Three-dimensional Magnetic Resonance Imaging Research Articles

Comparison of Left Ventricular Function Derived from Subject-Specific Inverse Finite Element Modeling Based on 3D ECHO and Magnetic Resonance Images.

Three-dimensional echocardiography (3D ECHO) and magnetic resonance (MR) imaging are frequently used in patients and animals to evaluate heart functions. Inverse finite element (FE) modeling is increasingly applied to MR images to quantify left ventricular (LV) function and estimate myocardial contractility and other cardiac biomarkers. It remains unclear, however, as to whether myocardial contractility derived from the inverse FE model based on 3D ECHO images is comparable to that derived from MR images. To address this issue, we developed a subject-specific inverse FE model based on 3D ECHO and MR images acquired from seven healthy swine models to investigate if there are differences in myocardial contractility and LV geometrical features derived using these two imaging modalities. We showed that end-systolic and end-diastolic volumes derived from 3D ECHO images are comparable to those derived from MR images (R2=0.805 and 0.969, respectively). As a result, ejection fraction from 3D ECHO and MR images are linearly correlated (R2=0.977) with the limit of agreement (LOA) ranging from -17.95% to 45.89%. Using an inverse FE modeling to fit pressure and volume waveforms in subject-specific LV geometry reconstructed from 3D ECHO and MR images, we found that myocardial contractility derived from these two imaging modalities are linearly correlated with an R2 value of 0.989, a gradient of 0.895, and LOA ranging from -6.11% to 36.66%. This finding supports using 3D ECHO images in image-based inverse FE modeling to estimate myocardial contractility.

AI-assisted Segmentation Tool for Brain Tumor MR Image Analysis.

TumorPrism3D software was developed to segment brain tumors with a straightforward and user-friendly graphical interface applied to two- and three-dimensional brain magnetic resonance (MR) images. The MR images of 185 patients (103 males, 82 females) with glioblastoma multiforme were downloaded from The Cancer Imaging Archive (TCIA) to test the tumor segmentation performance of this software. Regions of interest (ROIs) corresponding to contrast-enhancing lesions, necrotic portions, and non-enhancing T2 high signal intensity components were segmented for each tumor. TumorPrism3D demonstrated high accuracy in segmenting all three tumor components in cases of glioblastoma multiforme. They achieved a better Dice similarity coefficient (DSC) ranging from 0.83 to 0.91 than 3DSlicer with a DSC ranging from 0.80 to 0.84 for the accuracy of segmented tumors. Comparative analysis with the widely used 3DSlicer software revealed TumorPrism3D to be approximately 37.4% faster in the segmentation process from initial contour drawing to final segmentation mask determination. The semi-automated nature of TumorPrism3D facilitates reproducible tumor segmentation at a rapid pace, offering the potential for quantitative analysis of tumor characteristics and artificial intelligence-assisted segmentation in brain MR imaging.

The deltoid ligament complex is reliably visualised as four fascicles in two layers with 3D volumetric MRI in the ankles of 20 asymptomatic volunteers.

The anatomy of the deltoid ligament is complex. There is agreement on the presence of superficial and deep layers but the number and frequency of fascicles remains controversial. Identifying injuries to specific components of the deltoid ligament may inform decision-making on their management. The anatomy was reviewed to establish the number and dimension of fascicles visible with three-dimensional (3D) volumetric magnetic resonance images (MRI). Twenty ankles from asymptomatic healthy volunteers were imaged with 3D volumetric MRI. The presence of individual fascicles was recorded and measured in 3D. The median age of participants was 26 years (range: 20-37) of which 13 (65%) were female. All 20 ankles had a deltoid ligament formed of four fascicles in two layers: three fascicles in the superficial layer; tibionavicular (mean dimensions 22.5 × 10.0 × 2.4 mm), tibiospring (16.6 × 6.7 × 1.9 mm) and tibiocalcaneal (23.8 × 4.6 × 1.8 mm) and a deep layer consisting of the tibiotalar fascicle, which could be divided into two parts: anterior tibiotalar (mean dimensions 10 × 5.6 × 4.1 mm) and the significantly larger posterior tibiotalar (14.2 × 13.8 × 17.5 mm, p < 0.01). There were no additional fascicles observed. The deltoid ligament complex was consistently visualised as four fascicles (tibionavicular, tibiospring, tibiocalcaneal, tibiotalar) in two layers (superficial and deep) in all 20 ankles. The posterior part of the tibiotalar fascicle was the thickest of all the fascicles in the deltoid ligament. It is, therefore, possible to accurately identify the components of the deltoid ligament, and 3T MRI can be used to assess fascicle-specific injury, which will guide treatment and rehabilitation. Level III.

