Advanced Techniques in Body Magnetic Resonance Imaging 2.0

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 33391

Special Issue Editors

Radiological Sciences, Bioengineering, and Physics & Biology in Medicine, Magnetic Resonance Research Labs, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
Interests: magnetic resonance imaging (MRI); deep learning algorithms; image analysis techniques; early diagnosis; treatment guidance; therapeutic response assessment; oncology; cardiology; biologic markers
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Radiology, Biomedical Engineering, O’Neal Comprehensive Cancer Center, Cystic Fibrosis Center, Hepatorenal Fibrocystic Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA
Interests: diffusion and perfusion magnetic resonance imaging; abdominal cancers; data standardization and quantification
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA
Interests: development of machine kearning and deep learning-based algorithms for medical image analysis; characterization of myocardial fibrosis tissue; automated detection and evaluation of abdominal cancers
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent years have seen rapid growth in the interest in advanced MRI techniques of the body. Body MRI is promising in this respect due to its non-invasive nature and potential for early detection of abnormal tissue changes. Since morphological changes in body disease tend to be subtle, the ultimate utility of body MRI will depend on the ability to derive reliable quantitative MRI biomarkers. In addition, the mining of MRI images to derive quantitative signatures based on large feature sets (radiomics) as a distinct approach is primarily a research endeavor in recent years. Our aim with this Special Issue is to recognize the scientific underpinnings behind methods utilized in deep learning, radiomics, perfusion MRI, diffusion MRI, and image reconstruction as applied to body imaging applications, including breast, liver, prostate, pelvic, and interventional MRI. This Special Issue is also dedicated to describing applications of the advanced MRI techniques to fundamental anatomic, physiologic, and pathophysiologic studies involving animals and humans. We invite submissions of original research in any area of renal MRI biomarker research, including:

  • Machine learning and deep learning
  • Radiomics
  • Perfusion and diffusion imaging
  • Fast MRI techniques
  • MRI-guided therapy

Dr. Kyung Sung
Dr. Harrison Kim
Dr. Fatemeh Zabihollahy
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Body Magnetic Resonance Imaging
  • Artificial Intelligence
  • Deep Learning and Machine Learning
  • Imaging Reconstruction
  • Image Segmentation
  • Image Analysis and Modeling

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (15 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Other

10 pages, 1837 KiB  
Article
Ankle Joint MRI—Comparison of Image Quality and Effect of Sports-Related Stress
by Robert A. J. Gorzolla, Udo Rolle and Thomas J. Vogl
Diagnostics 2023, 13(17), 2750; https://doi.org/10.3390/diagnostics13172750 - 24 Aug 2023
Cited by 3 | Viewed by 1047
Abstract
Objectives: The main aims of the study were the evaluation of stress-related effects (strenuous vs. non-strenuous sport vs. nonathletes) in stimulating or reducing influences on cartilage volume in the ankle joint and the evaluation of the image quality of a magnetic resonance imaging [...] Read more.
Objectives: The main aims of the study were the evaluation of stress-related effects (strenuous vs. non-strenuous sport vs. nonathletes) in stimulating or reducing influences on cartilage volume in the ankle joint and the evaluation of the image quality of a magnetic resonance imaging (MRI) device with a field strength of 3.0 Tesla compared to one of 1.5 Tesla. Methods: A total of 15 subjects (6 male, 9 female) aged 19–33 years participated voluntarily in this prospective study. The subjects were divided into three groups: high-performance athletes of the German Football Association (DFB) (football/soccer = strenuous sport), high-performance athletes of the German Swimming Association (DSV) (swimming = non-strenuous sport), and nonathletes. MRI was performed on both ankle joints of all subjects in the 1.5 T and 3.0 T MRI scanners using survey sequences, proton density sequences in the coronal and sagittal planes, and VIBE sequences. Using the images of both feet produced by VIBE sequences, the cartilages of the talus and tibia were manually circumscribed using a computer mouse in every third layer, and the volume was calculated. For qualitative assessment, blinded images were submitted to three radiologists with defined standards. The images were scored using a scale from 1 to 5. Results: Cartilage volume: The investigation and examination of the individual cartilage volumes by analysis of variance (ANOVA) showed no significant differences among the three groups. The effect intensities, as calculated by Cohen’s d, were right tibia (Tiri) = 2.5, left tibia (Tile) = 2.2, right talus (Tari) = 1.9, and left talus (Tale) = 1.6 in the strenuous sport versus nonstrenuous sport groups; Tiri = 0.8, Tile = 1.2, Tari = 0.4, and Tale = 0.5 in the strenuous sport versus nonathlete groups; and Tiri = 0.3, Tile = 0.2, Tari = 0.7, and Tale = 0.5 in the nonstrenuous sport versus nonathlete groups. Device comparison: In the investigation of each evaluated area on the 1.5 T and 3.0 T MR images by the Wilcoxon matched-pair test, significant differences were found for the cartilage–bone border (KKG = 0.002), cancellous bone (Sp = 0.001), medial ligamentous apparatus (mBa = 0.001), lateral ligamentous apparatus (lBa = 0.001), and adipose tissue (Fg = 0.002). Thus, there were significant differences in the assessment of the 1.5 T MRI and the 3.0 T MRI in all five evaluated areas. Conclusion: The study showed no significant difference in the volume of hyaline articular cartilage in the upper ankle joint among the high-performance strenuous DFB athlete, high-performance non-strenuous DSV athlete, and nonathlete groups. The 3.0 Tesla device offers significant advantages in image quality compared to the 1.5 Tesla device. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure A1

