Quantitative MRI Analysis Research Articles

Integrated framework for quantitative T2-weighted MRI analysis following prostate cancer radiotherapy

PurposeThe aim of this study is to develop a framework for quantitative analysis of longitudinal T2-weighted MRIs (T2w) following radiotherapy (RT) for prostate cancer. Materials and methodsThe developed methodology includes: (i) deformable image registration of longitudinal series to pre-RT T2w for automated detection of prostate, peripheral zone (PZ), and gross tumor volume (GTV); and (ii) T2w signal-intensity harmonization based on three reference tissues. The REgistration and HARMonization (REHARM) framework was applied on T2w acquired in a clinical trial consisting of two pre-RT and three post-RT MRI exams. Image registration was assessed by the DICE coefficient between automatic and manual contours, and intensity normalization via inter-patient histogram intersection. Longitudinal consistency was evaluated by the repeatability coefficient and Pearson correlation (r) between the two T2w exams before RT. ResultsT2w from 107 MRI exams (23 patients) were utilized. Following REHARM, the histogram intersections for prostate, PZ and GTV increased from median = 0.43/0.16/0.13 to 0.66/0.44/0.46. The repeatability in T2w intensity estimation was better for the automatic than the manual contours for all three regions of interest (r = 0.9, p < 0.0001, for GTV). The changes in the tissues’ T2w values pre- and post-RT became significant, indicating the measurable quantitative signal related to radiation. ConclusionsThe developed methodology allows to automate longitudinal analysis reducing data acquisition-related variation and improving consistency. The quantitative characterization of RT-induced changes in T2w will lead to new understanding of radiation effects enabling prediction modeling of RT response.

Qualitative and quantitative MRI analysis of alveolar soft part sarcoma: correlation with histological grade and Ki-67 expression

ObjectiveTo investigate the correlation between MRI findings and histological features for preoperative prediction of histological grading and Ki-67 expression level in alveolar soft part sarcoma (ASPS).MethodsA retrospective analysis was conducted on 63 ASPS patients (Jan 2017–May 2023). All patients underwent 3.0-T MRI examinations, including conventional sequences, dynamic contrast-enhanced scans with time-intensity curve analysis, and diffusion-weighted imaging with apparent diffusion coefficient (ADC) measurements. Patients were divided into low-grade (histological Grade I) and high-grade (histological Grade II/III) groups based on pathology. Immunohistochemistry was used to assess Ki-67 expression levels in ASPS. Statistical analysis included chi-square tests, Wilcoxon rank-sum test, binary logistic regression analysis, Spearman correlation analysis, and receiver operating characteristic curve analysis of various observational data.ResultsThere were 29 low-grade and 34 high-grade patients (26 males and 37 females) and a wide age range (5–68 years). Distant metastasis, tumor enhancement characteristics, and ADC values were independent predictors of high-grade ASPS. High-grade ASPS had lower ADC values (p = 0.002), with an area under the curve (AUC), sensitivity, and specificity of 0.723, 79.4%, and 58.6%, respectively, for high-grade prediction. There was a negative correlation between ADC values and Ki-67 expression (r = −0.526; p < 0.001). When the cut-off value of ADC was 0.997 × 10−3 mm²/s, the AUC, sensitivity, and specificity for predicting high Ki-67 expression were 0.805, 65.6%, and 83.9%, respectively.ConclusionQualitative and quantitative MRI parameters are valuable for predicting histological grading and Ki-67 expression levels in ASPS.Critical relevance statementThis study will help provide a more nuanced understanding of ASPS and guide personalized treatment strategies.Key PointsThere is limited research on assessing ASPS prognosis through MRI.Metastasis, enhancement, and ADC correlated with histological grade; ADC related to Ki-67 expression.MRI provides clinicians with valuable information on ASPS grading and proliferation activity.Graphical

Positional contrastive learning for improved thigh muscle segmentation in MR images.

