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OBJECTIVES: To compare diagnostic accuracy of a deep learning artificial intelligence (AI) for cervical spine (C-spine) fracture detection on CT to attending radiologists and assess which undetected fractures were injuries in need of stabilising therapy (IST). METHODS: This single-centre, retrospective diagnostic accuracy study included consecutive patients (age ≥18 years; 2007-2014) screened for C-spine fractures with CT. To validate ground truth, one radiologist and three neurosurgeons independently examined scans positive for fracture. Negative scans were followed up until 2022 through patient files and two radiologists reviewed negative scans that were flagged positive by AI. The neurosurgeons determined which fractures were ISTs. Diagnostic accuracy of AI and attending radiologists (index tests) were compared using McNemar. RESULTS: Of the 2368 scans (median age, 48, interquartile range 30-65; 1441 men) analysed, 221 (9.3%) scans contained C-spine fractures with 133 IST. AI detected 158/221 scans with fractures (sensitivity 71.5%, 95% CI 65.5-77.4%) and 2118/2147 scans without fractures (specificity 98.6%, 95% CI 98.2-99.1). In comparison, attending radiologists detected 195/221 scans with fractures (sensitivity 88.2%, 95% CI 84.0-92.5%, p < 0.001) and 2130/2147 scans without fracture (specificity 99.2%, 95% CI 98.8-99.6, p = 0.07). Of the fractures undetected by AI 30/63 were ISTs versus 4/26 for radiologists. AI detected 22/26 fractures undetected by the radiologists, including 3/4 undetected ISTs. CONCLUSION: Compared to attending radiologists, the artificial intelligence has a lower sensitivity and a higher miss rate of fractures in need of stabilising therapy; however, it detected most fractures undetected by the radiologists, including fractures in need of stabilising therapy. Clinical relevance statement The artificial intelligence algorithm missed more cervical spine fractures on CT than attending radiologists, but detected 84.6% of fractures undetected by radiologists, including fractures in need of stabilising therapy. KEY POINTS: The impact of artificial intelligence for cervical spine fracture detection on CT on fracture management is unknown. The algorithm detected less fractures than attending radiologists, but detected most fractures undetected by the radiologists including almost all in need of stabilising therapy. The artificial intelligence algorithm shows potential as a concurrent reader.
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Algoritmos , Inteligencia Artificial , Vértebras Cervicales , Radiólogos , Sensibilidad y Especificidad , Fracturas de la Columna Vertebral , Tomografía Computarizada por Rayos X , Humanos , Masculino , Femenino , Persona de Mediana Edad , Vértebras Cervicales/lesiones , Vértebras Cervicales/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Fracturas de la Columna Vertebral/diagnóstico por imagen , Adulto , Estudios Retrospectivos , Anciano , Aprendizaje ProfundoRESUMEN
Anterior cruciate ligament (ACL) rupture is a frequently encountered injury among athletes, often requiring surgical intervention to restore knee stability. Magnetic resonance imaging (MRI) after ACL reconstruction is common, especially in the evaluation of clinical complications leading to knee instability, decreased range of motion, or pain. This article provides a detailed overview of normal and abnormal postoperative findings including a practical step-by-step guide for MRI assessment. MRI findings must be correlated with surgical technique, time interval from surgery to imaging, and clinical examination.
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Lesiones del Ligamento Cruzado Anterior , Reconstrucción del Ligamento Cruzado Anterior , Imagen por Resonancia Magnética , Humanos , Reconstrucción del Ligamento Cruzado Anterior/métodos , Imagen por Resonancia Magnética/métodos , Lesiones del Ligamento Cruzado Anterior/cirugía , Lesiones del Ligamento Cruzado Anterior/diagnóstico por imagen , Complicaciones Posoperatorias/diagnóstico por imagenRESUMEN
This case report highlights a case of extranodal NK/T cell lymphoma initially misdiagnosed as myositis, emphasizing the appearance on both MRI and FDG PET images. The patient presented with systemic symptoms and calf muscle swelling, prompting imaging studies that revealed diffuse muscle involvement. Despite negative myositis markers and inconclusive biopsy, post-amputation findings confirmed lymphoma with EBV positivity. The appearance in both MRI and FDG PET complicated the diagnostic process, underscoring the importance of considering lymphoma in cases of muscle-related symptoms to prevent delays in appropriate management. This case contributes to the understanding of the diagnostic challenges associated with extranodal NK/T cell lymphoma and emphasizes the significance of peripheral band-like features in imaging studies.