30 pages, 11719 KiB  
Article
α- and β-Genotyping of Thalassemia Patients Based on a Multimodal Liver MRI Radiomics Model: A Preliminary Study in Two Centers
by Fengming Xu, Qing Feng, Jixing Yi, Cheng Tang, Huashan Lin, Bumin Liang, Chaotian Luo, Kaiming Guan, Tao Li and Peng Peng
Diagnostics 2023, 13(5), 958; https://doi.org/10.3390/diagnostics13050958 - 3 Mar 2023
Cited by 4 | Viewed by 1536
Abstract
Background: So far, there is no non-invasive method that can popularize the genetic testing of thalassemia (TM) patients on a large scale. The purpose of the study was to investigate the value of predicting the α- and β- genotypes of TM patients based [...] Read more.
Background: So far, there is no non-invasive method that can popularize the genetic testing of thalassemia (TM) patients on a large scale. The purpose of the study was to investigate the value of predicting the α- and β- genotypes of TM patients based on a liver MRI radiomics model. Methods: Radiomics features of liver MRI image data and clinical data of 175 TM patients were extracted using Analysis Kinetics (AK) software. The radiomics model with optimal predictive performance was combined with the clinical model to construct a joint model. The predictive performance of the model was evaluated in terms of AUC, accuracy, sensitivity, and specificity. Results: The T2 model showed the best predictive performance: the AUC, accuracy, sensitivity, and specificity of the validation group were 0.88, 0.865, 0.875, and 0.833, respectively. The joint model constructed from T2 image features and clinical features showed higher predictive performance: the AUC, accuracy, sensitivity, and specificity of the validation group were 0.91, 0.846, 0.9, and 0.667, respectively. Conclusion: The liver MRI radiomics model is feasible and reliable for predicting α- and β-genotypes in TM patients. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

13 pages, 1607 KiB  
Article
Prediction of the Topography of the Corticospinal Tract on T1-Weighted MR Images Using Deep-Learning-Based Segmentation
by Laszlo Barany, Nirjhar Hore, Andreas Stadlbauer, Michael Buchfelder and Sebastian Brandner
Diagnostics 2023, 13(5), 911; https://doi.org/10.3390/diagnostics13050911 - 28 Feb 2023
Viewed by 1843
Abstract
Introduction: Tractography is an invaluable tool in the planning of tumor surgery in the vicinity of functionally eloquent areas of the brain as well as in the research of normal development or of various diseases. The aim of our study was to compare [...] Read more.
Introduction: Tractography is an invaluable tool in the planning of tumor surgery in the vicinity of functionally eloquent areas of the brain as well as in the research of normal development or of various diseases. The aim of our study was to compare the performance of a deep-learning-based image segmentation for the prediction of the topography of white matter tracts on T1-weighted MR images to the performance of a manual segmentation. Methods: T1-weighted MR images of 190 healthy subjects from 6 different datasets were utilized in this study. Using deterministic diffusion tensor imaging, we first reconstructed the corticospinal tract on both sides. After training a segmentation model on 90 subjects of the PIOP2 dataset using the nnU-Net in a cloud-based environment with graphical processing unit (Google Colab), we evaluated its performance using 100 subjects from 6 different datasets. Results: Our algorithm created a segmentation model that predicted the topography of the corticospinal pathway on T1-weighted images in healthy subjects. The average dice score was 0.5479 (0.3513–0.7184) on the validation dataset. Conclusions: Deep-learning-based segmentation could be applicable in the future to predict the location of white matter pathways in T1-weighted scans. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

