High-resolution Magnetic Resonance Imaging Research Articles

Cochlear measurement in computed tomography and magnetic resonance imaging data sets by the Otoplan measurement tool: a retrospective comparative study.

Using Otoplan software, it is possible to measure the cochlea before cochlear implant surgery. Until now, computed tomography (CT) of the cochlea has been necessary for this purpose. The aim of this study was to find out whether measuring the cochlea with magnetic resonance imaging (MRI) using Otoplan is possible with the same accuracy. The cochlea of 44 patients of the local cochlear implant centre was measured by Otoplan using high-resolution CT-bone and MRI images, and the determined lengths were compared. No significant difference was found between the cochlear lengths measured, regardless of whether the length measurement was based on a CT or an MRI data set. For the determination of cochlear length prior to cochlear implant surgery, MRI images are just as suitable as CT images, therefore CT is not mandatory for length measurement by Otoplan, which could reduce the patient's radiation exposure.

Usefulness of pituitary high-resolution 3D MRI with deep-learning-based reconstruction for perioperative evaluation of pituitary adenomas.

To evaluate the diagnostic value of T1-weighted 3D fast spin-echo sequence (CUBE) with deep learning-based reconstruction (DLR) for depiction of pituitary adenoma and parasellar regions on contrast-enhanced MRI. We evaluated 24 patients with pituitary adenoma or residual tumor using CUBE with and without DLR, 1-mm slice thickness 2D T1WI (1-mm 2D T1WI) with DLR, and 3D spoiled gradient echo sequence (SPGR) as contrast-enhanced MRI. Depiction scores of pituitary adenoma and parasellar regions were assigned by two neuroradiologists, and contrast-to-noise ratio (CNR) was calculated. CUBE with DLR showed significantly higher scores for depicting pituitary adenoma or residual tumor compared to CUBE without DLR, 1-mm 2D T1WI with DLR, and SPGR (p < 0.01). The depiction score for delineation of the boundary between adenoma and the cavernous sinus was higher for CUBE with DLR than for 1-mm 2D T1WI with DLR (p = 0.01), but the difference was not significant when compared to SPGR (p = 0.20). CUBE with DLR had better interobserver agreement for evaluating adenomas than 1-mm 2D T1WI with DLR (Kappa values, 0.75 vs. 0.41). The CNR of the adenoma to the brain parenchyma increased to a ratio of 3.6 (obtained by dividing 13.7, CNR of CUBE with DLR, by 3.8, that without DLR, p < 0.01). CUBE with DLR had a significantly higher CNR than SPGR, but not 1-mm 2D T1WI with DLR. On the contrast-enhanced MRI, compared to CUBE without DLR, 1-mm 2D T1WI with DLR and SPGR, CUBE with DLR improves the depiction of pituitary adenoma and parasellar regions.

Are there any differences at gray matter sites between severe obstructive sleep apnea patients and healthy controls?

ObjectivesObstructive sleep apnea (OSA) is a disease that may cause many medical conditions. Neurocognitive disorders may be triggered by OSA. In recent studies, selectively decreased gray matter tissue was observed in patients with OSA. We aimed to determine if there was a substantial difference in patients with extreme OSA by comparing the microstructural changes in different gray matter sub-areas with healthy controls using diffusion-weighted imaging methods. MethodsWe studied 15 diagnosed severe OSA subjects before any treatment and 32 healthy control subjects. High resolution Magnetic Resonance Imaging (MRI) T1 and T2-weighted scans were visually examined to assess any major brain lesions. ResultsThere were no statistically significant differences of age and gender between the groups.The left and right globus pallidus, putamen and thalamus values did not differ significantly between OSA and control subjects. Right putamen values was negatively correlated with Apnea Hypopnea Index (AHI), supine AHI and non-REM AHI in OSA subjects, but no correlations appeared with left putamen values. The other gray matter parameters did not show any correlations with PSG parameters. AHI, Supine AHI, Non-Supine AHI, REM and NON-REM AHI values was not show any correlation with Right and Left Putamen volume sizes. ConclusionsWe made a morphological comparison of various gray matter areas of OSA patients and healthy volunteers in our study. We observed a significant decrease in right putamen gray matter volumes in patients with higher AHI values. Decreased cognitive functions are found in patients with OSA. In order to demonstrate this cognitive loss in patients with morphologically there is a need for further prospective studies with larger sample sizes.