The accurate segmentation of individual muscles is essential for quantitative MRI analysis of thigh images. Deep learning methods have achieved state-of-the-art results in segmentation, but they require large numbers of labeled data to perform well. However, labeling individual thigh muscles slice by slice for numerous volumes is a laborious and time-consuming task, which limits the availability of annotated datasets. To address this challenge, self-supervised learning (SSL) emerges as a promising technique to enhance model performance by pretraining the model on unlabeled data. A recent approach, called positional contrastive learning, exploits the information given by the axial position of the slices to learn features transferable on the segmentation task. The aim of this work was to propose positional contrastive SSL for the segmentation of individual thigh muscles from MRI acquisitions in a population of elderly healthy subjects and to evaluate it on different levels of limited annotated data. An unlabeled dataset of 72 T1w MRI thigh acquisitions was available for SSL pretraining, while a labeled dataset of 52 volumes was employed for the final segmentation task, split into training and test sets. The effectiveness of SSL pretraining to fine-tune a U-Net architecture for thigh muscle segmentation was compared with that of a randomly initialized model (RND), considering an increasing number of annotated volumes (S= 1, 2, 5, 10, 20, 30, 40). Our results demonstrated that SSL yields substantial improvements in Dice similarity coefficient (DSC) when using a very limited number of labeled volumes (e.g., for = 1, DSC 0.631 versus 0.530 for SSL and RND, respectively). Moreover, enhancements are achievable even when utilizing the full number of labeled subjects, with DSC = 0.927 for SSL and 0.924 for RND. In conclusion, positional contrastive SSL was effective in obtaining more accurate thigh muscle segmentation, even with a very low number of labeled data, with a potential impact of speeding up the annotation process in clinics.

Deep Learning-based Thigh Muscle Investigation Using MRI For Prosthetic Development for Patients Undergoing Total Knee Replacement (TKR).

A prosthetic device is designed based on the quantitative analysis of muscle MRI which will improve the muscle control achieved with functional electrical stimulation/ guided robotic exoskeletons. Electromyography (EMG) provides muscle functionality information while MRI provides the physiological and functionality of muscles. The sensor feedbacks were used for the bionic prosthesis, but the length of muscle using image processing was not correlated. To investigate and perform qualitative and quantitative assessment of thigh muscle using MRI. The objective of the work is to improve the existing VAG signal classification method to diagnose abnormality using MRI for patients undergoing Total knee replacement (TKR). A deep learning method for qualitative and quantitative assessment of thigh muscle is done using MRI. In existing prosthetic devices, electrical measurements of a person's muscles are obtained using surface or implantable electrodes. Several methods were used for the classification and diagnostic processes. The existing methods have drawbacks in feature extraction and require experts to design the system. This work combines medical image processing and orthopaedic prosthetics to develop a therapeutic method. This design provides much more precise control of prosthetic limbs using the image processing technique. The hybrid CNN swarm-based method measures the muscle structure and functions. Along with the sensor readings, these details are combined for prosthetic control. The implementation was carried out in MATLAB, Sketchuppro, and Arduino IDE. A combined swarm intelligence and deep learning method were proposed for qualitative and quantitative assessment of thigh muscle. The prosthetic device choice was done from the scanned MRI image like Humerus-T prosthetics, segmental prosthesis and arthrodesis prosthesis. The investigation was done for the Total knee replacement (TKR) approach.

Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosis

BackgroundOsteoporosis is a serious global public health issue. Currently, there are few studies that explore the use of multiparametric MRI radiomics for osteoporosis detection. The purpose of this study was to compare the performance of radiomics features from multiple MRI sequences (T1WI, T2WI and T1WI combined with T2WI) for detecting osteoporosis in patients.MethodsA retrospective analysis was performed on 160 patients who had undergone dual-energy X-ray absorptiometry(DXA) and lumbar magnetic resonance imaging (MRI) at our hospital. Among them, 86 patients were diagnosed with abnormal bone mass (osteoporosis or low bone mass), and 74 patients were diagnosed with normal bone mass based on the DXA results. Sagittal T1-and T2-weighted images of all patients were imported into the uAI Research Portal (United Imaging Intelligence) for image delineation and radiomics analysis, where a series of radiomic features were obtained. A radiomic model that included T1WI, T2WI, and T1WI+T2WI was established using features selected by LASSO regression. We used ROC curve analysis to evaluate the predictive efficacy of each model for identifying bone abnormalities and conducted decision curve analysis (DCA) to evaluate the net benefit of each model. Finally, we validated the model in a sample of 35 patients from different health care institution.ResultsThe T1WI + T2WI radiomics model showed better screening performance for patients with abnormal bone mass. In the training group, the sensitivity was 0.758, the specificity was 0.78, and the accuracy was 0.768 (AUC =0.839, 95% CI=0.757-0.901). In the validation group, the sensitivity was 0.792, the specificity was 0.875, and the accuracy was 0.833 (AUC =0.86, 95% CI=0.73-0.943).The DCA also showed that the combined model had better net benefits. In the external validation group, the sensitivity was 0.764, the specificity was 0.833, and the accuracy was 0.8 (AUC =0.824, 95% CI 0.678-0.969).ConclusionsRadiomics-based multiparametric MRI can be used for the quantitative analysis of lumbar MRI and for accurately screening patients with abnormal bone mass.

