Showing papers by "Sharmila Majumdar published in 2022"
TL;DR: The state of the art in the field of OA is discussed in this paper , where the authors discuss the current state of science in the disease of osteoarthritis, identify the knowledge gaps, and examine the developmental and regulatory challenges in bringing these products to market.
6 citations
TL;DR: This retrospective imaging study aims to develop an interpretable deep learning‐based detection tool for voxel‐wise mapping of MCs, due to the lack of conclusive evidence of their associations with low back pain.
Abstract: Modic changes (MCs) are the most prevalent classification system for describing magnetic resonance imaging (MRI) signal intensity changes in the vertebrae. However, there is a growing need for novel quantitative and standardized methods of characterizing these anomalies, particularly for lesions of transitional or mixed nature, due to the lack of conclusive evidence of their associations with low back pain. This retrospective imaging study aims to develop an interpretable deep learning‐based detection tool for voxel‐wise mapping of MCs.
6 citations
TL;DR: Four ROAMES phenotypes may contribute to time to radiographic OA incidence and if validated could be used as promising tool for personalized OA management.
Abstract: Our study aimed to investigate the association between time to incidence of radiographic osteoarthritis (OA) and magnetic resonance imaging (MRI)–based structural phenotypes proposed by the Rapid Osteoarthritis MRI Eligibility Score (ROAMES).
4 citations
TL;DR: Football players with FAI syndrome did not report worse burden than those with other causes of hip/groin pain and cartilage defects and/or labral tears did not explain the effect ofFAI syndrome on reported burden.
Abstract: Background: It is unknown if football players with femoroacetabular impingement (FAI) syndrome report worse burden than those with other causes of hip/groin pain, and to what extent this is mediated by cartilage defects and labral tears. Hypothesis: Football players with FAI syndrome would report worse burden than other symptomatic players, with the effect partially mediated by cartilage defects and/or labral tears. Study Design: Cross-sectional study. Level of Evidence: Level 4. Methods: Football (soccer and Australian football) players (n = 165; 35 women) with hip/groin pain (≥6 months and positive flexion–adduction–internal rotation test) were recruited. Participants completed 2 patient-reported outcome measures (PROMs; the International Hip Outcome Tool–33 [iHOT-33] and Copenhagen Hip and Groin Outcome Score [HAGOS]) and underwent hip radiographs and magnetic resonance imaging (MRI). FAI syndrome was determined to be present when cam and/or pincer morphology were present. Cartilage defects and labral tears were graded as present or absent using MRI. Linear regression models investigated relationships between FAI syndrome (dichotomous independent variable) and PROM scores (dependent variables). Mediation analyses investigated the effect of cartilage defects and labral tears on these relationships. Results: FAI syndrome was not related to PROM scores (unadjusted b values ranged from −4.693 (P = 0.23) to 0.337 (P = 0.93)) and cartilage defects and/or labral tears did not mediate its effect (P = 0.22-0.97). Conclusion: Football players with FAI syndrome did not report worse burden than those with other causes of hip/groin pain. Cartilage defects and/or labral tears did not explain the effect of FAI syndrome on reported burden. Clinical Relevance: FAI syndrome, cartilage defects, and labral tears were prevalent but unrelated to reported burden in symptomatic football players.
3 citations
TL;DR: In this paper , the authors used a deep learning pipeline to predict longitudinal bone shape changes in the femur four years in advance, using bone surfaces that were extracted in knee MRIs from the OA initiative study, via a segmentation procedure and encoded as shape maps using spherical coordinates.
3 citations
TL;DR: In this article, the potential of quantifying R2 -R1ρ using one pair of signals with T1ρ preparation and T2 preparation incorporated to magnetization-prepared angle-modulated partitioned k-space spoiled gradient-echo snapshots (MAPSS) acquisition and to find an optimal preparation time (Tprep ) for in vivo knee MRI.