High-resolution prostate diffusion MRI using eddy current-nulled convex optimized diffusion encoding and random matrix theory-based denoising.

To develop and evaluate a technique combining eddy current-nulled convex optimized diffusion encoding (ENCODE) with random matrix theory (RMT)-based denoising to accelerate and improve the apparent signal-to-noise ratio (aSNR) and apparent diffusion coefficient (ADC) mapping in high-resolution prostate diffusion-weighted MRI (DWI). MATERIALS ANDMETHODS: Eleven subjects with clinical suspicion of prostate cancer were scanned at 3T with high-resolution (HR) (in-plane: 1.0 × 1.0 mm2) ENCODE and standard-resolution (1.6 × 2.2 mm2) bipolar DWI sequences (both had 7 repetitions for averaging, acquisition time [TA] of 5 min 50 s). HR-ENCODE was retrospectively analyzed using three repetitions (accelerated effective TA of 2 min 30 s). The RMT-based denoising pipeline utilized complex DWI signals and Marchenko-Pastur distribution-based principal component analysis to remove additive Gaussian noise in images from multiple coils, b-values, diffusion encoding directions, and repetitions. HR-ENCODE with RMT-based denoising (HR-ENCODE-RMT) was compared with HR-ENCODE in terms of aSNR in prostate peripheral zone (PZ) and transition zone (TZ). Precision and accuracy of ADC were evaluated by the coefficient of variation (CoV) between repeated measurements and mean difference (MD) compared to the bipolar ADC reference, respectively. Differences were compared using two-sided Wilcoxon signed-rank tests (P < 0.05 considered significant). HR-ENCODE-RMT yielded 62% and 56% higher median aSNR than HR-ENCODE (b = 800 s/mm2) in PZ and TZ, respectively (P < 0.001). HR-ENCODE-RMT achieved 63% and 70% lower ADC-CoV than HR-ENCODE in PZ and TZ, respectively (P < 0.001). HR-ENCODE-RMT ADC and bipolar ADC had low MD of 22.7 × 10-6 mm2/s in PZ and low MD of 90.5 × 10-6 mm2/s in TZ. HR-ENCODE-RMT can shorten the acquisition time and improve the aSNR of high-resolution prostate DWI and achieve accurate and precise ADC measurements in the prostate.

Innovative Neuroimaging Biomarker Distinction of Major Depressive Disorder and Bipolar Disorder through Structural Connectome Analysis and Machine Learning Models.

Major depressive disorder (MDD) and bipolar disorder (BD) share clinical features, which complicates their differentiation in clinical settings. This study proposes an innovative approach that integrates structural connectome analysis with machine learning models to discern individuals with MDD from individuals with BD. High-resolution MRI images were obtained from individuals diagnosed with MDD or BD and from HCs. Structural connectomes were constructed to represent the complex interplay of brain regions using advanced graph theory techniques. Machine learning models were employed to discern unique connectivity patterns associated with MDD and BD. At the global level, both BD and MDD patients exhibited increased small-worldness compared to the HC group. At the nodal level, patients with BD and MDD showed common differences in nodal parameters primarily in the right amygdala and the right parahippocampal gyrus when compared with HCs. Distinctive differences were found mainly in prefrontal regions for BD, whereas MDD was characterized by abnormalities in the left thalamus and default mode network. Additionally, the BD group demonstrated altered nodal parameters predominantly in the fronto-limbic network when compared with the MDD group. Moreover, the application of machine learning models utilizing structural brain parameters demonstrated an impressive 90.3% accuracy in distinguishing individuals with BD from individuals with MDD. These findings demonstrate that combined structural connectome and machine learning enhance diagnostic accuracy and may contribute valuable insights to the understanding of the distinctive neurobiological signatures of these psychiatric disorders.