MRI-based prostate cancer classification using 3D efficient capsule network.

Prostate cancer (PCa) is the most common cancer in men and the second leading cause of male cancer-related death. Gleason score (GS) is the primary driver of PCa risk-stratification and medical decision-making, but can only be assessed at present via biopsy under anesthesia. Magnetic resonance imaging (MRI) is a promising non-invasive method to further characterize PCa, providing additional anatomical and functional information. Meanwhile, the diagnostic power of MRI is limited by qualitative or, at best, semi-quantitative interpretation criteria, leading to inter-reader variability. Computer-aided diagnosis employing quantitative MRI analysis has yielded promising results in non-invasive prediction of GS. However, convolutional neural networks (CNNs) do not implicitly impose a frame of reference to the objects. Thus, CNNs do not encode the positional information properly, limiting method robustness against simple image variations such as flipping, scaling, or rotation. Capsule network (CapsNet) has been proposed to address this limitation and achieves promising results in this domain. In this study, we develop a 3D Efficient CapsNet to stratify GS-derived PCa risk using T2-weighted (T2W) MRI images. In our method, we used 3D CNN modules to extract spatial features and primary capsule layers to encode vector features. We then propose to integrate fully-connected capsule layers (FC Caps) to create a deeper hierarchy for PCa grading prediction. FC Caps comprises a secondary capsule layer which routes active primary capsules and a final capsule layer which outputs PCa risk. To account for data imbalance, we propose a novel dynamic weighted margin loss. We evaluate our method on a public PCa T2W MRI dataset from the Cancer Imaging Archive containing data from 976 patients. Two groups of experiments were performed: (1) we first identified high-risk disease by classifying low + medium risk versus high risk; (2) we then stratified disease in one-versus-one fashion: low versus high risk, medium versus high risk, and low versus medium risk. Five-fold cross validation was performed. Our model achieved an area under receiver operating characteristic curve (AUC) of 0.83 and 0.64 F1-score for low versus high grade, 0.79 AUC and 0.75 F1-score for low + medium versus high grade, 0.75 AUC and 0.69 F1-score for medium versus high grade and 0.59 AUC and 0.57 F1-score for low versus medium grade. Our method outperformed state-of-the-art radiomics-based classification and deep learning methods with the highest metrics for each experiment. Our divide-and-conquer strategy achieved weighted Cohen's Kappa score of 0.41, suggesting moderate agreement with ground truth PCa risks. In this study, we proposed a novel 3D Efficient CapsNet for PCa risk stratification and demonstrated its feasibility. This developed tool provided a non-invasive approach to assess PCa risk from T2W MR images, which might have potential to personalize the treatment of PCa and reduce the number of unnecessary biopsies.

Psychometric evaluation of the 5-item Medication Adherence Report Scale questionnaire in persons with multiple sclerosis.

The 5-item Medication Adherence Report Scale (MARS-5) is a reliable and valid questionnaire for evaluating adherence in patients with asthma, hypertension, and diabetes. Validity has not been determined in multiple sclerosis (MS). We aimed to establish criterion validity and reliability of the MARS-5 in persons with MS (PwMS). Our prospective study included PwMS on dimethyl fumarate (DMF). PwMS self-completed the MARS-5 on the same day before baseline and follow-up brain magnetic resonance imaging (MRI) 3 and 9 months after treatment initiation and were graded as highly and medium adherent upon the 24-cut-off score, established by receiver operator curve analysis. Health outcomes were represented by relapse occurrence from the 1st DMF dispense till follow-up brain MRI and radiological progression (new T2 MRI lesions and quantitative analysis) between baseline and follow-up MRI. Criterion validity was established by association with the Proportion of Days Covered (PDC), new T2 MRI lesions, and Beliefs in Medicines questionnaire (BMQ). The reliability evaluation included internal consistency and the test-retest method. We included 40 PwMS (age 37.6 ± 9.9 years, 75% women), 34 were treatment-naive. No relapses were seen during the follow-up period but quantitative MRI analysis showed new T2 lesions in 6 PwMS. The mean (SD) MARS-5 score was 23.1 (2.5), with 24 PwMS graded as highly adherent. The higher MARS-5 score was associated with higher PDC (b = 0.027, P<0.001, 95% CI: (0.0134-0.0403)) and lower medication concerns (b = -1.25, P<0.001, 95% CI: (-1.93-(-0,579)). Lower adherence was associated with increased number (P = 0.00148) and total volume of new T2 MRI lesions (P = 0.00149). The questionnaire showed acceptable internal consistency (Cronbach α = 0.72) and moderate test-retest reliability (r = 0.62, P < 0.0001, 95% CI: 0.33-0.79). The MARS-5 was found to be valid and reliable for estimating medication adherence and predicting medication concerns in persons with MS.

