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PURPOSE: To systematically review the use of artificial intelligence (AI) in musculoskeletal (MSK) ultrasound (US) with an emphasis on AI algorithm categories and validation strategies. MATERIAL AND METHODS: An electronic literature search was conducted for articles published up to January 2024. Inclusion criteria were the use of AI in MSK US, involvement of humans, English language, and ethics committee approval. RESULTS: Out of 269 identified papers, 16 studies published between 2020 and 2023 were included. The research was aimed at predicting diagnosis and/or segmentation in a total of 11 (69%) out of 16 studies. A total of 11 (69%) studies used deep learning (DL)-based algorithms, three (19%) studies employed conventional machine learning (ML)-based algorithms, and two (12%) studies employed both conventional ML- and DL-based algorithms. Six (38%) studies used cross-validation techniques with K-fold cross-validation being the most frequently employed (n = 4, 25%). Clinical validation with separate internal test datasets was reported in nine (56%) papers. No external clinical validation was reported. CONCLUSION: AI is a topic of increasing interest in MSK US research. In future studies, attention should be paid to the use of validation strategies, particularly regarding independent clinical validation performed on external datasets.
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This review examines the latest advancements in compositional and quantitative cartilage MRI techniques, addressing both their potential and challenges. The integration of these advancements promises to improve disease detection, treatment monitoring, and overall patient care. We want to highlight the pivotal task of translating these techniques into widespread clinical use, the transition of cartilage MRI from technical validation to clinical application, emphasizing its critical role in identifying early signs of degenerative and inflammatory joint diseases. Recognizing these changes early may enable informed treatment decisions, thereby facilitating personalized medicine approaches. The evolving landscape of cartilage MRI underscores its increasing importance in clinical practice, offering valuable insights for patient management and therapeutic interventions. This review aims to discuss the old evidence and new insights about the evaluation of articular cartilage through MRI, with an update on the most recent literature published on novel quantitative sequences.
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Cartílago Articular , Imagen por Resonancia Magnética , Humanos , Cartílago Articular/diagnóstico por imagen , Cartílago Articular/patología , Imagen por Resonancia Magnética/métodosRESUMEN
BACKGROUND: The purpose of the authors' narrative review was to outline the current literature regarding the use of ultrasound in main rheumatic disorders and summarize the updates, specifically about rheumatoid arthritis, psoriatic arthritis, and crystal-induced arthropathies. METHODS: The authors searched on PubMed for articles discussing the major updates regarding the role of ultrasound in the previously mentioned rheumatic conditions. RESULTS: The authors have provided the updated definitions, new criteria, and diagnostic scores. CONCLUSIONS: In rheumatology's dynamic landscape, this review provides valuable insights for researchers and clinicians on ultrasound's role in improving patient care and outcomes in rheumatic diseases.
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Enfermedades Reumáticas , Reumatología , Ultrasonografía , Humanos , Ultrasonografía/métodos , Enfermedades Reumáticas/diagnóstico por imagen , Reumatología/métodos , Artritis Psoriásica/diagnóstico por imagenRESUMEN
In patients with total hip arthroplasty (THA) with recurrent pain, symptoms may be caused by several conditions involving not just the joint, but also the surrounding soft tissues including tendons, muscles, bursae, and peripheral nerves. US and US-guided interventional procedures are important tools in the diagnostic work-up of patients with painful THA given that it is possible to reach a prompt diagnosis both directly identifying the pathological changes of periprosthetic structures and indirectly evaluating the response and pain relief to local injection of anesthetics under US monitoring. Then, US guidance can be used for the aspiration of fluid from the joint or periarticular collections, or alternatively to follow the biopsy needle to collect samples for culture analysis in the suspicion of prosthetic joint infection. Furthermore, US-guided percutaneous interventions may be used to treat several conditions with well-established minimally invasive procedures that involve injections of corticosteroid, local anesthetics, and platelet-rich plasma or other autologous products. In this review, we will discuss the clinical and technical applications of US-guided percutaneous interventional procedures in painful THA that can be used in routine daily practice for diagnostic and therapeutic purposes.