Abstract: Purpose To validate the potential of quantifying R2 -R1ρ using one pair of signals with T1ρ preparation and T2 preparation incorporated to magnetization-prepared angle-modulated partitioned k-space spoiled gradient-echo snapshots (MAPSS) acquisition and to find an optimal preparation time (Tprep ) for in vivo knee MRI. Methods Bloch equation simulations were first performed to assess the accuracy of quantifying R2 -R1ρ using T1ρ - and T2 -prepared signals with an equivalent Tprep . For validation of this technique in comparison to the conventional approach that calculates R2 -R1ρ after estimating both T2 and T1ρ , phantom experiments and in vivo validation with five healthy subjects and five osteoarthritis patients were performed at a clinical 3T scanner. Results Bloch equation simulations demonstrated that the accuracy of this efficient R2 -R1ρ quantification method and the optimal Tprep can be affected by image signal-to-noise ratio (SNR) and tissue relaxation times, but quantification can be closest to the reference with an around 25 ms Tprep for knee cartilage. Phantom experiments demonstrated that the proposed method can depict R2 -R1ρ changes with agarose gel concentration. With in vivo data, significant correlation was observed between cartilage R2 -R1ρ measured from the conventional and the proposed methods, and a Tprep of 25.6 ms provided the most agreement by Bland-Altman analysis. R2 -R1ρ was significantly lower in patients than in healthy subjects for most cartilage compartments. Conclusion As a potential biomarker to indicate cartilage degeneration, R2 -R1ρ can be efficiently measured using one pair of T1ρ -prepared and T2 -prepared signals with an optimal Tprep considering cartilage relaxation times and image SNR.
3 citations
TL;DR: In this article , a recurrent UNet deep learning architecture was proposed to provide T2 maps in knee cartilage, hip cartilage and lumbar spine IVDs from accelerated T2-prepared snapshot gradient-echo acquisitions.
Abstract: MRI T2 mapping sequences quantitatively assess tissue health and depict early degenerative changes in musculoskeletal (MSK) tissues like cartilage and intervertebral discs (IVDs) but require long acquisition times. In MSK imaging, small features in cartilage and IVDs are crucial for diagnoses and must be preserved when reconstructing accelerated data. To these ends, we propose region of interest-specific postprocessing of accelerated acquisitions: a recurrent UNet deep learning architecture that provides T2 maps in knee cartilage, hip cartilage, and lumbar spine IVDs from accelerated T2-prepared snapshot gradient-echo acquisitions, optimizing for cartilage and IVD performance with a multi-component loss function that most heavily penalizes errors in those regions. Quantification errors in knee and hip cartilage were under 10% and 9% from acceleration factors R = 2 through 10, respectively, with bias for both under 3 ms for most of R = 2 through 12. In IVDs, mean quantification errors were under 12% from R = 2 through 6. A Gray Level Co-Occurrence Matrix-based scheme showed knee and hip pipelines outperformed state-of-the-art models, retaining smooth textures for most R and sharper ones through moderate R. Our methodology yields robust T2 maps while offering new approaches for optimizing and evaluating reconstruction algorithms to facilitate better preservation of small, clinically relevant features.
2 citations
TL;DR: In this article , the authors demonstrate the feasibility of substituting automatic for human-demarcated segmentation of major anatomical structures in clinical lumbar spine MRI to generate quantitative image-based features and biomechanical models.
Abstract: STUDY DESIGN
In vivo retrospective study of fully automatic quantitative imaging feature extraction from clinically acquired lumbar spine magnetic resonance imaging (MRI).
OBJECTIVE
To demonstrate the feasibility of substituting automatic for human-demarcated segmentation of major anatomical structures in clinical lumbar spine MRI to generate quantitative image-based features and biomechanical models.
SETTING
Previous studies have demonstrated the viability of automatic segmentation applied to medical images; however, the feasibility of these networks to segment clinically acquired images has not yet been demonstrated, as they largely rely on specialized sequences or strict quality of imaging data to achieve good performance.
METHODS
Convolutional neural networks were trained to demarcate vertebral bodies, intervertebral disc, and paraspinous muscles from sagittal and axial T1-weighted MRIs. Intervertebral disc height, muscle cross sectional area, and subject-specific musculoskeletal models of tissue loading in the lumbar spine were then computed from these segmentations and compared against those computed from human-demarcated masks.
RESULTS
Segmentation masks, as well as the morphological metrics and biomechanical models computed from those masks, were highly similar between human- and computer-generated methods. Segmentations were similar with Dice Similarity Coefficients 0.77 or greater across networks, morphological metrics and biomechanical models were similar with Pearson R correlation coefficients 0.69 or greater when significant.