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OBJECTIVE: This study aimed to quantitatively assess the diagnostic value of bone marrow edema (BME) detection on virtual non-calcium (VNCa) images calculated from dual-energy CT (DECT) in people with diabetes mellitus and suspected Charcot neuro-osteoarthropathy (CN). MATERIALS AND METHODS: People with diabetes mellitus and suspected CN who underwent DECT of the feet (80kVp/Sn150kVp) were included retrospectively. Two blinded observers independently measured CT values on VNCa images using circular regions of interest in five locations in the midfoot (cuneiforms, cuboid and navicular) and the calcaneus of the contralateral or (if one foot was available) the ipsilateral foot. Two clinical groups were formed, one with active CN and one without active CN (no-CN), based on the clinical diagnosis. RESULTS: Thirty-two people with diabetes mellitus and suspected CN were included. Eleven had clinically active CN. The mean CT value in the midfoot was significantly higher in the CN group (-55.6 ± 18.7 HU) compared to the no-CN group (-94.4 ± 23.5 HU; p < 0.001). In the CN group, the difference in CT value between the midfoot and calcaneus was statistically significant (p = 0.003); this was not the case in the no-CN group (p = 0.357). The overall observer agreement was good for the midfoot (ICC = 0.804) and moderate for the calcaneus (ICC = 0.712). Sensitivity was 100.0% and specificity was 71.4% using a cutoff value of -87.6 HU. CONCLUSION: The detection of BME on VNCa images has a potential value in people with diabetes mellitus and suspected active CN.
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BACKGROUND: Weight-bearing CT (WBCT) 3D volumetric measurement has shown promising accuracy for the diagnosis of syndesmotic instability. However, these measurements are rather complex and time-consuming, rendering them a clinically unfavorable option. We hypothesized that automatized measurements would be more accurate and time-efficient than manual ones. METHODS: Thirty cases of intraoperatively confirmed syndesmotic instability along with thirty individuals with no injuries to the ankle joint were recruited as cases and controls, retrospectively. Two observers conducted the manual volumetric measurements two times, at a one-week interval. An automated algorithm for 3D WBCT measurements was developed to conduct the measurements on the axial images. The time spent on each method was recorded. Mann-Whitney U test was used to compare the values between human raters and computers. Inter- and intra-class reliability were calculated. RESULTS: The intra-class correlation coefficient was found to be "excellent" for the automated measurements (0.97) and "good" for the observers (0.75). Similarly, the Cronbach's alpha was shown to be higher for the computer (0.88) than the observers (0.60 and 0.62). The mean time spent on the measurements was different between human raters and the computer-assisted method (p < 0.001). CONCLUSION: Automated volumetric assessment of syndesmosis seems to be a faster and more reliable option than the manual one. We suggest future larger-scale prospective studies conducted under actual clinical circumstances for more definitive conclusions. LEVEL OF EVIDENCE: Retrospective case-control study - Level 3.
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MRI, ultrasound, and conventional radiography each play distinct roles in the evaluation of juvenile idiopathic arthritis (JIA), with MRI being the preferred imaging modality of choice for assessing both inflammatory and destructive changes. These various imaging modalities provide valuable insights into JIA in pediatric patients. However, challenges persist in terms of achieving precision, ensuring validity, and distinguishing between pathologic findings and normal anatomic variations. Establishing normal reference values and implementing scoring systems can aid in the precise evaluation of disease activity and provide information to assist treatment decisions for children with JIA. Ongoing advancements in imaging techniques and standardization initiatives aim to bolster the accuracy of JIA diagnosis and assessment, ultimately leading to enhanced patient care and treatment outcomes.
