular Signatures in Mild Cognitive Impairment and Alzheimer's Disease: A Data-Driven Meta-Analysis with N = 3,118.

The current study aimed to evaluate the susceptibility to regional brain atrophy and its biological mechanism in Alzheimer's disease (AD). We conducted data-driven meta-analyses to combine 3,118 structural magnetic resonance images from three datasets to obtain robust atrophy patterns. Then we introduced a set of radiogenomic analyses to investigate the biological basis of the atrophy patterns in AD. Our results showed that the hippocampus and amygdala exhibit the most severe atrophy, followed by the temporal, frontal, and occipital lobes in mild cognitive impairment (MCI) and AD. The extent of atrophy in MCI was less severe than that in AD. A series of biological processes related to the glutamate signaling pathway, cellular stress response, and synapse structure and function were investigated through gene set enrichment analysis. Our study contributes to understanding the manifestations of atrophy and a deeper understanding of the pathophysiological processes that contribute to atrophy, providing new insight for further clinical research on AD.

Sex differences of signal complexity at resting-state functional magnetic resonance imaging and their associations with the estrogen-signaling pathway in the brain.

Sex differences in the brain have been widely reported and may hold the key to elucidating sex differences in many medical conditions and drug response. However, the molecular correlates of these sex differences in structural and functional brain measures in the human brain remain unclear. Herein, we used sample entropy (SampEn) to quantify the signal complexity of resting-state functional magnetic resonance imaging (rsfMRI) in a large neuroimaging cohort (N = 1,642). The frontoparietal control network and the cingulo-opercular network had high signal complexity while the cerebellar and sensory motor networks had low signal complexity in both men and women. Compared with those in male brains, we found greater signal complexity in all functional brain networks in female brains with the default mode network exhibiting the largest sex difference. Using the gene expression data in brain tissues, we identified genes that were significantly associated with sex differences in brain signal complexity. The significant genes were enriched in the gene sets that were differentially expressed between the brain cortex and other tissues, the estrogen-signaling pathway, and the biological function of neural plasticity. In particular, the G-protein-coupled estrogen receptor 1 gene in the estrogen-signaling pathway was expressed more in brain regions with greater sex differences in SampEn. In conclusion, greater complexity in female brains may reflect the interactions between sex hormone fluctuations and neuromodulation of estrogen in women. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-023-09954-y.

Olfactory Neuroblastoma Is Not Always Located at the Roof of the Nasal Cavity.

Objectives: To evaluate the imaging characteristics of the tumor, emphasizing its location, and to determine the frequency of typical and atypical locations of olfactory neuroblastoma (ONB). Materials and Methods: We retrospectively reviewed the computed tomography and magnetic resonance imaging findings of patients with pathologically proven ONB between April 2000 and April 2023. Demographic information, chief complaints, tumor location, and tumor extension were extracted. Results: Of the 58 patients, 50 (86.2%) had the epicenter of the mass at the superior part of the nasal cavity, while eight patients (13.8%) had the epicenter at other atypical locations: seven patients (12.1%) at the middle part of the nasal cavity and one patient (1.7%) within both sphenoid sinuses. Conclusion: ONB is not always present in the upper part or the roof of the nasal cavity, and a significant number of ONBs are occasionally found in the rest of the nasal cavity and other atypical locations.

Pre-operative MRI in evaluating pathologic complete response to neoadjuvant chemotherapy in patients with breast cancer: a study focused on influencing factors of baseline clinical-pathological and imaging features.