14 pages, 2393 KiB  
Article
Advanced Diffusion-Weighted Imaging Sequences for Breast MRI: Comprehensive Comparison of Improved Sequences and Ultra-High B-Values to Identify the Optimal Combination
by Daniel Hausmann, Inga Todorski, Alexandra Pindur, Elisabeth Weiland, Thomas Benkert, Lars Bosshard, Michael Prummer and Rahel A. Kubik-Huch
Diagnostics 2023, 13(4), 607; https://doi.org/10.3390/diagnostics13040607 - 7 Feb 2023
Cited by 3 | Viewed by 2612
Abstract
This study investigated the image quality and choice of ultra-high b-value of two DWI breast-MRI research applications. The study cohort comprised 40 patients (20 malignant lesions). In addition to s-DWI with two m-b-values (b50 and b800) and three e-b-values (e-b1500, e-b2000, and e-b2500), [...] Read more.
This study investigated the image quality and choice of ultra-high b-value of two DWI breast-MRI research applications. The study cohort comprised 40 patients (20 malignant lesions). In addition to s-DWI with two m-b-values (b50 and b800) and three e-b-values (e-b1500, e-b2000, and e-b2500), z-DWI and IR m-b1500 DWI were applied. z-DWI was acquired with the same measured b-values and e-b-values as the standard sequence. For IR m-b1500 DWI, b50 and b1500 were measured, and e-b2000 and e-b2500 were mathematically extrapolated. Three readers used Likert scales to independently analyze all ultra-high b-values (b1500–b2500) for each DWI with regards to scan preference and image quality. ADC values were measured in all 20 lesions. z-DWI was the most preferred (54%), followed by IR m-b1500 DWI (46%). b1500 was significantly preferred over b2000 for z-DWI and IR m-b1500 DWI (p = 0.001 and p = 0.002, respectively). Lesion detection was not significantly different among sequences or b-values (p = 0.174). There were no significant differences in measured ADC values within lesions between s-DWI (ADC: 0.97 [±0.09] × 10−3 mm2/s) and z-DWI (ADC: 0.99 [±0.11] × 10−3 mm2/s; p = 1.000). However, there was a trend toward lower values in IR m-b1500 DWI (ADC: 0.80 [±0.06] × 10−3 mm2/s) than in s-DWI (p = 0.090) and z-DWI (p = 0.110). Overall, image quality was superior and there were fewer image artifacts when using the advanced sequences (z-DWI + IR m-b1500 DWI) compared with s-DWI. Considering scan preferences, we found that the optimal combination was z-DWI with a calculated b1500, especially regarding examination time. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