Learning carotid vessel wall segmentation in black-blood MRI using sparsely sampled cross-sections from 3D data.

Atherosclerosis of the carotid artery is a major risk factor for stroke. Quantitative assessment of the carotid vessel wall can be based on cross-sections of three-dimensional (3D) black-blood magnetic resonance imaging (MRI). To increase reproducibility, a reliable automatic segmentation in these cross-sections is essential. We propose an automatic segmentation of the carotid artery in cross-sections perpendicular to the centerline to make the segmentation invariant to the image plane orientation and allow a correct assessment of the vessel wall thickness (VWT). We trained a residual U-Net on eight sparsely sampled cross-sections per carotid artery and evaluated if the model can segment areas that are not represented in the training data. We used 218 MRI datasets of 121 subjects that show hypertension and plaque in the ICA or CCA measuring in ultrasound. The model achieves a high mean Dice coefficient of 0.948/0.859 for the vessel's lumen/wall, a low mean Hausdorff distance of , and a low mean average contour distance of on the test set. The model reaches similar results for regions of the carotid artery that are not incorporated in the training set and on MRI of young, healthy subjects. The model also achieves a low median Hausdorff distance of on the 2021 Carotid Artery Vessel Wall Segmentation Challenge test set. The proposed method can reduce the effort for carotid artery vessel wall assessment. Together with human supervision, it can be used for clinical applications, as it allows a reliable measurement of the VWT for different patient demographics and MRI acquisition settings.

ESMAC Best Paper Award 2023: Increased knee flexion in participants with cerebral palsy results in altered stresses at the distal femoral growth plate compared to a typically developing cohort

IntroductionFemoral deformities are highly prevalent in children with cerebral palsy (CP) and can have a severe impact on patients’ gait abilities. While the mechanical stress regime within the distal femoral growth plate remains underexplored, understanding it is crucial given bone's adaptive response to mechanical stimuli. We quantified stresses at the distal femoral growth plate to deepen our understanding of the relationship between healthy and pathological gait patterns, internal loading, and femoral growth patterns. MethodsThis study included three-dimensional motion capture data and magnetic resonance images of 13 typically developing children and twelve participants with cerebral palsy. Employing a multi-scale mechanobiological approach, integrating musculoskeletal simulations and subject-specific finite element analysis, we investigated the orientation of the distal femoral growth plate and the stresses within it. Limbs of participants with CP were grouped depending on their knee flexion kinematics during stance phase as this potentially changes the stresses induced by knee and patellofemoral joint contact forces. ResultsDespite similar growth plate orientation across groups, significant differences were observed in the shape and distribution of growth values. Higher growth rates were noted in the anterior compartment in CP limbs with high knee flexion while CP limbs with normal knee flexion showed high similarity to the group of healthy participants. DiscussionResults indicate that the knee flexion angle during the stance phase is of high relevance for typical bone growth at the distal femur. The evaluated growth rates reveal plausible results, as long-term promoted growth in the anterior compartment leads to anterior bending of the femur which was confirmed for the group with high knee flexion through analyses of the femoral geometry. The framework for these multi-scale simulations has been made accessible on GitHub, empowering peers to conduct similar mechanobiological studies. Advancing our understanding of femoral bone development could ultimately support clinical decision-making.