Purpose: To investigate what pre-treatment clinical-pathological features and MRI characteristics influence the performance of breast MRI in assessing the pathologic complete response (pCR) of breast cancer patients to Neoadjuvant Chemotherapy (NAC). Methods: A total of 225 patients with pathologically-confirmed breast cancer who underwent pre- and post-NAC breast MRI between January 2020 and April 2023 were retrospectively analyzed. All patients were categorized into radiologic complete response (rCR) and non-rCR groups based on pre-operative MRI. Univariable and multivariable logistic regression were used to identify independent clinicopathological and imaging features associated with imaging-pathological discordance. The performance of pre-operative MRI for predicting pCR to NAC was assessed according to the baseline characteristics of the clinicopathological data and pre-NAC MRI. In addition, the discrepancy between the pre-operative MRI and post-operative pathological findings was further analyzed by a case-control approach. Results: Among 225 patients, 99 (44.0%) achieved pCR after NAC. MRI showed the overall sensitivity of 97.6%, specificity of 58.6%, accuracy of 80.4%, a positive predictive value (PPV) of 75.0%, and a negative predictive value (NPV) of 95.1% in identifying pCR. Of baseline features, presence of ductal carcinoma in situ (DCIS) (OR, 3.975 [95% CI: 1.448-10.908], p = 0.007), luminal B (OR, 5.076 [95% CI: 1.401-18.391], p = 0.013), HER2-enriched subtype (OR, 10.949 [95% CI: 3.262-36.747], p < 0.001), multifocal or multicentric lesions (OR, 2.467 [95% CI: 1.067-5.706], p = 0.035), segmental or regional distribution of NME (OR, 8.514 [95% CI: 1.049-69.098], p = 0.045) and rim enhancement of mass (OR, 4.261 [95% CI: 1.347-13.477], p = 0.014) were significantly associated with the discrepancy between MRI and pathology. Conclusion: Presence of DCIS, luminal B or HER2-enriched subtype, multicentric or multifocal lesions, segmental or regional distribution of NME and rim enhancement of mass may lead to a decrease in diagnostic accuracy of MRI in patients of breast cancer treated with NAC.

Noninvasive assessment of Ki-67 labeling index in glioma patients based on multi-parameters derived from advanced MR imaging.

Purpose: To investigate the predictive value of multi-parameters derived from advanced MR imaging for Ki-67 labeling index (LI) in glioma patients. Materials and Methods: One hundred and nine patients with histologically confirmed gliomas were evaluated retrospectively. These patients underwent advanced MR imaging, including dynamic susceptibility-weighted contrast enhanced MR imaging (DSC), MR spectroscopy imaging (MRS), diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI), before treatment. Twenty-one parameters were extracted, including the maximum, minimum and mean values of relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), relative mean transit time (rMTT), relative apparent diffusion coefficient (rADC), relative fractional anisotropy (rFA) and relative mean diffusivity (rMD) respectively, and ration of choline (Cho)/creatine (Cr), Cho/N-acetylaspartate (NAA) and NAA/Cr. Stepwise multivariate regression was performed to build multivariate models to predict Ki-67 LI. Pearson correlation analysis was used to investigate the correlation between imaging parameters and the grade of glioma. One-way analysis of variance (ANOVA) was used to explore the differences of the imaging parameters among the gliomas of grade II, III, and IV. Results: The multivariate regression showed that the model of five parameters, including rCBVmax (RC=0.282), rCBFmax (RC=0.151), rADCmin (RC= -0.14), rFAmax (RC=0.325) and Cho/Cr ratio (RC=0.157) predicted the Ki-67 LI with a root mean square (RMS) error of 0. 0679 (R2 = 0.8025).The regression check of this model showed that there were no multicollinearity problem (variance inflation factor: rCBVmax, 3.22; rCBFmax, 3.14; rADCmin, 1.96; rFAmax, 2.51; Cho/Cr ratio, 1.64), and the functional form of this model was appropriate (F test: p=0.682). The results of Pearson correlation analysis showed that the rCBVmax, rCBFmax, rFAmax, the ratio of Cho/Cr and Cho/NAA were positively correlated with Ki-67 LI and the grade of glioma, while the rADCmin and rMDmin were negatively correlated with Ki-67 LI and the grade of glioma. Conclusion: Combining multiple parameters derived from DSC, DTI, DWI and MRS can precisely predict the Ki-67 LI in glioma patients.

Usefulness of magnetic resonance imaging in differentiation between status epilepticus and acute ischemic stroke.