16 pages, 961 KiB  
Article
Long-Term Psychosocial Consequences of Whole-Body Magnetic Resonance Imaging and Reporting of Incidental Findings in a Population-Based Cohort Study
by Dorina Korbmacher-Böttcher, Fabian Bamberg, Annette Peters, Birgit Linkohr, Karl-Heinz Ladwig, Lars Schwettmann, Sabine Weckbach, Christopher L. Schlett and Susanne Rospleszcz
Diagnostics 2022, 12(10), 2356; https://doi.org/10.3390/diagnostics12102356 - 28 Sep 2022
Cited by 3 | Viewed by 1637
Abstract
Management of radiological incidental findings (IF) is of rising importance; however, psychosocial implications of IF reporting remain unclear. We compared long-term psychosocial effects between individuals who underwent whole-body magnetic resonance imaging (MRI) with and without reported IF, and individuals who did not undergo [...] Read more.
Management of radiological incidental findings (IF) is of rising importance; however, psychosocial implications of IF reporting remain unclear. We compared long-term psychosocial effects between individuals who underwent whole-body magnetic resonance imaging (MRI) with and without reported IF, and individuals who did not undergo imaging. We used a longitudinal population-based cohort from Western Europe. Longitudinal analysis included three examinations (exam 1, 6 years prior to MRI; exam 2, MRI; exam 3, 4 years after MRI). Psychosocial outcomes included PHQ-9 (Patient Health Questionnaire), DEEX (Depression and Exhaustion Scale), PSS-10 (Perceived Stress Scale) and a Somatization Scale. Univariate analyses and adjusted linear mixed models were calculated. Among 855 included individuals, 25% (n = 212) underwent MRI and 6% (n = 50) had at least one reported IF. Compared to MRI participants, non-participants had a higher psychosocial burden indicated by PHQ-9 in exam 1 (3.3 ± 3.3 vs. 2.5 ± 2.3) and DEEX (8.6 ± 4.7 vs. 7.7 ± 4.4), Somatization Scale (5.9 ± 4.3 vs. 4.8 ± 3.8) and PSS-10 (14.7 ± 5.7 vs. 13.7 ± 5.3, all p < 0.05) in exam 3. MRI participation without IF reporting was significantly associated with lower values of DEEX, PHQ-9 and Somatization Scale. There were no significant differences at the three timepoints between MRI participants with and without IF. In conclusion, individuals who voluntarily participated in whole-body MRI had less psychosocial burden and imaging and IF reporting were not associated with adverse long-term psychosocial consequences. However, due to the study design we cannot conclude that the MRI exam itself represented a beneficial intervention causing improvement in mental health scores. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

11 pages, 3084 KiB  
Article
Granulomatous Prostatitis, the Great Mimicker of Prostate Cancer: Can Multiparametric MRI Features Help in This Challenging Differential Diagnosis?
by Elena Bertelli, Giulia Zantonelli, Alberto Cinelli, Sandro Pastacaldi, Simone Agostini, Emanuele Neri and Vittorio Miele
Diagnostics 2022, 12(10), 2302; https://doi.org/10.3390/diagnostics12102302 - 23 Sep 2022
Cited by 11 | Viewed by 2276
Abstract
Clinico-radiological presentation of granulomatous prostatitis (GP) is quite similar to cancer, and differential diagnosis can be very challenging. The study aims to highlight GP features based on clinical findings and multiparametric magnetic resonance imaging (mpMRI) characteristics. We retrospectively reviewed eleven patients from a [...] Read more.
Clinico-radiological presentation of granulomatous prostatitis (GP) is quite similar to cancer, and differential diagnosis can be very challenging. The study aims to highlight GP features based on clinical findings and multiparametric magnetic resonance imaging (mpMRI) characteristics. We retrospectively reviewed eleven patients from a cohort undergoing targeted biopsy between August 2019 and August 2021. Retrospective data including serum prostate-specific antigen (PSA) levels, PSA density and mpMRI findings were collected. Histopathology revealed seven cases of non-specific GP and four cases of specific GP as a result of intravesical Bacillus Calmette–Guérin (BCG) instillation. All lesions showed low signal intensity in T2w images, restricted diffusivity with hyperintensity in Diffusion-Weighted Imaging (DWI) and low Apparent Diffusion Coefficient (ADC) values. In Dynamic Contrast-Enhanced (DCE) imaging, the enhancement was high-peak and persistent in the majority of cases, especially in BCG-GPs. Moreover, almost all those latter lesions showed avascular core and peripheral rim enhancement. All areas identified on mpMRI were assessed with high to very high suspicion to hold prostate cancer (PIRADS v2.1 scores 4–5). Despite recent advances in imaging modalities and serological investigations, it is currently still a challenge to identify granulomatous prostatitis. Histopathology remains the gold standard in disease diagnosis. However, a differential diagnosis should be considered in patients with prior treatment with BCG. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