The imaging presentations of the fallopian canal cerebrospinal fluid leaking

Objective: To summarize the imaging presentations of the fallopian canal cerebrospinal fluid leaking (FCCFL). Methods: The high resolution CT (HRCT)and MRI materials of 4 patients (4 ears) with FCCFL confirmed by surgery between August 2016 to November 2023 were retrospectively analyzed. Among these, there were 2 males and 2 females, their ages ranged from 6 to 69 years. Results: All of the FCCFL were unilateral, including 2 on the left and 2 on the right.Clinically, the patients with FCCFL suffered from clear nasal fluid flow, ear tightness, and hearing loss. On CT, all of the affected ears were depicted markedly dilatation of the proximal portion of fallopian canal(FC), the labyrinthine segment and geniculate fossa were involved in 4 cases, and involvement of tympanic segment in 1 case at the same time. The geniculate fossa in the affected side were significantly enlarged, protruding upwards into the tympanic cavity, with one case simultaneously involving the cochlea. On MRI, the hyposignal on T1WI and hypersignal on T2WI or water sequence like cerebrospinal fluid (CSF) were shown in the enlargement FC, without diffusion restriction, and non-enhancing with administration Gadolinium contrast.CSF-like signal effusion was shown in all of the affected tympanum, of which, the CSF-like signal effusion was demonstrated in the area along the superficial petrosal nerve, the right pterygopalatine fossa and the parapharyngeal space. The adjacent intracranial meninges were presented thickening in 3 cases. Conclusion: The imaging appearances of FCCFL present some characteristics:on HRCT, the proximal portions of the affected FC depicts markedly enlargement,especially the geniculate fossa.While they present CSF-like signal, no diffusion restriction, and no enhancement administration, Gadolinium contrast on MRI, accompanying the CSF-like signal effusion in the affected tympanum.

Study of Comparison of Magnetic Resonance Imaging with Surgical and Pathological features in Carcinoma Rectum Patients.

Colorectal cancer is the second-most common cancer in the females and third-most common cancer in males worldwide and it is the second-most common cause of mortality. In India, colorectal cancer is the fifth-most common cancer overall, constituting 6.3%. With the advent of high-resolution magnetic resonance imaging (MRI), it has become the investigation of choice for local staging of rectal cancers as well as in predicting the response to neoadjuvant treatment and streamlining the management. The aims and objectives of this study were to compare the results of MRI with surgicopathological findings in carcinoma (Ca) rectum patients in Indian patients from a tertiary regional Cancer care centre. An observational retrospective study was carried out in the Department of Surgical Oncology Acharya Harihar Regional Cancer Centre, Cuttack, from January 2021 to June 2022. All the patients who were admitted and planned for the definitive surgery for Ca Rectum and Recto sigmoid Ca were included in the study. A total of 68 patients were included, including both upfront and post-neoadjuvant treatment cases. All the patients who received neoadjuvant treatment underwent an MRI for local staging. The findings of MRI were compared with surgical and histopathology results. Results were compared in terms of T staging, N staging and response to neoadjuvant therapy among MRI and surgical and pathological findings. Overall, there was good agreement between MRI and operative findings and histopathological findings.

High-resolution MRI synthesis using a data-driven framework with denoising diffusion probabilistic modeling

Objective. High-resolution magnetic resonance imaging (MRI) can enhance lesion diagnosis, prognosis, and delineation. However, gradient power and hardware limitations prohibit recording thin slices or sub-1 mm resolution. Furthermore, long scan time is not clinically acceptable. Conventional high-resolution images generated using statistical or analytical methods include the limitation of capturing complex, high-dimensional image data with intricate patterns and structures. This study aims to harness cutting-edge diffusion probabilistic deep learning techniques to create a framework for generating high-resolution MRI from low-resolution counterparts, improving the uncertainty of denoising diffusion probabilistic models (DDPM). Approach. DDPM includes two processes. The forward process employs a Markov chain to systematically introduce Gaussian noise to low-resolution MRI images. In the reverse process, a U-Net model is trained to denoise the forward process images and produce high-resolution images conditioned on the features of their low-resolution counterparts. The proposed framework was demonstrated using T2-weighted MRI images from institutional prostate patients and brain patients collected in the Brain Tumor Segmentation Challenge 2020 (BraTS2020). Main results. For the prostate dataset, the bicubic interpolation model (Bicubic), conditional generative-adversarial network (CGAN), and our proposed DDPM framework improved the noise quality measure from low-resolution images by 4.4%, 5.7%, and 12.8%, respectively. Our method enhanced the signal-to-noise ratios by 11.7%, surpassing Bicubic (9.8%) and CGAN (8.1%). In the BraTS2020 dataset, the proposed framework and Bicubic enhanced peak signal-to-noise ratio from resolution-degraded images by 9.1% and 5.8%. The multi-scale structural similarity indexes were 0.970 ± 0.019, 0.968 ± 0.022, and 0.967 ± 0.023 for the proposed method, CGAN, and Bicubic, respectively. Significance. This study explores a deep learning-based diffusion probabilistic framework for improving MR image resolution. Such a framework can be used to improve clinical workflow by obtaining high-resolution images without penalty of the long scan time. Future investigation will likely focus on prospectively testing the efficacy of this framework with different clinical indications.