Assessment of the sacroiliac joint in patients with axial spondyloarthritis via three-dimensional ultrashort echo time magnetic resonance imaging

Assessment of the sacroiliac joint in patients with axial spondyloarthritis via three-dimensional ultrashort echo time magnetic resonance imaging

Lower synaptic density and its association with cognitive dysfunction in patients with obsessive-compulsive disorder

BackgroundUnderstanding synaptic alteration in obsessive-compulsive disorder (OCD) is crucial for elucidating its pathological mechanisms, but in vivo research on this topic remains limited.AimsThis study aimed to identify the synaptic density...

Three-Dimensional MRI of Foot and Ankle: Current Perspectives and Advantages Over 2D MRI

The foot and ankle region, distinguished by its complex and intricate anatomy, is frequently susceptible to injuries, particularly in the context of sports-related activities and fall-related trauma. This article reviews the literature with respect to 3-Dimensional (3D) magnetic resonance imaging (MRI) of foot and ankle. Technical considerations and imaging and interpretation-related advantages and pitfalls will be discussed with relevant case examples. 3D MRI is advantageous over 2-Dimensional (2D) MRI in producing higher spatial resolution in a short duration of time with less partial volume artifacts and in creating structure-specific imaging using multiplanar and curved planar reconstructions. The reader will be able to apply such principles in their practice in obtaining higher-resolution volume imaging of ankle and foot with respect to ligaments, tendons, articular cartilage, plantar fascia, plantar plate, and peripheral nerves for the benefit of their patients and referring physicians.

Three-dimensional magnetic resonance imaging-based statistical shape analysis and machine learning-based prediction of patellofemoral instability.

This study performed three-dimensional (3D) magnetic resonance imaging (MRI)-based statistical shape analysis (SSA) by comparing patellofemoral instability (PFI) and normal femur models, and developed a machine learning (ML)-based prediction model. Twenty (19 patients) and 31 MRI scans (30 patients) of femurs with PFI and normal femurs, respectively, were used. Bone and cartilage segmentation of the distal femurs was performed and subsequently converted into 3D reconstructed models. The pointwise distance map showed anterior elevation of the trochlea, particularly at the central floor of the proximal trochlea, in the PFI models compared with the normal models. Principal component analysis examined shape variations in the PFI group, and several principal components exhibited shape variations in the trochlear floor and intercondylar width. Multivariate analysis showed that these shape components were significantly correlated with the PFI/non-PFI distinction after adjusting for age and sex. Our ML-based prediction model for PFI achieved a strong predictive performance with an accuracy of 0.909 ± 0.015, and an area under the curve of 0.939 ± 0.009 when using a support vector machine with a linear kernel. This study demonstrated that 3D MRI-based SSA can realistically visualize statistical results on surface models and may facilitate the understanding of complex shape features.

Volumetric Evaluation of Substantia Nigra in Major Depressive Disorder Using Atlas-Based Method

Aim: The substantia nigra pars compacta (SNc), a vital part of the brain that produces dopamine, is being closely studied due to its potential role in the monoamine hypothesis, which aims to explain the causes of Major Depressive Disorder (MDD). Dopamine, a chemical messenger in the brain, is linked to the monoamine hypothesis, suggesting that imbalances in these chemicals may contribute to MDD. This study aimed to calculate volumetric changes in the substantia nigra (SN), using brain magnetic resonance imaging (MRI) in individuals diagnosed with MDD. Material and Method: Sixty-six participants, comprising 33 individuals diagnosed with MDD (mean age=44.30±13.98 years) and 33 healthy individuals (mean age=46.27±14.94 years), were recruited from the university hospital psychiatry outpatient clinic. In the MDD group, there were 15 male participants (45%) and 18 female participants (55%). The healthy control group consisted of 28 males (84.8%) and 5 females (16.2%). Potential confounding factors, such as underlying chronic diseases, were ruled out by the clinician through a thorough examination of the patient's medical history, ensuring the study outcomes were not influenced. Three-dimensional brain MRI scans were conducted using a 1.5 Tesla MRI scanner. Volumes of the SN and midbrain were automatically computed using MRIStudio, an atlas-based image analysis program. Results: Statistically significant higher volumes were observed in the right SN in the MDD group compared to controls (0.146±0.045 cm³ vs. 0.122±0.035 cm³, p=0.02, p