9 pages, 1051 KiB  
Article
Knee Muscles Composition Using Electrical Impedance Myography and Magnetic Resonance Imaging
by Domenico Albano, Salvatore Gitto, Jacopo Vitale, Susan Bernareggi, Sveva Lamorte, Alberto Aliprandi, Luca Maria Sconfienza and Carmelo Messina
Diagnostics 2022, 12(9), 2217; https://doi.org/10.3390/diagnostics12092217 - 13 Sep 2022
Cited by 1 | Viewed by 2387
Abstract
We evaluated the correlation of electrical impedance myography (EIM) measurements of knee muscles composition using Skulpt ChiselTM with MRI data retrieved from muscles segmentation. A total of 140 patients (71 females, 52 ± 21 years) underwent knee MRI, EIM with Skulpt® [...] Read more.
We evaluated the correlation of electrical impedance myography (EIM) measurements of knee muscles composition using Skulpt ChiselTM with MRI data retrieved from muscles segmentation. A total of 140 patients (71 females, 52 ± 21 years) underwent knee MRI, EIM with Skulpt®, and clinical evaluation (SARC-F questionnaire). MRIs were reviewed to assess the cross-sectional area (CSA) and skeletal muscle index (SMI = CSA/height2) of vastus medialis, vastus lateralis, biceps, semimembranosus, and sartorius. We tested the correlations of EIM-derived parameters [body fat-percentage (BF%) and muscle quality] with total CSA, CSA of each muscle, SMI, and SARC-F scores (0–10) using Pearson correlation coefficient. We found medium negative correlation of BF% with SMI (r = −0.430, p < 0.001) and total CSA (r = −0.445, p < 0.001), particularly with biceps (r = −0.479, p < 0.001), sartorius (r = −0.440, p < 0.001), and semimembranosus (r = −0.357, p < 0.001). EIM-derived muscle quality showed small-to-medium positive correlation with MRI measurements, ranging from r = 0.234 of biceps (p = 0.006) to r = 0.302 of total CSA (p < 0.001), except for vastus lateralis (r = 0.014, p = 0.873). SARC-F scores showed small correlations with EIM and MRI data, ranging from r = −0.132 (p = 0.121) with EIM muscle quality to r = −0.288 (p = 0.001) with CSA of vastus medialis. Hence, we observed small-to-medium correlations of muscle parameters derived from Skulpt ChiselTM with SARC-F scores and MRI parameters. We recommend using Skulpt ChiselTM with caution for assessing knee skeletal muscles composition. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

17 pages, 1376 KiB  
Article
Bayesian Depth-Wise Convolutional Neural Network Design for Brain Tumor MRI Classification
by Favour Ekong, Yongbin Yu, Rutherford Agbeshi Patamia, Xiao Feng, Qian Tang, Pinaki Mazumder and Jingye Cai
Diagnostics 2022, 12(7), 1657; https://doi.org/10.3390/diagnostics12071657 - 7 Jul 2022
Cited by 14 | Viewed by 2286
Abstract
In recent years, deep learning has been applied to many medical imaging fields, including medical image processing, bioinformatics, medical image classification, segmentation, and prediction tasks. Computer-aided detection systems have been widely adopted in brain tumor classification, prediction, detection, diagnosis, and segmentation tasks. This [...] Read more.
In recent years, deep learning has been applied to many medical imaging fields, including medical image processing, bioinformatics, medical image classification, segmentation, and prediction tasks. Computer-aided detection systems have been widely adopted in brain tumor classification, prediction, detection, diagnosis, and segmentation tasks. This work proposes a novel model that combines the Bayesian algorithm with depth-wise separable convolutions for accurate classification and predictions of brain tumors. We combine Bayesian modeling learning and Convolutional Neural Network learning methods for accurate prediction results to provide the radiologists the means to classify the Magnetic Resonance Imaging (MRI) images rapidly. After thorough experimental analysis, our proposed model outperforms other state-of-the-art models in terms of validation accuracy, training accuracy, F1-score, recall, and precision. Our model obtained high performances of 99.03% training accuracy and 94.32% validation accuracy, F1-score, precision, and recall values of 0.94, 0.95, and 0.94, respectively. To the best of our knowledge, the proposed work is the first neural network model that combines the hybrid effect of depth-wise separable convolutions with the Bayesian algorithm using encoders. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