Differences in intracranial atherosclerosis plaque between posterior circulation and anterior circulation on high-resolution magnetic resonance imaging: A systematic review and meta-analysis

ObjectiveThe clinical characteristics and mechanisms of stroke caused by anterior circulation atherosclerotic plaques (ACAPs) and posterior circulation atherosclerotic plaques (PCAPs) are distinct. We aimed to compare the differences in vulnerability, morphology, and distribution between ACAPs and PCAPs based on hign-resolution magnetic resonance imaging (HR-MRI). Materials and MethodsThe PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), and Wanfang database were retrieved from inception through May 2023. Meta-analysis was performed by R 4.2.1 software. The quality of the literature was assessed by the Agency for Healthcare Research and Quality (AHRQ). Subgroup analysis was conducted to explore the heterogeneity of the pooled results. ResultsThere were a total of 13 articles, including 1194 ACAPs and 1037 PCAPs. The pooled estimates demonstrated that the incidence of intraplaque hemorrhage in the PCAPs was higher (OR 1.72, 95%CI 1.35-2.18). The plaque length (SMD 0.23, 95%CI 0.06-0.39) and remodeling index (SMD 0.29, 95%CI 0.14-0.44) of PCAPs were larger than those in ACAPs. However, there were no evident differences in significant enhancement or stenosis degree between the two groups. ConclusionThere were more unstable features in PCAPs, highlighting an elevated risk of recurrent ischemic stroke in the posterior circulation. Furthermore, PCAPs were prone to developing penetrating artery disease due to their wider distribution. Nevertheless, posterior circulation arteries exhibited a greater propensity for outward remodeling, which may lead treatment team to miss the optimal intervention stage by being overlooked on angiographic detection.

Abstract 36: Association Between High-Resolution Magnetic Resonance Imaging Characteristics and Recurrent Stroke in Patients With Symptomatic Intracranial Atherosclerotic Steno-Occlusive Disease: A Prospective Multicenter Study

Background and Objectives: This study aimed to investigate the association between high-resolution magnetic resonance imaging (HR-MRI) characteristics and recurrent ipsilateral stroke in patients with symptomatic intracranial atherosclerotic steno-occlusive disease (ICAS). Methods: This multicenter, observational study recruited first-ever acute ischemic stroke patients attributed to ICAS (&gt;50% stenosis or occlusion) within 7 days after onset. Participants were assessed by multi-parametric MRI including diffusion-weighted imaging, three-dimension time-of-flight magnetic resonance angiography, and three-dimensional T1-weighted HR-MRI. The patients were recommended to receive best medical therapy and were systematically followed up for 12 months. The association between HR-MRI characteristics and the time to recurrent ipsilateral stroke was investigated by univariable and multivariable analysis. Results: Two hundred and fifty-five consecutive patients were enrolled from 15 centers. The cumulative 12-month ipsilateral recurrence incidence was 4.1% (95% confidence interval [CI]: 1.6-6.6%). The plaque length (5.69±2.21 mm vs. 6.67±4.16 mm), plaque burden (78.40±7.37% vs. 78.22±8.32%), degree of stenosis (60.25±18.95% vs. 67.50±22.09%) and remodeling index (1.07±0.27 vs. 1.03±0.35) on HR-MRI did not exhibit discernible difference between patients with and without recurrent ipsilateral stroke. Patients with recurrent ipsilateral stroke exhibited higher rates of intraplaque hemorrhage (IPH) (30.0% vs. 6.5%) and eccentric plaque (90.0% vs. 48.2%), and lower occurrence of occlusive thrombus (10.0% vs. 23.7%). In the multivariable Cox regression analysis, IPH (hazard ratio: 7.05, 95% CI: 1.53-32.41, p=0.012) was significantly associated with recurrent ipsilateral stroke after adjustment. Discussion: We found IPH is significantly associated with recurrent ipsilateral stroke. Our results suggest IPH has potential value in the selection of patients for aggressive treatment strategies.