Quantitative Analysis of Prostate MRI: Correlation between Contrast-Enhanced Magnetic Resonance Fingerprinting and Dynamic Contrast-Enhanced MRI Parameters.

This research aimed to assess the relationship between contrast-enhanced (CE) magnetic resonance fingerprinting (MRF) values and dynamic contrast-enhanced (DCE) MRI parameters including (Ktrans, Kep, Ve, and iAUC). To evaluate the correlation between the MRF-derived values (T1 and T2 values, CE T1 and T2 values, T1 and T2 change) and DCE-MRI parameters and the differences in the parameters between prostate cancer and noncancer lesions in 68 patients, two radiologists independently drew regions-of-interest (ROIs) at the focal prostate lesions. Prostate cancer was identified in 75% (51/68) of patients. The CE T2 value was significantly lower in prostate cancer than in noncancer lesions in the peripheral zone and transition zone. Ktrans, Kep, and iAUC were significantly higher in prostate cancer than noncancer lesions in the peripheral zone (p < 0.05), but not in the transition zone. The CE T1 value was significantly correlated with Ktrans, Ve, and iAUC in prostate cancer, and the CE T2 value was correlated to Ve in noncancer. Some CE MRF values are different between prostate cancer and noncancer tissues and correlate with DCE-MRI parameters. Prostate cancer and noncancer tissues may have different characteristics regarding contrast enhancement.

Three-Dimensional Quantitative Magnetic Resonance Imaging Cartilage Evaluation of the Hand Joints of Systemic Sclerosis Patients: A Novel Insight on Hand Osteoarthritis Pathogenesis—Preliminary Report

Background. Osteoarthritis of the hand joints in systemic sclerosis (SSc) patients might be an independent manifestation leading to limitation of upper extremity function. There is no publication quantitatively assessing the thickness of articular cartilage within the hand joints of SSc patients by MRI. The purpose of our study was to quantify the condition and thickness of hand joints cartilage with three-dimensional quantitative MRI (3D q-MRI). Methods. The study was conducted in twenty people: ten patients with SSc and ten healthy individuals. All participants were examined with the 3D q-MRI with 3T scanner. The cartilage thickness of proximal (PIP) and distal interphalangeal (DIP) joints as well as metacarpophalangeal joints was measured. Results. There was no significant difference in cartilage thickness between both groups. However, the joint cartilage was thinner in fingers with acro-osteolysis. In PIP joint of the fingers with acro-osteolysis, the mean cartilage thickness was 0.5 mm (p = 0.0043) and 0.4 mm (p = 0.0034) in DIP joints. Conclusions. Quantitative MRI analysis of the joints of the hands of SSc patients does not indicate changes in thickness of the articular cartilage. A significant reduction in the articular cartilage thickness of the fingers with acro-osteolysis indicates the potential of an ischemic basis of articular cartilage destruction in SSc patients.

The application of quantitative perfusion analysis of golden-angle radial sparse parallel MRI and R2∗ value for predicting pathological prognostic factors in rectal cancer

To investigate the diagnostic value of golden-angle radial sparse parallel magnetic resonance imaging (MRI) (GRASP) and R2∗ in predicting the prognostic factors of resectable rectal cancer. A total of 108 patients with rectal adenocarcinoma were included in this retrospective study. The volume transfer constant (Ktrans), rate constant (Kep), plasma volume fraction (Ve), and R2∗ were obtained. Univariate and multivariate logistic regression were conducted. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the imaging parameters. The Ktrans was found to be significantly higher in rectal cancers with positive lymph node metastasis (LNM), higher tumour grade, positive lymphovascular invasion (LVI), and higher ki-67 (all p<0.05). The Kep was also significantly higher in the LNM-positive group (p<0.001), while the R2∗ was higher in rectal cancers with LNM-positive, higher tumour grade, LVI-positive, and higher ki-67 (all p<0.05). Combining the Ktrans and R2∗ provided the highest area under the ROC curve (AUC) for LNM-positive and higher ki-67 tumours differentiation (0.790 and 0.823, respectively). Combining quantitative parameters of the Ktrans and R2∗ could be used to non-invasively predict pathological prognostic factors preoperatively.

Quantitative MRI Analysis of Brachial Plexus and Limb-Girdle Muscles in Upper Extremity Onset Amyotrophic Lateral Sclerosis.