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Artritis Juvenil , Imagen por Resonancia Magnética , Ultrasonografía , Humanos , Artritis Juvenil/diagnóstico por imagen , Niño , Imagen por Resonancia Magnética/métodos , Ultrasonografía/métodos , Radiografía/métodos , Articulaciones/diagnóstico por imagenRESUMEN
Metal artifacts degrade CT image quality, hampering clinical assessment. Numerous metal artifact reduction methods are available to improve the image quality of CT images with metal implants. In this review, an overview of traditional methods is provided including the modification of acquisition and reconstruction parameters, projection-based metal artifact reduction techniques (MAR), dual energy CT (DECT) and the combination of these techniques. Furthermore, the additional value and challenges of novel metal artifact reduction techniques that have been introduced over the past years are discussed such as photon counting CT (PCCT) and deep learning based metal artifact reduction techniques.
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Artefactos , Tomografía Computarizada por Rayos X , Humanos , Tomografía Computarizada por Rayos X/métodos , Prótesis e Implantes , Metales , AlgoritmosRESUMEN
OBJECTIVE: To systematically review radiomic feature reproducibility and model validation strategies in recent studies dealing with CT and MRI radiomics of bone and soft-tissue sarcomas, thus updating a previous version of this review which included studies published up to 2020. METHODS: A literature search was conducted on EMBASE and PubMed databases for papers published between January 2021 and March 2023. Data regarding radiomic feature reproducibility and model validation strategies were extracted and analyzed. RESULTS: Out of 201 identified papers, 55 were included. They dealt with radiomics of bone (n = 23) or soft-tissue (n = 32) tumors. Thirty-two (out of 54 employing manual or semiautomatic segmentation, 59%) studies included a feature reproducibility analysis. Reproducibility was assessed based on intra/interobserver segmentation variability in 30 (55%) and geometrical transformations of the region of interest in 2 (4%) studies. At least one machine learning validation technique was used for model development in 34 (62%) papers, and K-fold cross-validation was employed most frequently. A clinical validation of the model was reported in 38 (69%) papers. It was performed using a separate dataset from the primary institution (internal test) in 22 (40%), an independent dataset from another institution (external test) in 14 (25%) and both in 2 (4%) studies. CONCLUSIONS: Compared to papers published up to 2020, a clear improvement was noted with almost double publications reporting methodological aspects related to reproducibility and validation. Larger multicenter investigations including external clinical validation and the publication of databases in open-access repositories could further improve methodology and bring radiomics from a research area to the clinical stage. CRITICAL RELEVANCE STATEMENT: An improvement in feature reproducibility and model validation strategies has been shown in this updated systematic review on radiomics of bone and soft-tissue sarcomas, highlighting efforts to enhance methodology and bring radiomics from a research area to the clinical stage. KEY POINTS: ⢠2021-2023 radiomic studies on CT and MRI of musculoskeletal sarcomas were reviewed. ⢠Feature reproducibility was assessed in more than half (59%) of the studies. ⢠Model clinical validation was performed in 69% of the studies. ⢠Internal (44%) and/or external (29%) test datasets were employed for clinical validation.
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INTRODUCTION: Patients with pelvic fragility fractures suffer from high morbidity and mortality rates. Despite the high incidence, there is currently no regional or nationwide treatment protocol which results in a wide variety of clinical practices. Recently, there have been new insights into treatment strategies, such as early diagnosis and minimally invasive operative treatment. The aim of this study is to implement an evidence-based and experience-based treatment clinical pathway to improve outcomes in this fragile patient population. METHODS AND ANALYSIS: This study will be a regional stepped-wedge cluster randomised controlled trial. All older adult patients (≥50 years old) who suffered a pelvic fragility fracture after low-energetic trauma are eligible for inclusion. The pathway aims to optimise the diagnostic process, to guide the decision-making process for further treatment (eg, operative or conservative), to structure the follow-up and to provide guidelines on pain management, weight-bearing and osteoporosis workup. The primary outcome is mobility, measured by the Parker Mobility Score. Secondary outcomes are mobility measured by the Elderly Mobility Scale, functional performance, quality of life, return to home rate, level of pain, type and dosage of analgesic medications, the number of falls after treatment, the number of (fracture-related) complications, 1-year and 2-year mortality. Every 6 weeks, a cluster will switch from current practice to the clinical pathway. The aim is a total of 393 inclusions, which provides an 80% statistical power for an improvement in mobility of 10%, measured by the Parker mobility score. ETHICS AND DISSEMINATION: The Medical Research Ethics Committee of Academic Medical Center has exempted the PELVIC study from the Medical Research Involving Human Subjects Act (WMO). Informed consent will be obtained using the opt-out method and research data will be stored in a database and handled confidentially. The final study report will be shared via publication without restrictions from funding parties and regardless of the outcome. TRIAL REGISTRATION NUMBER: NCT06054165. PROTOCOL VERSION: V.1.0, 19 July 2022.