Epidemiology, Pathophysiology, and Imaging of Atherosclerotic Intracranial Disease.

Intracranial atherosclerotic disease (ICAD) is one of the most common causes of stroke worldwide. Among people with stroke, those of East Asia descent and non-White populations in the United States have a higher burden of ICAD-related stroke compared with Whites of European descent. Disparities in the prevalence of asymptomatic ICAD are less marked than with symptomatic ICAD. In addition to stroke, ICAD increases the risk of dementia and cognitive decline, magnifying ICAD societal burden. The risk of stroke recurrence among patients with ICAD-related stroke is the highest among those with confirmed stroke and stenosis ≥70%. In fact, the 1-year recurrent stroke rate of >20% among those with stenosis >70% is one of the highest rates among common causes of stroke. The mechanisms by which ICAD causes stroke include plaque rupture with in situ thrombosis and occlusion or artery-to-artery embolization, hemodynamic injury, and branch occlusive disease. The risk of stroke recurrence varies by the presumed underlying mechanism of stroke, but whether techniques such as quantitative magnetic resonance angiography, computed tomographic angiography, magnetic resonance perfusion, or transcranial Doppler can help with risk stratification beyond the degree of stenosis is less clear. The diagnosis of ICAD is heavily reliant on lumen-based studies, such as computed tomographic angiography, magnetic resonance angiography, or digital subtraction angiography, but newer technologies, such as high-resolution vessel wall magnetic resonance imaging, can help distinguish ICAD from stenosing arteriopathies.

Abstract TP3: Predicting Rupture Risk of Intracranial Aneurysms Through Radiomics Analysis

Background: Intracranial aneurysm rupture is a devastating event. Accurate estimation of their rupture risk can help guide management decisions. However, existing prediction methods remain subjective and have limited accuracy. This study is aimed at using clinical and imaging data to create an accurate predictive clinical tool for identification of aneurysms at a higher risk of rupturing. Methods: A prospectively acquired database of patients scanned with 3T high-resolution MRI between 2018 to 2023 was analyzed. Symptomatic status was defined as aneurysms that caused a cranial nerve neuropathy due to compression, and/or presented with a sentinel headache. Saccular aneurysms were segmented within 3D Slicer using co-registered T1 and T1+Gd 3T images. Morphological and aneurysm wall enhancement (AWE) metrics were obtained from the 3D models. Radiomic features (RFs) were extracted using pyRadiomics extension of 3D Slicer. This database was utilized for training and testing different machine learning prediction models. Finally, a Naïve bayes model was then employed for constructing clinical nomograms (Figure). Results: A total of one hundred and four aneurysms were analyzed. Twenty-nine were symptomatic. There were 87 RFs significantly different between symptomatic and asymptomatic aneurysms. Four machine learning prediction models were created based on clinical, morphological, AWE and RFs data. The best predictive model was based on RFs, achieving an accuracy of 74%. Conclusion: RFs combined with clinical, morphological and AWE metrics could potentially be a valuable clinical tool to predict intracranial aneurysms rupture risk.

MR IMAGING AND EVALUATION OF THE PITUITARY STALK: SIZE, SHAPE, AND ENHANCEMENT PATTERN

Background: Knowing the normal imaging appearance of the pituitary stalk is essential for diagnosing pituitary infundibular lesions and a more accurate assessment of the stalk. Objective: We aimed to evaluate the normal pituitary stalk using high-resolution magnetic resonance imaging(MRI) at 1.5T. Materials and Methods: All images were obtained with a 1.5 T MR scanner using a dedicated pituitary MRI protocol. A total of 50 patients, with a gender distribution of 32 men and 18 women, were included in the study. Their ages ranged from 18 to 70 years, averaging 43 years. The diameter and length of the pituitary stalk were measured. The signal intensity and enhancement of the stalk were visually evaluated on pre- and post-contrast T1-weighted images. Results: The average anterior-posterior (AP) and transverse diameters of the pituitary stalk at the optic chiasm level were 3.19 ± 0.48 mm and 3.25 ± 0.46 mm, respectively. The average AP and transverse diameters of the pituitary stalk at the pituitary gland insertion were 1.93 ± 0.38 mm and 1.95 ± 0.40 mm, respectively. The length of the pituitary stalk was 6.35 ± 1.63 mm. Compared to the optic chiasm and neurohypophysis,the stalk demonstrated hypointensity on unenhancedMR images. The enhancement of the pituitary stalk is observed in all cases. Conclusions: The study pinpointed key MRI criteria for evaluating the normal pituitary stalks size, shape, and how it takes up contrast dye. These details act as a roadmap for spotting and understanding pituitary gland issues.