BACKGROUND: Status epilepticus, characterized by the temporal neurological deficits, often mimics acute ischemic stroke. We investigated the usefulness of magnetic resonance imaging for differentiation of status epilepticus from acute ischemic stroke. METHODS: A retrospective case series of patients with status epilepticus who underwent brain magnetic resonance imaging. For comparative analysis, a series of patients with acute ischemic stroke caused by unilateral middle cerebral artery occlusion was used. RESULTS: Ten patients (4 females and 6 males) with status epilepticus who underwent brain magnetic resonance imaging were included. The median age at diagnosis was 82 years (age range, 70-90 years). In all ten patients, hyperintensities in diffusion-weighted imaging with decreased apparent diffusion coefficient values, decreased venous intensity in susceptibility-weighted imaging, and hyperperfusion in arterial spin labeling perfusion were detected in the cortex of the affected side. Four patients showed an additional diffusion restriction in the thalamus. The apparent diffusion coefficient value of the lesional area was 13.1% less than the contralateral, which was less than one-third as acute ischemic stroke. Status epilepticus patients showed no change in medullary venous intensity of the affected area in susceptibility-weighted imaging, whereas acute ischemic stroke patients showed increased cortical and medullary venous intensity in affected hemisphere. Seven of eight patients with status epilepticus who underwent magnetic resonance angiography showed dilation of the cerebral arteries in the ipsilateral side. CONCLUSIONS: The combined use of diffusion-weighted imaging, susceptibility-weighted imaging, and arterial spin labeling perfusion may help accurate and prompt diagnosis of status epilepticus.

Leptomeningeal Metastases in IDH-wildtype Glioblastomas Revisited: Comprehensive Analysis of Incidence, Risk Factors, and Prognosis Based on Post-contrast FLAIR.

BACKGROUND: The incidence of leptomeningeal metastases (LM) has been reported diversely. This study aimed to investigate the incidence, risk factors, and prognosis of LM in patients with IDH-wildtype glioblastoma. METHODS: A total of 828 patients with IDH-wildtype glioblastoma were enrolled between 2005 and 2022. Baseline preoperative MRI including post-contrast fluid-attenuated inversion recovery (FLAIR) was used for LM diagnosis. Qualitative and quantitative features, including distance between tumor and subventricular zone (SVZ) and tumor volume by automatic segmentation of the lateral ventricles and tumor, were assessed. Logistic analysis of LM development was performed using clinical, molecular, and imaging data. Survival analysis was performed. RESULTS: The incidence of LM was 11.4%. MGMTp unmethylation (odds ratio [OR] = 1.92, P = 0.014), shorter distance between tumor and SVZ (OR = 0.94, P = 0.010), and larger contrast-enhancing tumor volume (OR = 1.02, P < 0.001) were significantly associated with LM. The overall survival (OS) was significantly shorter in patients with LM than in those without (log-rank test; P < 0.001), with median OS of 12.2 and 18.5 months, respectively. Presence of LM remained an independent prognostic factor for OS in IDH-wildtype glioblastoma (hazard ratio = 1.42, P = 0.011), along with other clinical, molecular, imaging, and surgical prognostic factors. CONCLUSION: The incidence of LM is high in patients with IDH-wildtype glioblastoma, and aggressive molecular and imaging factors are correlated with LM development. The prognostic significance of LM based on post-contrast FLAIR imaging suggests acknowledgement of post-contrast FLAIR as a reliable diagnostic tool for clinicians.

Evaluation of treatment response by multiparametric MR imaging in locally advanced rectal tumors following neoadjuvant chemotherapy.

PURPOSE: To investigate the effectiveness of multiparametric MRI examination in determining tumor response after neoadjuvant chemoradiotherapy (CRT) in locally advanced rectal tumors. METHODS: 46 patients with locally advanced rectal adenocarcinoma were included and were divided into two groups as complete responders and nonresponders based on Mandard score. On MRI, relative T2w signal intensity and ADC values obtained before and after treatment and tumour volumes in dynamic contrast enhanced images (DCI) were used to determine complete response to treatment. RESULTS: There were no significant differences between mean ADC values obtained by single slice ADC and three circular ROI methods. There were significant differences between two groups in terms of Post-CRT ADC value, ΔADC and %ΔADC obtained by whole tumour volume ADC method (p < 0.05). There were significant differences between Pre-CRT and Post-CRT volume values. ΔV DCI and %ΔV DCI, ΔV ADC and T2w volume values were significantly lower in complete responders (p < 0.05). In multivariate analysis, sensitivity and specificity were calculated as 88.9% and 91.9% (AUC = 0.943) when Post-CRT mean ADC value and Post-CRT DCI volume values were used together, and sensitivity and specificity were calculated as 88.9% and 94.6% (AUC = 0.949) when ΔADC and Post-CRT DCI volume values were used together. CONCLUSION: Whole tumour volume mean ADC value is the most useful method to determine treatment response. Post-CRT DCI volume measurement stands out as the most useful method in assessing complete response alone. The highest diagnostic values are achieved when the post-CRT DCI volume is combined with the ADC change value of the whole tumor volume.