Harmonizing three-dimensional MRI using pseudo-warping field guided GAN

In pursuit of cultivating automated models for magnetic resonance imaging (MRI) to aid in diagnostics, an escalating demand for extensive, multisite, and heterogeneous brain imaging datasets has emerged. This potentially introduces biased outcomes when directly applied for subsequent analysis. Researchers have endeavored to address this issue by pursuing the harmonization of MRIs. However, most existing image-based harmonization methods for MRI are tailored for 2D slices, which may introduce inter-slice variations when they are combined into a 3D volume. In this study, we aim to resolve inconsistencies between slices by introducing a pseudo-warping field. This field is created randomly and utilized to transform a slice into an artificially warped subsequent slice. The objective of this pseudo-warping field is to ensure that generators can consistently harmonize adjacent slices to another domain, without being affected by the varying content present in different slices. Furthermore, we construct unsupervised spatial and recycle loss to enhance the spatial accuracy and slice-wise consistency across the 3D images. The results demonstrate that our model effectively mitigates inter-slice variations and successfully preserves the anatomical details of the images during the harmonization process. Compared to generative harmonization models that employ 3D operators, our model exhibits greater computational efficiency and flexibility.

Altered cortical thickness and structural covariance networks in chronic low back pain

BackgroundDespite regional brain structural changes having been reported in patients with chronic low back pain (CLBP), the topological properties of structural covariance networks (SCNs), which refer to the organization of the SCNs, remain unclear. This study applied graph theoretical analysis to explore the alterations of the topological properties of SCNs, aiming to comprehend the integration and separation of SCNs in patients with CLBP. MethodsA total of 38 patients with CLBP and 38 healthy controls (HCs), balanced for age and sex, were scanned using three-dimensional T1-weighted magnetic resonance imaging. The cortical thickness was extracted from 68 brain regions, according to the Desikan–Killiany atlas, and used to reconstruct the SCNs. Subsequently, graph theoretical analysis was employed to evaluate the alterations of the topological properties in the SCNs of patients with CLBP. ResultsIn comparison to HCs, patients with CLBP had less cortical thickness in the left superior frontal cortex. Additionally, the cortical thickness of the left superior frontal cortex was negatively correlated with the Visual Analogue Scale scores of patients with CLBP. Furthermore, patients with CLBP, relative to HCs, exhibited lower global efficiency and small-worldness, as well as a longer characteristic path length. This indicates a decline in the brain's capacity to transmit and process information, potentially impacting the processing of pain signals in patients with CLBP and contributing to the development of CLBP. In contrast, there were no significant differences in the clustering coefficient, local efficiency, nodal efficiency, nodal betweenness centrality, or nodal degree between the two groups. ConclusionsFrom the regional cortical thickness to the complex brain network level, our study demonstrated changes in the cortical thickness and topological properties of the SCNs in patients with CLBP, thus aiding in a better understanding of the pathophysiological mechanisms of CLBP.

Who am I with my Lewy bodies? The insula as a core region of the self-concept networks.

Dementia with Lewy bodies (DLB) is characterized by insular atrophy, which occurs at the early stage of the disease. Damage to the insula has been associated with disorders reflecting impairments of the most fundamental components of the self, such as anosognosia, which is a frequently reported symptom in patients with Lewy bodies (LB). The purpose of this study was to investigate modifications of the self-concept (SC), another component of the self, and to identify neuroanatomical correlates, in prodromal to mild DLB. Twenty patients with prodromal to mild DLB were selected to participate in this exploratory study along with 20 healthy control subjects matched in terms of age, gender, and level of education. The Twenty Statements Test (TST) was used to assess the SC. Behavioral performances were compared between LB patients and control subjects. Three-dimensional magnetic resonance images (MRI) were acquired for all participants and correlational analyses were performed using voxel-based morphometry (VBM) in whole brain and using a mask for the insula. The behavioral results on the TST showed significantly impaired performances in LB patients in comparison with control subjects (p < .0001). Correlational analyses using VBM revealed positive correlations between the TST and grey matter volume within insular cortex, right supplementary motor area, bilateral inferior temporal gyri, right inferior frontal gyrus, and left lingual gyrus, using a threshold of p = .001 uncorrected, including total intracranial volume (TIV), age, and MMSE as nuisance covariates. Additionally, correlational analysis using a mask for the insula revealed positive correlation with grey matter volume within bilateral insular cortex, using a threshold of p = .005. The behavioral results confirm the existence of SC impairments in LB patients from the prodromal stage of the disease, compared to matched healthy controls. As we expected, VBM analyses revealed involvement of the insula, among that of other brain regions, already known to be involved in other self-components. While this study is exploratory, our findings provide important insights regarding the involvement of the insula within the self, confirming the insula as a core region of the self-networks, including for high-order self-representations such as the SC.