Cerebro-cerebellar gray matter abnormalities associated with cognitive impairment in patients with recent-onset and chronic schizophrenia

Although the role of the cerebellum in schizophrenia has gained attention, its contribution to cognitive impairment remains unclear. We aimed to investigate volumetric alterations in the cerebro-cerebellar gray matter (GM) in patients with recent-onset schizophrenia (ROS) and chronic schizophrenia (CS) compared with healthy controls (HCs). Seventy-two ROS, 43 CS, and 127 HC participants were recruited, and high-resolution T1-weighted structural magnetic resonance images of the brain were acquired. We compared cerebellar GM volumes among the groups using voxel-based morphometry and examined the cerebro-cerebellar GM volumetric correlations in participants with schizophrenia. Exploratory correlation analysis investigated the functional relevance of cerebro-cerebellar GM volume alterations to cognitive function in the schizophrenia group. The ROS and CS participants demonstrated smaller cerebellar GM volumes, particularly in Crus I and II, than HCs. Extracted cerebellar GM volumes demonstrated significant positive correlations with the cerebral GM volume in the fronto-temporo-parietal association areas engaged in higher-order association. The exploratory analysis showed that smaller cerebellar GM in the posterior lobe regions was associated with poorer cognitive performance in participants with schizophrenia. Our study suggests that cerebellar pathogenesis is present in the early stages of schizophrenia and interconnected with structural abnormalities in the cerebral cortex. Integrating the cerebellum into the pathogenesis of schizophrenia will help advance our understanding of the disease and identify novel treatment targets concerning dysfunctional cerebro-cerebellar interactions.

Pyramidalis muscle formation during human embryonic and early fetal periods.

The pyramidalis muscle (PM) is a paired small triangular muscle of the anterior abdominal wall; however, its physiological significance is unclear. Recent studies have failed to detect this muscle during embryonic period. Hence, the present study aimed to determine the time when PM is emerging and reveal its features using high-resolution magnetic resonance imaging. Fourteen embryos between Carnegie stage (CS)18 and CS23 and 59 fetuses (crown-rump length: 39.5-185.0 mm) were selected for this study. The PM was first detected in one of the three samples at CS20. It was detected in five of the seven samples (71.4%) between CS21 and CS23. Forty-eight samples (81.4%) at early fetal period had PMs on both the right and left sides, and 3 (5.1%) had it only on the right side. Eight samples (13.6%) had no PMs. No side-differences or sexual dimorphisms were detected. The PM length was larger than the width in most samples, although the length/width ratio varied among the samples. The PM/rectus abdominis muscle length and PM/umbilicus-pubic symphysis length ratios were almost constant, irrespective of the crown-rump length. The PM was located ventrally inferior to the rectus abdominis and closer to the medial muscle groups of the lower limb than the rectus abdominis. The present study demonstrated that PM formation occurred in the late embryonic period, and that the frequency, side differences, sex dimorphism, and spatial position of the PM in the early fetal period were similar to those in adults.

Whole-brain mapping of increased manganese levels in welders and its association with exposure and motor function

Although manganese (Mn) is a trace metal essential for humans, chronic exposure to Mn can cause accumulation of this metal ion in the brain leading to an increased risk of neurological and neurobehavioral health effects. This is a concern for welders exposed to Mn through welding fumes. While brain Mn accumulation in occupational settings has mostly been reported in the basal ganglia, several imaging studies also revealed elevated Mn in other brain areas. Since Mn functions as a magnetic resonance imaging (MRI) T1 contrast agent, we developed a whole-brain MRI approach to map in vivo Mn deposition differences in the brains of non-exposed factory controls and exposed welders. This is a cross-sectional analysis of 23 non-exposed factory controls and 36 exposed full-time welders from the same truck manufacturer. We collected high-resolution 3D MRIs of brain anatomy and R1 relaxation maps to identify regional differences using voxel-based quantification (VBQ) and statistical parametric mapping. Furthermore, we investigated the associations between excess Mn deposition and neuropsychological and motor test performance. Our results indicate that: (1) Using whole-brain MRI relaxometry methods we can generate excess Mn deposition maps in vivo, (2) excess Mn accumulation due to occupational exposure occurs beyond the basal ganglia in cortical areas associated with motor and cognitive functions, (3) Mn likely diffuses along white matter tracts in the brain, and (4) Mn deposition in specific brain regions is associated with exposure (cerebellum and frontal cortex) and motor metrics (cerebellum and hippocampus).