Hoffmann's sign in cervical spondylotic myelopathy patients: pathological insights from neuroimaging.

OBJECTIVE: Hoffmann's sign testing is a commonly used physical examination in clinical practice for patients with cervical spondylotic myelopathy (CSM). However, the pathophysiological mechanisms underlying its occurrence and development have not been thoroughly investigated. Therefore, the present study aimed to explore whether a positive Hoffmann's sign (PHS) in CSM patients is associated with spinal cord and brain remodeling and to identify potential neuroimaging biomarkers with diagnostic value. METHODS: Seventy-six patients with CSM and 40 sex- and age-matched healthy controls (HCs) underwent multimodal MRI. Based on the results of the Hoffmann's sign examination, patients were divided into two groups: those with a PHS (n = 38) and those with a negative Hoffmann's sign (NHS; n = 38). Quantification of spinal cord and brain structural and functional parameters of the participants was performed using various methods, including functional connectivity analysis, voxel-based morphometry, and atlas-based analysis based on functional MRI and structural MRI data. Furthermore, this study conducted a correlation analysis between neuroimaging metrics and neurological function and utilized a support vector machine (SVM) algorithm for the classification of PHS and NHS. RESULTS: In comparison with the NHS and HC groups, PHS patients exhibited significant reductions in the cross-sectional area and fractional anisotropy (FA) of the lateral corticospinal tract (CST), reticulospinal tract (RST), and fasciculus cuneatus, concomitant with bilateral reductions in the volume of the lateral pallidum. The functional connectivity analysis indicated a reduction in functional connectivity between the left lateral pallidum and the right angular gyrus in the PHS group. The correlation analysis indicated a significant positive association between the CST and RST FA and the volume of the left lateral pallidum in PHS patients. Furthermore, all three variables exhibited a positive correlation with the patients' motor function. Finally, using multimodal neuroimaging metrics in conjunction with the SVM algorithm, PHS and NHS were classified with an accuracy rate of 85.53%. CONCLUSIONS: This research revealed a correlation between structural damage to the pallidum and RST and the presence of Hoffmann's sign as well as the motor function in patients with CSM. Features based on neuroimaging indicators have the potential to serve as biomarkers for assessing the extent of neuronal damage in CSM patients.

Comparison of cerebral safety following atrial fibrillation using pulsed field and thermal ablation: Results of the Neurological Assessment Subgroup in the ADVENT Trial.

BACKGROUND: Atrial fibrillation (AF) ablation carries the risk of silent cerebral event (SCE) and silent cerebral lesion (SCL). Though "silent," these may have long-term clinical implications and are challenging to study as post-procedural MRI is not standard-of-care. OBJECTIVE: The neurological assessment subgroup (NAS) of ADVENT compared cerebral effects of pulsed field ablation (PFA) to standard-of-care thermal ablation. METHODS: The NAS included consecutive randomized PFA and thermal ablation patients who received post-procedural brain MRI 12-48 hours post-ablation. Patients with apparent SCE or SCL findings underwent a modified Rankin Scale (mRS) assessment. MRI images were subsequently reviewed by a blinded Brain Imaging Core Laboratory. RESULTS: In total, 77 patients with paroxysmal AF were enrolled at 6 centers; 71 had analyzable scans (34 PFA; 37 thermal ablation). Through individual center review, 6 PFA and 4 thermal scans were identified as SCE/SCL positive, of which, 3 PFA and 0 thermal SCE/SCL findings were confirmed by a blinded core laboratory. MRI findings revealed one patient with 2-4mm SCEs, one patient with a 3mm SCE, and one patient with 2 SCLs (5.5mm and 11mm). All mRS and NIHSS scores were 0 prior to discharge and at 90-day follow-up. There were only two neurological safety events (1 TIA (PFA) and 1 stroke (thermal) in the ADVENT study, neither of which was part of the NAS. CONCLUSIONS: The ADVENT trial provides the first prospective, randomized data on the cerebral impact of PFA and thermal ablation of AF. Incidence of SCE/SCLs following ablation in the NAS was low.