7 pages, 720 KiB  
Article
MRI Segmentation of Cervical Muscle Volumes in Survived Strangulation: Is There an Association between Side Differences in Muscle Volume and the Handedness of the Perpetrator? A Retrospective Study
by Marc Marty, Akos Dobay, Lars Ebert, Sebastian Winklhofer, Michael Thali, Jakob Heimer and Sabine Franckenberg
Diagnostics 2022, 12(3), 743; https://doi.org/10.3390/diagnostics12030743 - 18 Mar 2022
Cited by 2 | Viewed by 1776
Abstract
We evaluate the potential value of magnetic resonance imaging (MRI) in the examination of survivors of manual strangulation. Our hypothesis was that trauma-induced edema of the cervical muscles might lead to a side difference in the muscle volumes, associated with the handedness of [...] Read more.
We evaluate the potential value of magnetic resonance imaging (MRI) in the examination of survivors of manual strangulation. Our hypothesis was that trauma-induced edema of the cervical muscles might lead to a side difference in the muscle volumes, associated with the handedness of the perpetrator. In 50 individuals who survived strangulation, we performed MRI-based segmentation of the cervical muscle volumes. As a control group, the neck MRIs of 10 clinical patients without prior trauma were used. The ratio of the right to left muscle volume was calculated for each muscle group of the control and strangulation groups. Cutoff values for the assumed physiological muscle volume ratios between the right and left sides were identified from our control group. There was no significant difference among the individuals in the pathological muscle volume ratio between right-handed versus both-handed strangulation for the sternocleidomastoid, pretracheal, anterior deep, or trapezoid muscle groups. Only the posterior deep muscle group showed a statistically significant difference in the pathological muscle volume ratio for both-handed strangulations (p = 0.011). Measurement of side differences in cervical muscle volume does not allow for a conclusion concerning the probable handedness of the perpetrator. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

17 pages, 4351 KiB  
Article
Assessment of Bone Microarchitecture in Fresh Cadaveric Human Femurs: What Could Be the Clinical Relevance of Ultra-High Field MRI
by Enrico Soldati, Martine Pithioux, Daphne Guenoun, David Bendahan and Jerome Vicente
Diagnostics 2022, 12(2), 439; https://doi.org/10.3390/diagnostics12020439 - 8 Feb 2022
Cited by 4 | Viewed by 2389
Abstract
MRI could be applied for bone microarchitecture assessment; however, this technique is still suffering from low resolution compared to the trabecular dimension. A clear comparative analysis between MRI and X-ray microcomputed tomography (μCT) regarding microarchitecture metrics is still lacking. In this study, we [...] Read more.
MRI could be applied for bone microarchitecture assessment; however, this technique is still suffering from low resolution compared to the trabecular dimension. A clear comparative analysis between MRI and X-ray microcomputed tomography (μCT) regarding microarchitecture metrics is still lacking. In this study, we performed a comparative analysis between μCT and 7T MRI with the aim of assessing the image resolution effect on the accuracy of microarchitecture metrics. We also addressed the issue of air bubble artifacts in cadaveric bones. Three fresh cadaveric femur heads were scanned using 7T MRI and µCT at high resolution (0.051 mm). Samples were submitted to a vacuum procedure combined with vibration to reduce the volume of air bubbles. Trabecular interconnectivity, a new metric, and conventional histomorphometric parameters were quantified using MR images and compared to those derived from µCT at full resolution and downsized resolutions (0.102 and 0.153 mm). Correlations between bone morphology and mineral density (BMD) were evaluated. Air bubbles were reduced by 99.8% in 30 min, leaving partial volume effects as the only source of bias. Morphological parameters quantified with 7T MRI were not statistically different (p > 0.01) to those computed from μCT images, with error up to 8% for both bone volume fraction and trabecular spacing. No linear correlation was found between BMD and all morphological parameters except trabecular interconnectivity (R2 = 0.69 for 7T MRI-BMD). These results strongly suggest that 7T MRI could be of interest for in vivo bone microarchitecture assessment, providing additional information about bone health and quality. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