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Huesos Pélvicos , Humanos , Huesos Pélvicos/lesiones , Anciano , Vías Clínicas , Persona de Mediana Edad , Ensayos Clínicos Controlados Aleatorios como Asunto , Femenino , Masculino , Calidad de Vida , Fracturas Osteoporóticas/terapia , Estudios Multicéntricos como Asunto , Manejo del Dolor/métodosRESUMEN
BACKGROUND: To compare image quality, metal artifacts, and diagnostic confidence of conventional computed tomography (CT) images of unilateral total hip arthroplasty patients (THA) with deep learning-based metal artifact reduction (DL-MAR) to conventional CT and 130-keV monoenergetic images with and without orthopedic metal artifact reduction (O-MAR). METHODS: Conventional CT and 130-keV monoenergetic images with and without O-MAR and DL-MAR images of 28 unilateral THA patients were reconstructed. Image quality, metal artifacts, and diagnostic confidence in bone, pelvic organs, and soft tissue adjacent to the prosthesis were jointly scored by two experienced musculoskeletal radiologists. Contrast-to-noise ratios (CNR) between bladder and fat and muscle and fat were measured. Wilcoxon signed-rank tests with Holm-Bonferroni correction were used. RESULTS: Significantly higher image quality, higher diagnostic confidence, and less severe metal artifacts were observed on DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001 for all comparisons). Higher image quality, higher diagnostic confidence for bone and soft tissue adjacent to the prosthesis, and less severe metal artifacts were observed on DL-MAR when compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.014). CNRs were higher for DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001). Higher CNRs were observed on DL-MAR images compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.010). CONCLUSIONS: DL-MAR showed higher image quality, diagnostic confidence, and superior metal artifact reduction compared to conventional CT images and 130-keV monoenergetic images with and without O-MAR in unilateral THA patients. RELEVANCE STATEMENT: DL-MAR resulted into improved image quality, stronger reduction of metal artifacts, and improved diagnostic confidence compared to conventional and virtual monoenergetic images with and without metal artifact reduction, bringing DL-based metal artifact reduction closer to clinical application. KEY POINTS: ⢠Metal artifacts introduced by total hip arthroplasty hamper radiologic assessment on CT. ⢠A deep-learning algorithm (DL-MAR) was compared to dual-layer CT images with O-MAR. ⢠DL-MAR showed best image quality and diagnostic confidence. ⢠Highest contrast-to-noise ratios were observed on the DL-MAR images.