CONCLUSIONS
This study demonstrates the feasibility of substituting computer-generated for human-generated segmentations of major anatomical structures in lumbar spine MRI to compute quantitative image-based morphological metrics and subject-specific musculoskeletal models of tissue loading quickly, efficiently, and at scale without interrupting routine clinical care.
2 citations
TL;DR: In this article , a 6-month course of oral montelukast after ACL reconstruction was shown to reduce systemic markers of inflammation and biochemical and imaging biomarkers of cartilage degradation, including prostaglandin E2, monocyte chemoattractant protein-1 and pro-inflammatory cytokines.
Abstract: After anterior cruciate ligament (ACL) reconstruction, patient-reported outcomes are improved 10 years post-surgery; however, cytokine concentrations remain elevated years after surgery with over 80% of those with combined ACL and meniscus injuries having posttraumatic osteoarthritis (PTOA) within 10-15 years. The purpose of this multicenter, randomized, placebo-controlled trial is to assess whether a 6-month course of oral montelukast after ACL reconstruction reduces systemic markers of inflammation and biochemical and imaging biomarkers of cartilage degradation.We will enroll 30 individuals undergoing primary ACL reconstruction to participate in this IRB-approved multicenter clinical trial. This trial will target those at greatest risk of a more rapid PTOA onset (age range 25-50 with concomitant meniscus injury). Patients will be randomly assigned to a group instructed to take 10 mg of montelukast daily for 6 months following ACL reconstruction or placebo. Patients will be assessed prior to surgery and 1, 6, and 12 months following surgery. To determine if montelukast alters systemic inflammation following surgery, we will compare systemic concentrations of prostaglandin E2, monocyte chemoattractant protein-1, and pro-inflammatory cytokines between groups. We will also compare degradative changes on magnetic resonance imaging (MRI) collected 1 and 12 months following surgery between groups with reductions in early biomarkers of cartilage degradation assessed with urinary biomarkers of type II collagen breakdown and bony remodeling.There is a complex interplay between the pro-inflammatory intra-articular environment, underlying bone remodeling, and progressive cartilage degradation. PTOA affects multiple tissues and appears to be more similar to rheumatoid arthritis than osteoarthritis with respect to inflammation. There is currently no treatment to delay or prevent PTOA after ACL injury. Since there is a larger and more persistent inflammatory response after ACL reconstruction than the initial insult of injury, treatment may need to be initiated after surgery, sustained over a period of time, and target multiple mechanisms in order to successfully alter the disease process. This study will assess whether a 6-month postoperative course of oral montelukast affects multiple PTOA mechanisms. Because montelukast administration can be safely sustained for long durations and offers a low-cost treatment option, should it be proven effective in the current trial, these results can be immediately incorporated into clinical practice.ClinicalTrials.gov NCT04572256 . Registered on October 1, 2020.
1 citations
TL;DR: Performance of non-arthrographic MRI in diagnosing acetabular chondral delamination showed good results, yet inter-observer reproducibility among different radiologists was only moderate, suggesting that an increased level of awareness, for signs of delamination using MRI, will be helpful for detecting chondrals delamination in patients with a history of FAI.
Abstract: Background Femoroacetabular impingement (FAI) frequently leads to acetabular chondral delamination. Early identification and treatment of these cases is crucial to prevent further damage to the hip. Purpose To evaluate the accuracy of morphological signs of cartilage acetabular delamination in non-arthrographic magnetic resonance imaging (MRI) using intra-articular arthroscopic findings in patients undergoing FAI surgery. Material and Methods All hip MRI scans were assessed individually by three independent radiologists. Images were assessed for signs of delamination including the presence of a linear area of bright signal intensity along the acetabular subchondral bone and an area of darker tissue at the surface of the acetabular cartilage. All FAI patients underwent surgery; arthroscopy served as the standard of reference. Results The mean age of participants was 36.1±10.9 years with 36 (48.6%) women. In the FAI group, arthroscopic surgery showed acetabular chondral delamination in 37 hips. In all hips (including the controls), MRI signs of acetabular cartilage delamination showed an average sensitivity across the three raters of 73.0% with a specificity of 71.0%. In a separate analysis of only the FAI patients, a slightly higher sensitivity (77.7%) but lower specificity (66.7%) was demonstrated. The interrater reliability showed a moderate agreement (average [k]) across the raters (0.450). Conclusion Performance of non-arthrographic MRI in diagnosing acetabular chondral delamination showed good results, yet inter-observer reproducibility among different radiologists was only moderate. Our results suggest that an increased level of awareness, for signs of delamination using MRI, will be helpful for detecting chondral delamination in patients with a history of FAI.