15 pages, 2351 KiB  
Article
Before and after Endovascular Aortic Repair in the Same Patients with Aortic Dissection: A Cohort Study of Four-Dimensional Phase-Contrast Magnetic Resonance Imaging
by Chien-Wei Chen, Yueh-Fu Fang, Yuan-Hsi Tseng, Min Yi Wong, Yu-Hui Lin, Yin-Chen Hsu, Bor-Shyh Lin and Yao-Kuang Huang
Diagnostics 2021, 11(10), 1912; https://doi.org/10.3390/diagnostics11101912 - 15 Oct 2021
Cited by 1 | Viewed by 2254
Abstract
(1) Background: We used four-dimensional phase-contrast magnetic resonance imaging (4D PC-MRI) to evaluate the impact of an endovascular aortic repair (TEVAR) on aortic dissection. (2) Methods: A total of 10 patients received 4D PC-MRI on a 1.5-T MR both before and after TEVAR. [...] Read more.
(1) Background: We used four-dimensional phase-contrast magnetic resonance imaging (4D PC-MRI) to evaluate the impact of an endovascular aortic repair (TEVAR) on aortic dissection. (2) Methods: A total of 10 patients received 4D PC-MRI on a 1.5-T MR both before and after TEVAR. (3) Results: The aortas were repaired with either a GORE TAG Stent (Gore Medical; n = 7) or Zenith Dissection Endovascular Stent (Cook Medical; n = 3). TEVAR increased the forward flow volume of the true lumen (TL) (at the abdominal aorta, p = 0.047). TEVAR also reduced the regurgitant fraction in the TL at the descending aorta but increased it in the false lumen (FL). After TEVAR, the stroke distance increased in the TL (at descending and abdominal aorta, p = 0.018 and 0.015), indicating more effective blood transport per heartbeat. Post-stenting quantitative flow revealed that the reductions in stroke volume, backward flow volume, and absolute stroke volume were greater when covered stents were used than when bare stents were used in the FL of the descending aorta. Bare stents had a higher backward flow volume than covered stents did. (4) Conclusions: TEVAR increased the stroke volume in the TL and increased the regurgitant fraction in the FL in patients with aortic dissection. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

20 pages, 8172 KiB  
Article
Validation and Optimization of Proximal Femurs Microstructure Analysis Using High Field and Ultra-High Field MRI
by Enrico Soldati, Jerome Vicente, Daphne Guenoun, David Bendahan and Martine Pithioux
Diagnostics 2021, 11(9), 1603; https://doi.org/10.3390/diagnostics11091603 - 2 Sep 2021
Cited by 3 | Viewed by 2676
Abstract
Trabecular bone could be assessed non-invasively using MRI. However, MRI does not yet provide resolutions lower than trabecular thickness and a comparative analysis between different MRI sequences at different field strengths and X-ray microtomography (μCT) is still missing. In this study, we compared [...] Read more.
Trabecular bone could be assessed non-invasively using MRI. However, MRI does not yet provide resolutions lower than trabecular thickness and a comparative analysis between different MRI sequences at different field strengths and X-ray microtomography (μCT) is still missing. In this study, we compared bone microstructure parameters and bone mineral density (BMD) computed using various MRI approaches, i.e., turbo spin echo (TSE) and gradient recalled echo (GRE) images used at different magnetic fields, i.e., 7T and 3T. The corresponding parameters computed from μCT images and BMD derived from dual-energy X-ray absorptiometry (DXA) were used as the ground truth. The correlation between morphological parameters, BMD and fracture load assessed by mechanical compression tests was evaluated. Histomorphometric parameters showed a good agreement between 7T TSE and μCT, with 8% error for trabecular thickness with no significative statistical difference and a good intraclass correlation coefficient (ICC > 0.5) for all the extrapolated parameters. No correlation was found between DXA-BMD and all morphological parameters, except for trabecular interconnectivity (R2 > 0.69). Good correlation (p-value < 0.05) was found between failure load and trabecular interconnectivity (R2 > 0.79). These results suggest that MRI could be of interest for bone microstructure assessment. Moreover, the combination of morphological parameters and BMD could provide a more comprehensive view of bone quality. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

11 pages, 15811 KiB  
Article
Diagnostic Value of Whole-Body MRI Short Protocols in Bone Lesion Detection in Multiple Myeloma Patients
by Davide Ippolito, Teresa Giandola, Cesare Maino, Davide Gandola, Maria Ragusi, Paolo Brambilla, Pietro Andrea Bonaffini and Sandro Sironi
Diagnostics 2021, 11(6), 1053; https://doi.org/10.3390/diagnostics11061053 - 8 Jun 2021
Cited by 1 | Viewed by 4116
Abstract
The aim of the study is to evaluate the effectiveness of short whole-body magnetic resonance imaging (WBMRI) protocols for the overall assessment of bone marrow involvement in patients with multiple myeloma (MM), in comparison with standard whole-body MRI protocol. Patients with biopsy-proven MM, [...] Read more.
The aim of the study is to evaluate the effectiveness of short whole-body magnetic resonance imaging (WBMRI) protocols for the overall assessment of bone marrow involvement in patients with multiple myeloma (MM), in comparison with standard whole-body MRI protocol. Patients with biopsy-proven MM, who underwent a WBMRI with full-body coverage (from vertex to feet) were retrospectively enrolled. WBMRI images were independently evaluated by two expert radiologists, in terms of infiltration patterns (normal, focal, diffuse, and combined), according to location (the whole skeleton was divided into six anatomic districts: skull, spine, sternum and ribs, upper limbs, pelvis and proximal two-thirds of the femur, remaining parts of lower limbs) and lytic lesions number (<5, 5–20, and >20). The majority of patients showed focal and combined infiltration patterns with bone lesions predominantly distributed in the spine and pelvis. As skull and lower limbs are less frequently involved by focal bone lesions, excluding them from the standard MRI protocol allows to obtain a shorter protocol, maintaining a good diagnostic value. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