Clinical value of 18F-PSMA-1007 PET/MRI in primary staging of patients with intermediate- to high-risk prostate cancer.

To assess the utility of 18F-PSMA-1007 PET/MRI in initial staging of intermediate- to high-risk prostate cancer (HRPCa). A total of 46 patients with pathologically verified intermediate and/or HRPCa who underwent 18F-PSMA-1007 PET/MRI with dedicated pelvic high-resolution multiparametric MRI (mpMRI) were included. PET/MRI showed 100% sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), and accuracy in detecting seminal vesicle (SV) and rectal invasion, versus 87.5%, 100%, 100% 93.8%, 95.7% and 50%, 100%,100%, 95.5%, and 95.7% for mpMRI respectively. However, PET/MRI had poor SN (40% and 0%) but high SP (94.4% and 100%) in detection of UB and neurovascular bundle (NV) invasion compared to 100% SN and SP for mpMRI. PET/MRI demonstrated stronger TNM staging agreement with the gold standard than mpMRI-WBMRI. It demonstrated concordance with T, N, and M stages in 40, 41, and 36 patients (k 0.84, 0.60, and 0.68, respectively) versus 29, 33, and 31 patients (k 0.54, 0.22, and 0.50) with accurate over all staging of 38/46 patients versus 30/46 patients (K 0.52 versus 0.22). 18F-PSMA-1007 PET/MRI is a promising imaging modality with high diagnostic accuracy in staging intermediate- and HRPCa; it improves local tumour evaluation and provides precise TNM staging. 18F-PSMA-1007 PET/MRI could have high diagnostic accuracy as shown in the current study for staging HRPCa patients that is crucial for treatment selection. We think that our study will contribute to the body of knowledge and improve the literature surrounding the clinical uses of integrated 18F-PSMA-1007 PET/MRI.

Evaluation of brain age changes in patients with liver cirrhosis and hepatic encephalopathy with deep learning models based on structural magnetic resonance imaging

Objective: To investigate the brain aging in patients with cirrhosis and hepatic encephalopathy(HE), constructed a prediction model of brain age based on deep learning and T1 high-resolution MRI, and try to reveal the specific regions where cirrhosis and HE accelerating brain aging. Methods: A cross-sectional study. A brain age prediction model based on the 3D full convolutional neural network was constructed through T1 high-resolution MRI data from 3 609 healthy individuals across eight global public datasets. The mean absolute error (MAE) between actual age and predicted brain age, Pearson correlation coefficient (r) and determination coefficient (R2) were calculated to evaluate the accuracy of the model's predictions. A test set (n=555) from the Human Connectome Project was used to assess the accuracy of the model. A total of 136 patients with cirrhosis were recruited from Tianjin First Central Hospital as the case group (79 patients with cirrhosis without HE and 57 patients with cirrhosis with HE), and 70 healthy individuals were recruited from the society as the healthy control group during the same period. Brain-predicted age difference (Brain-PAD), digital connection-A (NCT-A) and digital-symbol test (DST) scores of all subjects were calculated for all subjects to assess brain aging and cognitive function in the healthy control group, the cirrhosis without HE group, and the cirrhosis with HE group. The network occlusion sensitivity analysis method was employed to assess the importance of each brain region in predicting brain age. Results: As for the prediction model, in the training set, MAE=2.85, r=0.98, R2=0.96. In the test set, MAE=4.45, r=0.96, R2=0.92. In the local data set of the healthy control group, MAE=3.77, r=0.85, R2=0.73. The time of NCT-A in both cirrhosis groups was longer than healthy control group, while the DST scores were lower than healthy control group, and the differences were statistically significant (both P<0.001); the Brain-PAD of healthy control group was (0.8±4.5) years, the Brain-PAD of no-HE group was (6.9±8.1) years, and the HE group was (10.2±7.7) years. The differences between the three groups were statistically significant (P<0.001), and the differences between any two groups were statistically significant (all P<0.05). The importance ratio of visual network in predicting brain age increased in cirrhosis patients, and the HE group was higher than no-HE group. Conclusions: In patients with cirrhosis, the cognitive function is reduced, brain aging is accelerated, and these changes are more obvious in patients with HE. The importance differences of each brain network in predicting brain aging provide a new direction for identifying the specific regions where cirrhosis and HE accelerate brain aging.