Reconstruction of 3D knee MRI using deep learning and compressed sensing: a validation study on healthy volunteers.

To investigate the potential of combining compressed sensing (CS) and artificial intelligence (AI), in particular deep learning (DL), for accelerating three-dimensional (3D) magnetic resonance imaging (MRI) sequences of the knee. Twenty healthy volunteers were examined using a 3-T scanner with a fat-saturated 3D proton density sequence with four different acceleration levels (10, 13, 15, and 17). All sequences were accelerated with CS and reconstructed using the conventional and a new DL-based algorithm (CS-AI). Subjective image quality was evaluated by two blinded readers using seven criteria on a 5-point-Likert-scale (overall impression, artifacts, delineation of the anterior cruciate ligament, posterior cruciate ligament, menisci, cartilage, and bone). Using mixed models, all CS-AI sequences were compared to the clinical standard (sense sequence with an acceleration factor of 2) and CS sequences with the same acceleration factor. 3D sequences reconstructed with CS-AI achieved significantly better values for subjective image quality compared to sequences reconstructed with CS with the same acceleration factor (p ≤ 0.001). The images reconstructed with CS-AI showed that tenfold acceleration may be feasible without significant loss of quality when compared to the reference sequence (p ≥ 0.999). For 3-T 3D-MRI of the knee, a DL-based algorithm allowed for additional acceleration of acquisition times compared to the conventional approach. This study, however, is limited by its small sample size and inclusion of only healthy volunteers, indicating the need for further research with a more diverse and larger sample. DRKS00024156. Using a DL-based algorithm, 54% faster image acquisition (178s versus 384s) for 3D-sequences may be possible for 3-T MRI of the knee. • Combination of compressed sensing and DL improved image quality and allows for significant acceleration of 3D knee MRI. •DL-based algorithm achieved better subjective image quality than conventional compressed sensing. •For 3D knee MRI at 3 T, 54% faster image acquisition may be possible.

Simulation of time-intensity curve based on k-space filling in breast dynamic contrast-enhanced three-dimensional magnetic resonance imaging.

This study elucidated the effects of a three-dimensional k-space trajectory incorporating the partial Fourier (PF) technique on a time-intensity curve (TIC) in a dynamic contrast-enhanced magnetic resonance imaging of a typical malignant breast tumor using a digital phantom. Images were obtained from the Cancer Imaging Archive Open Data for Breast Cancer, and 1-min scans with high temporal resolution were analyzed. The order of the k-space trajectory was set as Linear (sequential), Low-High (centric), PF (62.5%; Z-, Y-, and both directions), and Low-High Radial. k0 (center of the k-space) timing and TIC shape were affected by the chosen k-space trajectory and implementation of the PF technique. A small TIC gradient was obtained using a Low-High Radial order. If the k-space filling method (particularly the radial method) produces a gentle TIC gradient, misinterpretation could arise during the assessment of tumor malignancy status.