Recent evidence highlights the potential of axonal degeneration as a biomarker for amyotrophic lateral sclerosis (ALS) detection. However, the diagnostic potential of peripheral nerve axon changes in ALS remains unclear. To evaluate the diagnostic performance of quantitative MRI of the brachial plexus and limb-girdle muscles (LGMs) in patients with upper extremity onset of ALS. Retrospective. 47 patients with upper extremity onset of ALS and 20 healthy volunteers. 3-T, three-dimensional sampling perfection with application-optimized contrasts using different flip angle evolutions with short-tau inversion recovery sequences, T2-weighted turbo spin-echo Dixon sequence. The cross-sectional area (CSA) and nerve-muscle T2 signal intensity ratio (nT2) of the bilateral brachial plexus as well as the CSA and fat fraction (FF) of the bilateral LGMs were assessed by two radiologists. Disease severity and clinical stage of ALS patients were assessed by two neurologists. Student's t-test, Wilcoxon rank-sum test, binary logistic regression, interclass correlation coefficient, receiver operating characteristic analysis, and correlation analysis were performed for MRI quantitative metrics and clinical variables. Significance level: P < 0.05. In the affected limbs of patients with ALS, the CSA of the brachial plexus roots, trunks, and cords and the nT2 values of the brachial plexus trunks were significantly smaller than in the healthy controls. In the LGMs, the affected limbs of ALS showed significantly smaller CSA and higher FF than controls. The model containing parameters such as brachial plexus trunk CSA, subscapularis CSA, infraspinatus CSA, and subscapularis FF had excellent diagnostic efficacy for ALS. Additionally, increased subscapularis FF and supraspinatus FF were correlated with disease severity, and subscapularis CSA was negatively correlated with the clinical stage. Brachial plexus thinning, LGM atrophy, and fatty infiltration might serve as MRI-derived biomarkers for ALS with upper extremity onset. 4 TECHNICAL EFFICACY: Stage 2.

Quantitative Analysis of Whole-Body MRI for Accessing the Degree of Diffuse Infiltration Patterns and Identifying High Risk Cases of Newly Diagnosed Multiple Myeloma.

Accurate identification of high-risk multiple myeloma (HRMM) is important for prognostication. The degree of diffuse infiltration patterns on magnetic resonance imaging (MRI) is associated with patient prognosis in multiple myeloma. However, objective indexes to determine the degree of diffuse infiltration patterns are unavailable. To investigate whether qualitative and quantitative evaluations of diffuse infiltration patterns on MRI could identify HRMM. Retrospective. Totally, 180 patients (79 HRMM and 101 standard-risk MM) were assessed. The presence of del(17p), t(4;14), t(14;16), t(14;20), gain 1q, and/or p53 mutations was considered to indicate HRMM. 3.0 T/diffusion-weighted whole-body imaging with background body signal suppression (DWIBS), modified Dixon chemical-shift imaging Quant (mDIXON Quant), and short TI inversion recovery (STIR). Qualitative analysis involved assessing the degree of diffuse marrow infiltration (mild, moderate, or severe), and quantitative analysis involved evaluating apparent diffusion coefficient (ADC), fat fraction (FF), and T2* values. Clinical data such as sex, age, hemoglobin, serum albumin, serum calcium, serum creatinine, serum lactate dehydrogenase, β2-microglobulin, and bone marrow plasma cells (BMPCs) were also included. Univariate and multivariate analyses, receiver operating characteristic (ROC) curve. P < 0.05 was considered statistically significant. The high-risk group had significantly higher ADC and T2* and lower FF compared with the standard-risk group. Multivariate analysis indicated BMPCs as a significant independent risk factor for HRMM (odds ratio (OR) = 1.019, 95% CI 1.004-1.033), while FF was a significant independent protective factor associated with HRMM (OR = 0.972, 95% CI 0.946-0.999). The combination of BMPCs and FF achieved the highest areas under the curve (AUC) of 0.732, with sensitivity and specificity of 70.9% and 68.3%, respectively. Compared with qualitative analysis, FF value was independently associated with HRMM. The quantitative features of diffuse marrow infiltration on MRI scans are more effective in detecting HRMM. 3 TECHNICAL EFFICACY: Stage 2.