Breast lesion morphology assessment with high and standard b values in diffusion-weighted imaging at 3 Tesla

IntroductionWith increasing spatial resolution, diffusion-weighted imaging (DWI) may be suitable for morphologic lesion characterization in breast MRI – an area that has traditionally been occupied by dynamic contrast-enhanced imaging (DCE). This investigation compared DWI with b values of 800 and 1600 s/mm2 to DCE for lesion morphology assessment in high-resolution breast MRI at 3 Tesla. Material and methodsMultiparametric breast MRI was performed in 91 patients with 93 histopathologically proven lesions (31 benign, 62 malignant). Two radiologists independently evaluated three datasets per patient (DWIb800; DWIb1600; DCE) and assessed lesion visibility and BIRADS morphology criteria. Diagnostic accuracy was compared among readers and datasets using Cochran's Q test and pairwise post-hoc McNemar tests. Bland-Altman analyses were conducted for lesion size comparisons. ResultsDiscrimination of carcinomas was superior compared to benign findings in both DWIb800 and DWIb1600 (p < 0.001) with no b value-dependent difference. Similarly, assessability of mass lesions was better than of non-mass lesions, irrespective of b value (p < 0.001). Intra-reader reliability for the analysis of morphologic BIRADS criteria among DCE and DWI datasets was at least moderate (Fleiss κ≥0.557), while at least substantial inter-reader agreement was ascertained over all assessed categories (κ≥0.776). In pairwise Bland-Altman analyses, the measurement bias between DCE and DWIb800 was 0.7 mm, whereas the difference between DCE and DWIb1600 was 2.8 mm. DWIb1600 allowed for higher specificity than DCE (p = 0.007/0.062). ConclusionsDWI can be employed for reliable morphologic lesion characterization in high-resolution breast MRI. High b values increase diagnostic specificity, while lesion size assessment is more precise with standard 800 s/mm2 images.

Carotid atherosclerotic plaque predicts progression of intracranial artery atherosclerosis: A MR imaging-based community cohort study

PurposeIntracranial artery atherosclerosis (ICAS) progression is associated with stroke. However, the association of carotid plaque with ICAS progression among stroke-free participants is still unclear. This study aimed to evaluate the association between carotid plaque and ICAS progression in stroke-free participants. MethodStroke-free participants were recruited from a community-based cohort study. All participants underwent questionnaire interviews, blood tests, and high-resolution vessel wall magnetic resonance (MR) imaging at baseline and follow-up for around three years. The atherosclerotic plaque was defined as eccentric wall thickening on MR imaging. The presence, location, total number, and burden (maximum wall thickness, length, and stenosis) of carotid and intracranial plaque were evaluated. ICAS progression was defined as the number increased or plaque burden (maximum wall thickness, length, or stenosis increase) increased by ≥ 20 %. The association between carotid plaque and ICAS progression was evaluated using multivariable logistic regression. ResultsOf the 312 participants (mean age at baseline: 59.85 ± 13.04 years; 136 males) who completed baseline and follow-up studies with a mean time interval of 3.15 ± 0.59 years, 85 (27.24 %) had progression of ICAS during follow-up. At least one carotid plaque was detected at baseline in 167 (53.53 %) participants. In the multivariable logistic analysis, carotid plaque was a significant predictor for the progression of ICAS (odds ratio, 2.04; 95 % confidence interval, 1.06–3.92; P = 0.032). ConclusionsCarotid plaque is associated with intracranial artery atherosclerosis progression in stroke-free population. Our findings suggest that carotid plaque may be an effective predictor for intracranial artery atherosclerosis progression.