Other

Jump to: Research

7 pages, 575 KiB  
Brief Report
Magnetic Resonance Imaging Findings Corresponding to Vasculitis as Defined via [18F]FDG Positron Emission Tomography or Ultrasound
by Andrea K. Hemmig, Christof Rottenburger, Markus Aschwanden, Christoph T. Berger, Diego Kyburz, Maurice Pradella, Daniel Staub, Stephan Imfeld, Gregor Sommer and Thomas Daikeler
Diagnostics 2023, 13(23), 3559; https://doi.org/10.3390/diagnostics13233559 - 29 Nov 2023
Cited by 1 | Viewed by 1197
Abstract
Background: We sought to investigate magnetic resonance imaging (MRI) parameters that correspond to vasculitis observed via [18F]FDG positron emission tomography/computed tomography (PET/CT) and ultrasound in patients with large-vessel giant cell arteritis (LV-GCA). Methods: We performed a cross-sectional analysis of patients diagnosed [...] Read more.
Background: We sought to investigate magnetic resonance imaging (MRI) parameters that correspond to vasculitis observed via [18F]FDG positron emission tomography/computed tomography (PET/CT) and ultrasound in patients with large-vessel giant cell arteritis (LV-GCA). Methods: We performed a cross-sectional analysis of patients diagnosed with LV-GCA. Patients were selected if MRI, PET/CT, and vascular ultrasound were performed at the time of LV-GCA diagnosis. Imaging findings in vessel segments (axillary segment per side, thoracic aorta) assessed using at least two methods were compared. Vessel wall thickening, oedema, and contrast agent enhancement were each assessed via MRI. Results: Twelve patients with newly diagnosed LV-GCA were included (seven females, 58%; median age 72.1, IQR 65.5–74.2 years). The MRI results showed mural thickening in 9/24 axillary artery segments. All but 1 segment showed concomitant oedema, and additional contrast enhancement was found in 3/9 segments. In total, 8 of these 9 segments corresponded to vasculitic findings in the respective segments as observed via PET/CT, and 2/9 corresponded to vasculitis in the respective ultrasound images. If MRI was performed more than 6 days after starting prednisone treatment, thickening and oedema were seen in only 1/24 segments, which was also pathologic according to ultrasound findings but not those obtained via PET/CT. Four patients had mural thickening, oedema, and contrast enhancement in the aorta, among whom three patients also had vasculitic findings observed via PET/CT. Isolated mural thickening in one patient corresponded to a negative PET/CT result. Conclusions: In the MRI results, mural thickening due to oedema corresponded to vasculitic PET/CT findings but not vasculitic ultrasound findings. The duration of steroid treatment may reduce the sensitivity of MRI. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

10 pages, 5378 KiB  
Technical Note
End to End Colonic Content Assessment: ColonMetry Application
by Bernat Orellana, Eva Monclús, Isabel Navazo, Álvaro Bendezú, Carolina Malagelada and Fernando Azpiroz
Diagnostics 2023, 13(5), 910; https://doi.org/10.3390/diagnostics13050910 - 28 Feb 2023
Cited by 1 | Viewed by 1621
Abstract
The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only [...] Read more.
The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be distinguished in T1 weighted images. In this paper, we present an end-to-end quasi-automatic framework that comprises all the steps needed to accurately segment the colon in T2 and T1 images and to extract colonic content and morphology data to provide the quantification of colonic content and morphology data. As a consequence, physicians have gained new insights into the effects of diets and the mechanisms of abdominal distension. Full article
(This article belongs to the Special Issue Advanced Techniques in Body Magnetic Resonance Imaging 2.0)
Show Figures

Figure 1

Back to TopTop