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Artroplastia de Reemplazo de Cadera , Aprendizaje Profundo , Humanos , Tomografía Computarizada por Rayos X/métodos , Artefactos , AlgoritmosRESUMEN
BACKGROUND: Intravoxel incoherent motion (IVIM)-corrected diffusion tensor imaging (DTI) potentially enhances return-to-play (RTP) prediction after hamstring injuries. However, the long scan times hamper clinical implementation. We assessed accelerated IVIM-corrected DTI approaches in acute hamstring injuries and explore the sensitivity of the perfusion fraction (f) to acute muscle damage. METHODS: Athletes with acute hamstring injury received DTI scans of both thighs < 7 days after injury and at RTP. For a subset, DTI scans were repeated with multiband (MB) acceleration. Data from standard and MB-accelerated scans were fitted with standard and accelerated IVIM-corrected DTI approach using high b-values only. Segmentations of the injury and contralateral healthy muscles were contoured. The fitting methods as well as the standard and MB-accelerated scan were compared using linear regression analysis. For sensitivity to injury, Δ(injured minus healthy) DTI parameters between the methods and the differences between injured and healthy muscles were compared (Wilcoxon signed-rank test). RESULTS: The baseline dataset consisted of 109 athletes (16 with MB acceleration); 64 of them received an RTP scan (8 with MB acceleration). Linear regression of the standard and high-b DTI fitting showed excellent agreement. With both fitting methods, standard and MB-accelerated scans were comparable. Δ(injured minus healthy) was similar between standard and accelerated methods. For all methods, all IVIM-DTI parameters except f were significantly different between injured and healthy muscles. CONCLUSIONS: High-b DTI fitting with MB acceleration reduced the scan time from 11:08 to 3:40 min:s while maintaining sensitivity to hamstring injuries; f was not different between healthy and injured muscles. RELEVANCE STATEMENT: The accelerated IVIM-corrected DTI protocol, using fewer b-values and MB acceleration, reduced the scan time to under 4 min without affecting the sensitivity of the quantitative outcome parameters to hamstring injuries. This allows for routine clinical monitoring of hamstring injuries, which could directly benefit injury treatment and monitoring. KEY POINTS: ⢠Combining high-b DTI-fitting and multiband-acceleration dramatically reduced by two thirds the scan time. ⢠The accelerated IVIM-corrected DTI approaches maintained the sensitivity to hamstring injuries. ⢠The IVIM-derived perfusion fraction was not sensitive to hamstring injuries.
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Imagen de Difusión por Resonancia Magnética , Imagen de Difusión Tensora , Humanos , Imagen de Difusión por Resonancia Magnética/métodos , Movimiento (Física)RESUMEN
Segment coordinate systems (CSs) of marker-based multi-segment foot models are used to measure foot kinematics, however their relationship to the underlying bony anatomy is barely studied. The aim of this study was to compare marker-based CSs (MCSs) with bone morphology-based CSs (BCSs) for the hindfoot and forefoot. Markers were placed on the right foot of fifteen healthy adults according to the Oxford, Rizzoli and Amsterdam Foot Model (OFM, RFM and AFM, respectively). A CT scan was made while the foot was loaded in a simulated weight-bearing device. BCSs were based on axes of inertia. The orientation difference between BCSs and MCSs was quantified in helical and 3D Euler angles. To determine whether the marker models were able to capture inter-subject variability in bone poses, linear regressions were performed. Compared to the hindfoot BCS, all MCSs were more toward plantar flexion and internal rotation, and RFM was also oriented toward more inversion. Compared to the forefoot BCS, OFM and RFM were oriented more toward dorsal and plantar flexion, respectively, and internal rotation, while AFM was not statistically different in the sagittal and transverse plane. In the frontal plane, OFM was more toward eversion and RFM and AFM more toward inversion compared to BCS. Inter-subject bone pose variability was captured with RFM and AFM in most planes of the hindfoot and forefoot, while this variability was not captured by OFM. When interpreting multi-segment foot model data it is important to realize that MCSs and BCSs do not always align.