The Association Between Chronic Tobacco Smoking and Brain Alterations in Schizophrenia: A Systematic Review of Magnetic Resonance Imaging Studies.

BACKGROUND AND HYPOTHESIS: The high co-occurrence of tobacco smoking in patients with schizophrenia spectrum disorders (SSD) poses a serious health concern, linked to increased mortality and worse clinical outcomes. The mechanisms underlying this co-occurrence are not fully understood. STUDY DESIGN: Addressing the need for a comprehensive overview of the impact of tobacco use on SSD neurobiology, we conducted a systematic review of neuroimaging studies (including structural, functional, and neurochemical magnetic resonance imaging studies) that investigate the association between chronic tobacco smoking and brain alterations in patients with SSD. STUDY RESULTS: Eight structural and fourteen functional studies were included. Structural studies show widespread independent and additive reductions in gray matter in relation to smoking and SSD. The majority of functional studies suggest that smoking might be associated with improvements in connectivity deficits linked to SSD. However, the limited number of and high amount of cross-sectional studies, and high between-studies sample overlap prevent a conclusive determination of the nature and extent of the impact of smoking on brain functioning in patients with SSD. Overall, functional results imply a distinct neurobiological mechanism for tobacco addiction in patients with SSD, possibly attributed to differences at the nicotinic acetylcholine receptor level. CONCLUSIONS: Our findings highlight the need for more longitudinal and exposure-dependent studies to differentiate between inherent neurobiological differences and the (long-term) effects of smoking in SSD, and to unravel the complex interaction between smoking and schizophrenia at various disease stages. This could inform more effective strategies addressing smoking susceptibility in SSD, potentially improving clinical outcomes.

Effects of computerized cognitive training on functional brain networks in patients with vascular cognitive impairment and no dementia.

AIMS: Previous neuroimaging studies of vascular cognitive impairment, no dementia (VCIND), have reported functional alterations, but far less is known about the effects of cognitive training on functional connectivity (FC) of intrinsic connectivity networks (ICNs) and how they relate to intervention-related cognitive improvement. This study provides comprehensive research on the changes in intra- and inter-brain functional networks in patients with VCIND who received computerized cognitive training, with a focus on the underlying mechanisms and potential therapeutic strategies. METHODS: We prospectively collected 60 patients with VCIND who were randomly divided into the training group (N = 30) receiving computerized cognitive training and the control group (N = 30) receiving fixed cognitive training. Functional MRI scans and cognitive assessments were performed at baseline, at the 7-week training, and at the 6-month follow-up. Utilizing templates for ICNs, the study employed a linear mixed model to compare intra- and inter-network FC changes between the two groups. Pearson correlation was applied to calculate the relationship between FC and cognitive function. RESULTS: We found significantly decreased intra-network FC within the default mode network (DMN) following computerized cognitive training at Month 6 (p = 0.034), suggesting a potential loss of functional specialization. Computerized training led to increased functional coupling between the DMN and sensorimotor network (SMN) (p = 0.01) and between the language network (LN) and executive control network (ECN) at Month 6 (p < 0.001), indicating compensatory network adaptations in patients with VCIND. Notably, the intra-LN exhibited enhanced functional specialization after computerized cognitive training (p = 0.049), with significant FC increases among LN regions, which correlated with improvements in neuropsychological measures (p < 0.05), emphasizing the targeted impact of computerized cognitive training on language abilities. CONCLUSIONS: This study provides insights into neuroplasticity and adaptive changes resulting from cognitive training in patients with VCIND, with implications for potential therapeutic strategies.

Magnetic resonance imaging features of progressive familial intrahepatic cholestasis type 3.