Quantitative Correlation Analysis of TCM Syndrome Types and Brain MRI in Wilson's Disease

Quantitative Correlation Analysis of TCM Syndrome Types and Brain MRI in Wilson's Disease

Poster 248: Lateral extra-articular tenodesis augmentation of anterior cruciate ligament reconstruction does not impact cartilage health in the patellofemoral joint based on post-operative two year qualitative and quantitative MRI analysis

Objectives: Lateral extra-articular tenodesis (LET) augmentation of anterior cruciate ligament reconstruction (ACLR) has been shown in multiple clinical and biomechanics studies to be an effective procedure to control rotational laxity, reducing failure rates. However, it is uncertain whether augmentation with an iliotibial band based LET may cause increased contact pressure in the patellofemoral joint (PFJ), resulting in cartilage damage. The purpose of the current study was to assess PFJ cartilage status in patients that underwent ACLR with or without LET augmentation using magnetic resonance imaging (MRI). It was hypothesized that 1) the addition of LET at the time of ACLR would have no effect on cartilage health on post-operative two-year MRI; 2) higher cartilage relaxation values would be associated with worse patient reported and functional outcomes at two years post-operatively. Methods: A subset of patients from the STABILITY 1 randomized controlled trial were included. All patients underwent primary ACLR with a hamstring autograft. The patients were randomized either to receive LET augmentation (modified Lemaire technique) or not. Cartilage status in the PFJ between ACLR alone group and ACLR+LET group were compared by quantitative MRI (qMRI) analysis of T2 and T1 rho sequences (figure 1), and qualitative assessment by ACL osteoarthritis score (ACLOAS) on post-operative two year MRI for surgical and contralateral non-surgical knees. Objective functional outcomes (range of motion (ROM), hop test and isokinetic strength) and patient reported outcome measures including Knee injury Osteoarthritis and Outcome Score (KOOS) and International Knee Documentation Committee (IKDC) score were attained. Descriptive statistics were calculated for each group using means and standard deviations (SD) for continuous variables and proportions for categorical variables. ANCOVA was used to determine the adjusted mean difference in T1rho and T2 relaxation times between groups for each compartment in the patella and trochlea. Spearman’s rho was used to assess the correlation between relaxation times within each compartment and patient-reported and functional outcomes at two-years postoperative. Statistical significance was set at P = 0.05. Results: Ninety-two patients (43 patients in ACLR group, mean age (±SD) 18.9±3.2 years, 60.5% female, and 49 patients in ACLR+LET group, 18.7±3.2 years, 63.3% females) were included. No significant differences were seen in patient background, meniscal treatment and cartilage status at the time of surgery (table 1). No significant differences were seen in the mean values (milliseconds) for qMRI for adjusted T1 rho relaxation times in the medial patella (MP) (47.8 vs 47.3), central patella (CP) (45.5 vs 44.1), and lateral patella (LP) (48.2 vs 47.3), and medial trochlea (MT) (54.7 vs 56.4), central trochlea (CT) (53.3 vs 53.1), and lateral trochlea (LT) (54.9 vs 53.9), and adjusted T2 relaxation times in MP (42.2 vs 43.2), CP (42.5 vs 42.7), LP (43.5 vs 43.0), MT (50.9 vs 50.9), CT (51.1 vs 52.0), LT (52.1 vs 52.6) between ACLR and ACLR+LET groups. Similarly, no difference in ACLOAS scores (overall score 10 vs 11, p = 0.99) were observed. An increase in medial patellar T2 relaxation times were associated with decreasing IKDC score (p = 0.046), KOOS symptoms subscale (p = 0.01), and total KOOS score (p = 0.01). Increasing limb symmetry on the hop test was associated with increasing T1ρ (p = 0.04) and T2 (p = 0.01) relaxation in the lateral trochlea Conclusions: No difference was found in patellofemoral cartilage health between knees undergoing primary ACLR with hamstring tendon autograft with or without LET at two years post-operative. Statistically significant correlations were found between qMRI relaxation times and functional outcome scores and PROMs, however the correlations were weak and the clinical significance of these changes are undetermined. [Table: see text]

Quantitative magnetic resonance spectroscopy and imaging analysis of the lipid content in the psoas major and its association with intervertebral disc degeneration: a cross-sectional study