Recent advances in orthognathic surgery and modern diagnostic techniques

New technological tools are increasingly being applied in orthognathic surgery. Advanced techniques of imaging, diagnosis and treatment planning development, as well as simulation, guidance and evaluation of the treatment outcome are gradually taking the place of conventional techniques, enabling three-dimensional (3D) digital planning and personalized treatment of craniofacial deformities. Conventional and advanced three-dimensional techniques, such as three-dimensional ultrasound imaging (3D U/S), three-dimensional magnetic resonance imaging (3T-MRI), three-dimensional computed tomography (CT) and cone beam computed tomography (CBCT) imaging, as well as combinations of these techniques, are classified as modern technological tools, while robotic surgery and four-dimensional video stereophotogrammetry have already begun to find clinical application. In conclusion, advances in diagnostic and planning techniques in orthognathic surgery present many preoperative, intraoperative and postoperative advantages, significantly reducing the chances of complications and providing safety, accuracy and a high level of medical care. The aim of this literature review is to collect, present and evaluate new data and contemporary diagnostic methods in the field of orthognathic surgery.

The Importance of Medial Patellar Shape as a Risk Factor for Recurrent Patellar Dislocation in Adults

Background: Research on the cause of lateral patellar dislocation (LPD) has focused on trochlear morphologic parameters, joint alignment, and patellofemoral soft tissue forces. A paucity of information is available regarding how patellar morphologic parameters influence the risk for LPD. Purpose/Hypothesis: The purpose was to assess whether patellar morphology is a risk factor for recurrent LPD. It was hypothesized that (1) patients with recurrent LPD would have decreased patellar width and volume and (2) patellar morphologic parameters would accurately discriminate patients with recurrent LPD from controls. Study Design: Cohort study (diagnosis); Level of evidence, 3. Methods: A total of 21 adults with recurrent LPD (age, 29.7 ± 11.1 years; height, 170.8 ± 9.9 cm; weight, 76.1 ± 17.5 kg; 57% female) were compared with 21 sex- and height-matched controls (age, 27.2 ± 6.7 years; height, 172.0 ± 10.6 cm; weight, 71.1 ± 12.8 kg; 57% female). Three-dimensional axial fat-saturated magnetic resonance imaging scans were used to measure patellar medial, lateral, and total width; patellar volume; patellar medial and lateral facet length; the Wiberg index; and previously validated knee joint alignment and femoral shape measurements (eg, tibial tuberosity to trochlear groove distance, trochlear dysplasia). Results: The LPD group demonstrated reduced medial patellar width (Δ = −3.6 mm; P < .001) and medial facet length (Δ = −3.7 mm; P < .001) but no change in lateral width or facet length. This resulted in decreased total patellar width (Δ = −3.2 mm; P = .009), decreased patellar volume (Δ = −0.3 cm3; P = .025), and an increased Wiberg index (Δ = 0.05; P < .001). No significant differences were found for all other patellar shape measures between cohorts. Medial patellar width was the strongest single discriminator (83.3% accuracy) for recurrent LPD. Combining medial patellar width, patellofemoral tilt, and trochlear groove length increased the discrimination to 92.9%. Conclusion: The medial patellar width was significantly smaller in patients with recurrent LPD and was the single most accurate discriminator for recurrent LPD, even compared with traditional trochlear shape and joint alignment measures (eg, trochlear dysplasia, patella alta). Therefore, medial patellar morphology should be assessed in patients with LPD as a risk factor for recurrence and a potential means to improve treatment.

Altered volume of the amygdala subregions in patients with chronic low back pain.

Neuroimaging studies have suggested a pivotal role for the amygdala involvement in chronic low back pain (CLBP). However, the relationship between the amygdala subregions and CLBP has not yet been delineated. This study aimed to analyze whether the amygdala subregions were linked to the development of CLBP. A total of 45 patients with CLBP and 45 healthy controls (HCs) were included in this study. All subjects were asked to complete a three-dimensional T1-weighted magnetic resonance imaging (3D-T1 MRI) scan. FreeSurfer 7.3.2 was applied to preprocess the structural MRI images and segment the amygdala into nine subregions. Afterwards, comparisons were made between the two groups in terms of the volumes of the amygdala subregions. Correlation analysis is utilized to examine the relationship between the amygdala subregion and the scale scores, as well as the pain duration in patients with CLBP. Additionally, logistic regression was used to explore the risk of the amygdala and its subregions for CLBP. In comparison to HCs, patients with CLBP exhibited a significant enlargement of the left central nucleus (Ce) and left cortical nucleus (Co). Furthermore, the increased volume of the left Ce was associated with a higher risk of CLBP. Our study suggests that the left Ce and left Co may be involved in the pathophysiological processes of CLBP. Moreover, the volume of the left Ce may be a biomarker for detecting the risk of CLBP.