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Pie , Marcha , Adulto , Humanos , Pie/diagnóstico por imagen , Caminata , Mano , Extremidad Inferior , Fenómenos BiomecánicosRESUMEN
PURPOSE: To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies. METHODS: We conducted an online modified Delphi study with a group of international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members to identify the items to be voted; and Stage#3, four rounds of the modified Delphi exercise by panelists to determine the items eligible for the METRICS and their weights. The consensus threshold was 75%. Based on the median ranks derived from expert panel opinion and their rank-sum based conversion to importance scores, the category and item weights were calculated. RESULT: In total, 59 panelists from 19 countries participated in selection and ranking of the items and categories. Final METRICS tool included 30 items within 9 categories. According to their weights, the categories were in descending order of importance: study design, imaging data, image processing and feature extraction, metrics and comparison, testing, feature processing, preparation for modeling, segmentation, and open science. A web application and a repository were developed to streamline the calculation of the METRICS score and to collect feedback from the radiomics community. CONCLUSION: In this work, we developed a scoring tool for assessing the methodological quality of the radiomics research, with a large international panel and a modified Delphi protocol. With its conditional format to cover methodological variations, it provides a well-constructed framework for the key methodological concepts to assess the quality of radiomic research papers. CRITICAL RELEVANCE STATEMENT: A quality assessment tool, METhodological RadiomICs Score (METRICS), is made available by a large group of international domain experts, with transparent methodology, aiming at evaluating and improving research quality in radiomics and machine learning. KEY POINTS: ⢠A methodological scoring tool, METRICS, was developed for assessing the quality of radiomics research, with a large international expert panel and a modified Delphi protocol. ⢠The proposed scoring tool presents expert opinion-based importance weights of categories and items with a transparent methodology for the first time. ⢠METRICS accounts for varying use cases, from handcrafted radiomics to entirely deep learning-based pipelines. ⢠A web application has been developed to help with the calculation of the METRICS score ( https://metricsscore.github.io/metrics/METRICS.html ) and a repository created to collect feedback from the radiomics community ( https://github.com/metricsscore/metrics ).
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We describe an elite youth football player who developed lateral foot pain of previously unknown origin. A thorough patient history and physical examination as well as an in-depth presentation of radiographic findings on Computed tomography (CT) and Magnetic Resonance Imaging (MRI) scan were described. Through this combination, the puzzle was resolved and a rare peroneus longus tendinopathy due to bony spurs in the cuboid groove was diagnosed. A peroneus longus exploration, release and reduction of the cuboidal bone spurs was performed and intensive rehabilitation phase followed. The patient successfully returned to performance and set a career in professional football.
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This study was undertaken to analyze the magnetic resonance imaging (MRI) findings in the clinically asymptomatic neuropathic feet of leprosy patients. Since in the literature no MRI data are available concerning the asymptomatic neuropathic foot in leprosy, the interpretation of MRI examinations in clinically suspected neuropathic feet in leprosy is difficult. We examined 10 adult leprosy patients with clinically asymptomatic neuropathic feet. Inclusion criteria were a normal or near normal neuropathic foot, without signs of inflammation. All patients underwent an MRI protocol with the inclusion of two-point Dixon chemical shift imaging as fat suppression sequence. We found MRI changes in almost all patients. The most striking were the changes located in the region of the first metacarpophalangeal (MTP) joint. These changes ranged from degradation and interruption of the subcutaneous fat to effusion/synovitis in the first MTP joint. This study reveals significant MRI changes in clinically asymptomatic neuropathic feet in patients with leprosy. These changes may relate to the development of ulcerations. MRI may play an important role in detecting feet at risk and may influence clinical decision making.
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Humanos , Espectroscopía de Resonancia Magnética , Espectroscopía de Resonancia Magnética/instrumentación , Lepra/fisiopatologíaRESUMEN
This study was undertaken to analyze MRI findings in leprosy patients with neuropathic feet, which are suspected of having osteomyelitis. As far as we know, there is no literature concerning osteomyelitis and MRI in neuropathic leprosy feet at present. Therefore, we have included MRI examination of 18 events of suspected osteomyelitis in 12 leprosy patients. All patients with long-standing neuropathic foot problems were clinically suspected of having osteomyelitis. All patients underwent the MRI protocol with the inclusion of Two Point Dixon Chemical Shift Imaging as a fat-suppression sequence. For the MRI evaluation, we used signs that are described in literature for detecting osteomyelitis in diabetic feet. The primary MRI signs were positive in 17 of 18 patients. The secondary MRI signs were positive in 100% of the patients. Our results show that MRI with the use of Two Point Dixon Chemical Shift Imaging is a promising diagnostic modality to detect osteomyelitis in the presence of neurosteoarthropathic changes in patients with leprosy. Whenever available, MRI could play an important role in detecting osteomyelitis in leprosy patients with long-standing neuropathic feet.