Aim: It is shown that the diminished function of the psoas major is mainly associated with increased lipid content; nonetheless, whether the fat content of the psoas major is associated with intervertebral disc degeneration (IVDD) is still under study. It is hypothesized that IVDD is correlated with the lipid content of the psoas major and that IVDD can be comprehensively investigated using quantitative magnetic resonance imaging (MRI). Consequently, this study aimed to analyse the association between the psoas major extramyocellular lipid (EMCL) and intramyocellular lipid (IMCL) content and disc degeneration quantified using MRI T2 mapping in patients with chronic low back pain (CLBP). Methods: In this study, 20 men and 23 women (mean age, 63.1 years ± 2.6 years) underwent magnetic resonance spectroscopy (MRS). The psoas major IMCL and EMCL content of patients was analysed. T2 values of the anterior annulus fibrosus (AF), nucleus pulposus (NP), and posterior AF were evaluated using MRI T2 mapping. Multiple linear regression analysis was used to determine the possible correlations of the psoas major EMCL and IMCL content with the T2 values of the anterior AF, NP, and posterior AF. Results: The EMCL content and T2 values of the anterior AF were significantly and negatively correlated [standardised partial regression coefficient (β) = −0.60, P &lt; 0.01]. There were no significant correlations between the EMCL content and T2 values of the NP (β = −0.16, P = 0.30) or posterior AF (β = −0.14, P = 0.49) or between the IMCL content and T2 values of the anterior AF (β = −0.04, P = 0.82), NP (β = 0.05, P = 0.73), or posterior AF (β = −0.11, P = 0.58). Conclusions: The EMCL content and T2 values of the anterior AF were correlated. Conversely, the IMCL content and T2 values were not correlated.

Optimal length and temporal resolution of dynamic contrast-enhanced MR imaging for the differentiation between prostate cancer and normal peripheral zone tissue.

The value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the detection of prostate cancer is controversial. There are currently insufficient peer reviewed published data or expert consensus to support routine adoption of DCE-MRI for clinical use. Thus, the objective of this study was to explore the optimal temporal resolution and measurement length for DCE-MRI to differentiate cancerous from normal prostate tissue of the peripheral zone of the prostate by non-parametric MRI analysis and to compare with a quantitative MRI analysis. Predictors of interest were onset time, relative signal intensity (RSI), wash-in slope, peak enhancement, wash-out and wash-out slope determined from non-parametric characterisation of DCE-MRI intensity-time profiles. The discriminatory power was estimated from C-statistics based on cross validation. We analyzed 54 patients with 97 prostate tissue specimens (47 prostate cancer, 50 normal prostate tissue) of the peripheral zone, mean age 63.8 years, mean prostate-specific antigen 18.9 ng/mL and mean of 10.5 days between MRI and total prostatectomy. When comparing prostate cancer tissue with normal prostate tissue, median RSI was 422% vs 330%, and wash-in slope 0.870 vs 0.539. The peak enhancement of 67 vs 42 was higher with prostate cancer tissue, while wash-out (-30% vs -23%) and wash-out slope (-0.037 vs -0.029) were lower, and the onset time (32 seconds) was comparable. The optimal C-statistics was 0.743 for temporal resolution of 8.0 seconds and measurement length of 2.5 minutes compared with 0.656 derived from a quantitative MRI analysis. This study provides evidence that the use of a non-parametric approach instead of a more established parametric approach resulted in greater precision to differentiate cancerous from normal prostate tissue of the peripheral zone of the prostate.

Lateral Extra-Articular Tenodesis Augmentation of Anterior Cruciate Ligament Reconstruction Does Not Impact Cartilage health in the patellofemoral joint based on post-operative two year qualitative and quantitative MRI analysis

Lateral Extra-Articular Tenodesis Augmentation of Anterior Cruciate Ligament Reconstruction Does Not Impact Cartilage health in the patellofemoral joint based on post-operative two year qualitative and quantitative MRI analysis

Technical note: The design and validation of a multi-modality lung phantom.

Clinically relevant models that enable certain tasks such as calibration of medical imaging devices or techniques, device validation, training healthcare professionals, and more are vital to research throughout the medical field and are referred to as phantoms. Phantoms range in complexity from a vile of water to complex designs that emulate in vivo properties. Specific phantoms that model the lungs have focused on replication of tissue properties but lack replication of the anatomy. This limits the use across multiple imaging modalities and for device testing when anatomical considerations as well as tissue properties are needed. This work reports a lung phantom design utilizing materials that accurately mimic the ultrasound and magnetic resonance imaging (MRI) properties of in vivo lungs and includes relevant anatomical equivalence. The tissue mimicking materials were selected based on published studies of the materials, through qualitative comparisons of the materials with ultrasound imaging, and quantitative MRI relaxation values. A PVC ribcage was used as the structural support. The muscle/fat combined layer and the skin layer were constructed with various types of silicone with graphite powder added as a scattering agent where appropriate. Lung tissue was mimicked with silicone foam. The pleural layer was replicated by the interface between the muscle/fat layer and the lung tissue layer, requiring no additional material. The design was validated by accurately mimicking the distinct tissue layers expected with in vivo lung ultrasound while maintaining tissue-mimicking relaxation values in MRI as compared to reported values. Comparisons between the muscle/fat material and in vivo muscle/fat tissue demonstrated a 1.9% difference in T1 relaxation and a 19.8% difference in T2 relaxation. Qualitative US and quantitative MRI analysis verified the proposed lung phantom design for accurate modeling of the human lungs.