Volumetric assessment of ulnar nerves in cubital tunnel syndrome with 3D modeling of the MRI and its relationship with electrodiagnostic findings

BackgroundThickened nerve cross-sectional areas (CSA) have been investigated in compressive neuropathy, but the longitudinal extent of nerve swelling has yet to be evaluated. We did a volumetric assessment of the ulnar nerve in cubital tunnel syndrome (CuTS) with three-dimensional (3D) magnetic resonance imaging (MRI) modeling and investigated this relationship with clinical and electrodiagnostic parameters. MethodsWe compared 40 CuTS patient elbow MRIs to 46 patient elbow MRIs with lateral elbow epicondylitis as controls. The ulnar nerve was modeled with Mimics software and was assessed qualitatively and quantitatively. The CSA and ulnar nerve volumes were recorded, and the area under the receiver operating characteristic (ROC) curve was calculated for diagnostic performance. We analyzed clinical and electrodiagnostic parameters to investigate their relationship with the 3D ulnar nerve parameters. ResultsFor the diagnosis of CuTS, the area under the curve value was 0.915 for the largest CSA and 0.910 for the volume in the ROC curve. The optimal cut-off was 14.53 mm2 and 529 mm3 respectively. When electrodiagnostic parameters were investigated, the 3D ulnar nerve volume was significantly inversely associated with motor conduction velocity, although there was no association between the largest CSA and any of the electrodiagnostic parameters. ConclusionsThe 3D ulnar nerve volume, which is an integration or multilevel measurement of CSAs, showed diagnostic usefulness similar to CSA, but it correlated better with conduction velocity, indicating demyelination or early-to-moderate nerve damage in CuTS.

Spatial distribution pattern of local tumor progression analysis after microwave ablation of hepatocellular carcinoma based on three-dimensional magnetic resonance imaging

Objective: To investigate the spatial distribution pattern of local tumor progression (LTP) for hepatocellular carcinoma (HCC) ≤5 cm after microwave ablation. Methods: A retrospective analysis was performed on 169 HCCs with matched MRI before and after ablation from December 2009 to December 2019. A tumor MRI was reconstructed using three-dimensional visualization technology. LTP was classified as contact or non-contact, early or late stage, according to whether LTP was in contact with the edge of the ablation zone and the occurrence time (24 months). The tumor-surrounded area was divided into eight quadrants by using the eight-quadrant map method. An analysis was conducted on the spatial correlation between the quadrant where the ablative margin (AM) safety boundary was located and the quadrant where different types of LTP occurred. The t-test, or rank-sum test, was used for the measurement data. 2-test for count data was used to compare the difference between the two groups. Results: The AM quadrant had a distribution of 54.4% LTP, 64.2% early LTP stage, and 69.1% contact LTP, suggesting this quadrant was much more concentrated than the other quadrants (P < 0.001). Additionally, the AM quadrant had only 15.2% of non-contact type LTP and 17.1% of late LTP, which was not significantly different from the average distribution probability of 12.5% (100/8%) among the eight quadrants (P = 0.667, 0.743). 46.6% of early contact type LTP was located at the ablation needle tip, 25.2% at the body, and 28.1% at the caudal, while the location distribution probabilities of non-early contact LTP were 34.8%, 31.8%, and 33.3%, respectively. Conclusion: LTP mostly occurs in areas where the ablation safety boundary is the shortest. However, non-contact LTP and late LTP stages exhibit the feature of uniform distribution. Thus, this type of LPT may result from an inadequate non-ablation safety boundary.