1 citations
TL;DR: Men exhibited accelerated T1ρ increases across the femoral cartilage compared to women, suggesting sex should be considered when evaluating early hip OA, and patterns of short-term relaxometry increases could indicate hip OOA progression.
Abstract: Although T1ρ and T2 have emerged as early indicators for hip osteoarthritis (OA), there is little information regarding longitudinal changes across the cartilage in the early stages of this disease.
TL;DR: The herein presented SOPs are meant to improve understanding of pain mechanisms and facilitate patient phenotyping by codifying MRI-based methods that provide standardized, non-invasive assessments of spinal pathologies.
Abstract: Management of patients suffering from low back pain (LBP) is challenging and requires development of diagnostic techniques to identify specific patient subgroups and phenotypes in order to customize treatment and predict clinical outcome. The Back Pain Consortium (BACPAC) Spine Imaging Working Group has developed standard operating procedures (SOPs) for spinal imaging protocols to be used in all BACPAC studies. These SOPs include procedures to conduct spinal imaging assessments with guidelines for standardizing the collection, reading/grading (using structured reporting with semi-quantitative evaluation using ordinal rating scales), and storage of images. This article presents the approach to image acquisition and evaluation recommended by the BACPAC Spine Imaging Working Group. While the approach is specific to BACPAC studies, it is general enough to be applied at other centers performing MRI acquisitions in patients with LBP. The herein presented SOPs are meant to improve understanding of pain mechanisms and facilitate patient phenotyping by codifying MRI-based methods that provide standardized, non-invasive assessments of spinal pathologies. Finally, these recommended procedures may facilitate the integration of better harmonized MRI data of the lumbar spine across studies and sites within and outside of BACPAC studies.
TL;DR: The study suggests that patella malalignment as a risk factor for worsening cartilage health, informing clinicians with a better rehabilitation program that targets PFJ degeneration.
TL;DR: In this paper , the authors applied deep learning and survival analysis to investigate the association between time to incident radiographic osteoarthritis (OA) and ROAMES structural phenotypes.
TL;DR: In this paper , a deep learning-generated ROAMES phenotyping of osteoarthritis (OA) has been demonstrated to predict incidence of structural and symptomatic OA as well as likelihood of total knee replacement (TKR) within 96 months.
TL;DR: “Harry Genant, San Francisco” are familiar words to many of us who have attended osteoporosis, arthritis, and skeletal imaging conferences for more than four decades, but that introduction and the insightful questions, edifying comments, or genuine compliments that followed it, will be heard no more.
Abstract: “Harry Genant, San Francisco” are familiar words to many of us who have attended osteoporosis, arthritis, and skeletal imaging conferences for more than four decades. Sadly, that introduction and the insightful questions, edifying comments, or genuine compliments that followed it, will be heard no more. Harry K. Genant, MD, Professor Emeritus of Radiology, Medicine, Epidemiology and Orthopaedic Surgery, University of California San Francisco and Senior Consultant to Bioclinica (Synarc), died unexpectedly at age 78 years on January 14, 2021, at his home in Napa, CA. Many readers of the Journal of Bone and Mineral Research (JBMR) will remember Harry for his ubiquitous presence at the ASBMR annual meeting and other conferences in the osteoporosis and arthritis fields. Strategically seated at the front of convention halls, Harry’s quickness to themicrophonewasmatched by the quickness of his intellect to digest the research just presented. His questions struck to the heart of the presentation. His comments brought context and relevance to the findings reported. His suggestions moved the research into new territory. His criticisms were delivered with compassion and genuine interest to advance the presenter’s topic to its full potential, as well as the career of the young investigator.