Multi-tensor diffusion abnormalities of gray matter in an animal model of cortical dysplasia.

Focal cortical dysplasias are a type of malformations of cortical development that are a common cause of drug-resistant focal epilepsy. Surgical treatment is a viable option for some of these patients, with their outcome being highly related to complete surgical resection of lesions visible in magnetic resonance imaging (MRI). However, subtle lesions often go undetected on conventional imaging. Several methods to analyze MRI have been proposed, with the common goal of rendering subtle cortical lesions visible. However, most image-processing methods are targeted to detect the macroscopic characteristics of cortical dysplasias, which do not always correspond to the microstructural disarrangement of these cortical malformations. Quantitative analysis of diffusion-weighted MRI (dMRI) enables the inference of tissue characteristics, and novel methods provide valuable microstructural features of complex tissue, including gray matter. We investigated the ability of advanced dMRI descriptors to detect diffusion abnormalities in an animal model of cortical dysplasia. For this purpose, we induced cortical dysplasia in 18 animals that were scanned at 30 postnatal days (along with 19 control animals). We obtained multi-shell dMRI, to which we fitted single and multi-tensor representations. Quantitative dMRI parameters derived from these methods were queried using a curvilinear coordinate system to sample the cortical mantle, providing inter-subject anatomical correspondence. We found region- and layer-specific diffusion abnormalities in experimental animals. Moreover, we were able to distinguish diffusion abnormalities related to altered intra-cortical tangential fibers from those associated with radial cortical fibers. Histological examinations revealed myelo-architectural abnormalities that explain the alterations observed through dMRI. The methods for dMRI acquisition and analysis used here are available in clinical settings and our work shows their clinical relevance to detect subtle cortical dysplasias through analysis of their microstructural properties.

PO-02-126 DEEP PHENOTYPING OF DSP-ENCODED DESMOPLAKIN CARRYING GENOTYPE POSITIVE UKBB SUBJECTS REVEALS ECG CHANGES AS A POSSIBLE EARLY DIAGNOSTIC MARKER OF DISEASE

Arrhythmogenic cardiomyopathy (ACM) is defined by fibrofatty replacement of the ventricular myocardium with loss of myocytes that can result in arrhythmias, sudden cardiac death, and heart failure, especially in young patients. DSP-encoded desmoplakin is a structural protein integral to the cardiac desmosome. Pathogenic variants in DSP are implicated with ACM and renders carriers uniquely susceptible to inflammation which can mimic myocarditis. Thus, there is a need to identify diagnostically informative markers which can help identify individuals with pathogenic DSP variants and ACM. The study aims to use the UK Biobank (UKBB) to describe clinical markers associated with individuals who host DSP variants that can help identify individuals with ACM predisposition. UKBB participants who had undergone whole exome sequencing, ECG, and cardiovascular MRI were selected for study. DSP variants were identified by ClinVar, InterVar, and predicted loss of function in silico modeling, and interpreted manually using ACMG criteria. Variants were matched by age and sex with controls that were genotype negative (G-) for diagnostic cardiomyopathy and ion channelopathy variants. Quantitative ECG and MRI analyses were used with ICD codes to deep phenotype participants. In 122 putative pathogenic DSP carriers (55.52 ± 7.66 years), 11 (9.0%) had atrial fibrillation and/or flutter on ECG analysis compared to 18 (4.9%) in 366 G- controls (55.52 ± 7.64 years). ECG analysis identified smaller S-wave peak amplitude in lead III (192.95 ± 298.66 vs. 287.11 ± 359.35; p=0.009), and in lead aVF (121.87 ± 199.19 vs. 169.00 ± 237.67; p=0.049) among DSP G+ vs. G- participants. Further, T-wave inversion in anterolateral leads was seen in 13 (10.7%) vs. 20 (5.5%) and in inferior leads in 20 (16.4%) vs. 37 (10.1%) in DSP G+ vs. G- controls, respectively. Individuals who host putatively pathogenic DSP variants have distinct ECG markers that may suggest early stages of ACM development, and thus may aid in guiding prognostication. Future steps include stratifying risk by pathogenicity of DSP variants by ACMG criteria to ascertain a more concrete association of likely-pathogenic variants in DSP with atrial fibrillation and/or flutter. Ongoing studies also include further characterization of DSP variants with more detailed MRI analyses with RV/LV characteristics.