PURPOSE: Progressive familial intrahepatic cholestasis type 3 (PFIC-3) is a rare autosomal recessive cholestatic liver disorder. This study aimed to present the clinical and magnetic resonance imaging (MRI) features of three patients with PFIC­3. METHODS: The study included three patients with cholestasis and pathogenic variants in the ABCB4 gene identified by next-generation sequencing of a targeted-gene panel or by whole-exome sequencing. The clinical, laboratory, histological, molecular, and MRI features of the patients were collected. RESULTS: Three patients (one male and two females) were enrolled. The age when clinical signs and symptoms were first noted was 21, 14, and 39 years, respectively, and the signs and symptoms included pruritus and splenomegaly (in all three patients). Parenchymatous lace-like fibrosis was associated with periportal hyperintensity and periportal halo sign in three patients. Segmental atrophy was observed in two patients, diffuse atrophy was observed in one patient, and liver surface irregularity caused by regenerating nodules was observed in three patients. Magnetic resonance cholangiopancreatography (MRCP) images showed irregular bile duct changes in three patients, focal hilar bile duct stenosis, and local intrahepatic bile duct dilatation. CONCLUSIONS: Imaging studies using MRI and MRCP can support the clinical and laboratory results in cases of PFIC­3 and can also be used as a noninvasive diagnostic option.

Cross-Modality Reference and Feature Mutual-Projection for 3D Brain MRI Image Super-Resolution.

High-resolution (HR) magnetic resonance imaging (MRI) can reveal rich anatomical structures for clinical diagnoses. However, due to hardware and signal-to-noise ratio limitations, MRI images are often collected with low resolution (LR) which is not conducive to diagnosing and analyzing clinical diseases. Recently, deep learning super-resolution (SR) methods have demonstrated great potential in enhancing the resolution of MRI images; however, most of them did not take the cross-modality and internal priors of MR seriously, which hinders the SR performance. In this paper, we propose a cross-modality reference and feature mutual-projection (CRFM) method to enhance the spatial resolution of brain MRI images. Specifically, we feed the gradients of HR MRI images from referenced imaging modality into the SR network to transform true clear textures to LR feature maps. Meanwhile, we design a plug-in feature mutual-projection (FMP) method to capture the cross-scale dependency and cross-modality similarity details of MRI images. Finally, we fuse all feature maps with parallel attentions to produce and refine the HR features adaptively. Extensive experiments on MRI images in the image domain and k-space show that our CRFM method outperforms existing state-of-the-art MRI SR methods.

Deep Learning-Based Approach for Identifying and Measuring Focal Liver Lesions on Contrast-Enhanced MRI.

BACKGROUND: The number of focal liver lesions (FLLs) detected by imaging has increased worldwide, highlighting the need to develop a robust, objective system for automatically detecting FLLs. PURPOSE: To assess the performance of the deep learning-based artificial intelligence (AI) software in identifying and measuring lesions on contrast-enhanced magnetic resonance imaging (MRI) images in patients with FLLs. STUDY TYPE: Retrospective. SUBJECTS: 395 patients with 1149 FLLs. FIELD STRENGTH/SEQUENCE: The 1.5 T and 3 T scanners, including T1-, T2-, diffusion-weighted imaging, in/out-phase imaging, and dynamic contrast-enhanced imaging. ASSESSMENT: The diagnostic performance of AI, radiologist, and their combination was compared. Using 20 mm as the cut-off value, the lesions were divided into two groups, and then divided into four subgroups: <10, 10-20, 20-40, and ≥40 mm, to evaluate the sensitivity of radiologists and AI in the detection of lesions of different sizes. We compared the pathologic sizes of 122 surgically resected lesions with measurements obtained using AI and those made by radiologists. STATISTICAL TESTS: McNemar test, Bland-Altman analyses, Friedman test, Pearson's chi-squared test, Fisher's exact test, Dice coefficient, and intraclass correlation coefficients. A P-value <0.05 was considered statistically significant. RESULTS: The average Dice coefficient of AI in segmentation of liver lesions was 0.62. The combination of AI and radiologist outperformed the radiologist alone, with a significantly higher detection rate (0.894 vs. 0.825) and sensitivity (0.883 vs. 0.806). The AI showed significantly sensitivity than radiologists in detecting all lesions <20 mm (0.848 vs. 0.788). Both AI and radiologists achieved excellent detection performance for lesions ≥20 mm (0.867 vs. 0.881, P = 0.671). A remarkable agreement existed in the average tumor sizes among the three measurements (P = 0.174). DATA CONCLUSION: AI software based on deep learning exhibited practical value in automatically identifying and measuring liver lesions. TECHNICAL EFFICACY: Stage 2.

Advances and prospects in deuterium metabolic imaging (DMI): a systematic review of in vivo studies.

BACKGROUND: Deuterium metabolic imaging (DMI) has emerged as a promising non-invasive technique for studying metabolism in vivo. This review aims to summarize the current developments and discuss the futures in DMI technique in vivo. METHODS: A systematic literature review was conducted based on the PRISMA 2020 statement by two authors. Specific technical details and potential applications of DMI in vivo were summarized, including strategies of deuterated metabolites detection, deuterium-labeled tracers and corresponding metabolic pathways in vivo, potential clinical applications, routes of tracer administration, quantitative evaluations of metabolisms, and spatial resolution. RESULTS: Of the 2,248 articles initially retrieved, 34 were finally included, highlighting 2 strategies for detecting deuterated metabolites: direct and indirect DMI. Various deuterated tracers (e.g., [6,6'-2H2]glucose, [2,2,2'-2H3]acetate) were utilized in DMI to detect and quantify different metabolic pathways such as glycolysis, tricarboxylic acid cycle, and fatty acid oxidation. The quantifications (e.g., lactate level, lactate/glutamine and glutamate ratio) hold promise for diagnosing malignancies and assessing early anti-tumor treatment responses. Tracers can be administered orally, intravenously, or intraperitoneally, either through bolus administration or continuous infusion. For metabolic quantification, both serial time point methods (including kinetic analysis and calculation of area under the curves) and single time point quantifications are viable. However, insufficient spatial resolution remains a major challenge in DMI (e.g., 3.3-mL spatial resolution with 10-min acquisition at 3 T). CONCLUSIONS: Enhancing spatial resolution can facilitate the clinical translation of DMI. Furthermore, optimizing tracer synthesis, administration protocols, and quantification methodologies will further enhance their clinical applicability. RELEVANCE STATEMENT: Deuterium metabolic imaging, a promising non-invasive technique, is systematically discussed in this review for its current progression, limitations, and future directions in studying in vivo energetic metabolism, displaying a relevant clinical potential. KEY POINTS: • Deuterium metabolic imaging (DMI) shows promise for studying in vivo energetic metabolism. • This review explores DMI's current state, limits, and future research directions comprehensively. • The clinical translation of DMI is mainly impeded by limitations in spatial resolution.

Investigation of the anatomic risk factors in acute anterior cruciate ligament ruptures to develop ramp lesions of the medial meniscus by quantitative MRI.

OBJECTIVE: To investigate the anatomic risk factors of knee in patients with acute non-contact anterior cruciate ligament (aACL) ruptures to develop ramp lesions. METHODS: A total of 202 subjects were retrospectively divided into three groups: (1) aACL ruptures combined with ramp lesions group (n = 76); (2) isolated ACL ruptures group (n = 56) and (3) normal controls group (n = 70). Quantitative morphological parameters on MRI were measured including: diameter of medial femoral condyle (MFC), anterior-posterior length and depth of medial tibial plateau (MTP AP length and depth), lateral posterior tibial slope (LPTS) and medial posterior tibial slope (MTPS), asymmetry of LPTS and MPTS (LMPTS), lateral meniscal slope (LMS), and medial meniscal slope (MMS). RESULTS: The MTP AP length, MTP AP length/MFC diameter ratio, MTP depth, LPTS and the asymmetry of LMPTS showed significant differences among the three groups (p < 0.001). The risk factors associated with the ramp lesions including a longer MTP AP length (OR 1.17, 95% CI 1.00-1.44, p = 0.044), increased MTP depth (OR 1.91, 95% CI 1.22-3.00, p = 0.005) and lager ratio (OR 1.11, 95% CI 1.01-1.22, p = 0.036). The highest AUC was the MTP AP length/MFC diameter ratio (0.74; 95% CI, 0.66-0.82). The combination model increased higher accuracy (0.80; 95% CI, 0.72-0.88). CONCLUSION: Several bony anatomic characteristics of the knee, especially the morphology of medial tibia plateau, are additional risk factors for aACL ruptures to develop ramp lesions. CRITICAL RELEVANCE STATEMENT: Predictive anatomic risk factors of the knee for patients with acute non-contact anterior cruciate ligament (aACL) ruptures to develop ramp lesions, especially the morphology of medial tibia plateau, are detectable by MRI. KEY POINTS: Ramp lesion development can complicate aACL ruptures and requires specific treatment. Longer AP length and increased MTP depth are risk factors for concurrent ramp lesions. Identification of ramp lesions allows for the most appropriate treatment.