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Total hip arthroplasty (THA) is the best surgical approach for treating advanced hip degeneration, providing pain relief, and improved function in most cases. In the past, MR imaging quality has been highly compromised by in-plane distortions, inadequate fat saturation, and other artifacts due to metal components of THA. Technological advancements have made pathologic conditions, which were previously hidden by periprosthetic artifacts, outstanding features due to the optimization of several sequences. To date, several short and long-term complications involving bony and soft-tissue structures may be detected through magnetic resonance imaging (MRI). The use of MRI with adapted sequences and protocols may drastically reduce artifacts thereby providing essential pre-operative elements for planning revision surgery of failed THA. This review has the purpose of conveying new insights to musculoskeletal radiologists about the techniques to suppress metal-related artifacts and the hallmark MRI findings of painful THA. CRITICAL RELEVANCE STATEMENT: Advancements in metal-suppression have given radiologists the opportunity to play an emerging role in THA management. This article provides technical and imaging insights into challenges that can be encountered in cases of THA, which may present complications and characteristic imaging findings. KEY POINTS: Imaging total hip arthroplasty requires adapted MRI protocol and awareness of the common complications. We have reported the available metal-suppression sequences for evaluating total hip arthroplasty. Many structures and conditions should be considered when dealing with painful aseptic or septic arthroplasty.
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OBJECTIVES: Health technology assessment (HTA) is a systematic process used to evaluate the properties and effects of healthcare technologies within their intended use context. This paper describes the adoption of HTA process to assess the adoption of the EOSedge™ system in clinical practice. METHODS: The EOSedge™ system is a digital radiography system that delivers whole-body, high-quality 2D/3D biplanar images covering the complete set of musculoskeletal and orthopedic exams. Full HTA model was chosen using the EUnetHTA Core Model® version 3.0. The HTA Core Model organizes the information into nine domains. Information was researched and obtained by consulting the manufacturers' user manuals, scientific literature, and institutional sites for regulatory aspects. RESULTS: All nine domains of the EUnetHTA Core Model® helped conduct the HTA of the EOSedge, including (1) description and technical characteristics of the technology; (2) health problem and current clinical practice; (3) safety; (4) clinical effectiveness; (5) organizational aspects; (6) economic evaluation; (7) impact on the patient; (8) ethical aspects; and (9) legal aspects. CONCLUSIONS: EOS technologies may be a viable alternative to conventional radiographs. EOSedge has the same intended use and similar indications for use, technological characteristics, and operation principles as the EOS System and provides significant dose reduction factors for whole spine imaging compared to the EOS System without compromising image quality. Regarding the impact of EOS imaging on patient outcomes, most studies aim to establish technical ability without evaluating their ability to improve patient outcomes; thus, more studies on this aspect are warranted.
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Enfermedades Musculoesqueléticas , Evaluación de la Tecnología Biomédica , Humanos , Enfermedades Musculoesqueléticas/diagnóstico por imagen , Intensificación de Imagen Radiográfica/métodosRESUMEN
Dual-energy CT stands out as a robust and innovative imaging modality, which has shown impressive advancements and increasing applications in musculoskeletal imaging. It allows to obtain detailed images with novel insights that were once the exclusive prerogative of magnetic resonance imaging. Attenuation data obtained by using different energy spectra enable to provide unique information about tissue characterization in addition to the well-established strengths of CT in the evaluation of bony structures. To understand clearly the potential of this imaging modality, radiologists must be aware of the technical complexity of this imaging tool, the different ways to acquire images and the several algorithms that can be applied in daily clinical practice and for research. Concerning musculoskeletal imaging, dual-energy CT has gained more and more space for evaluating crystal arthropathy, bone marrow edema, and soft tissue structures, including tendons and ligaments. This article aims to analyze and discuss the role of dual-energy CT in musculoskeletal imaging, exploring technical aspects, applications and clinical implications and possible perspectives of this technique.
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Enfermedades Musculoesqueléticas , Imagen Radiográfica por Emisión de Doble Fotón , Tomografía Computarizada por Rayos X , Humanos , Tomografía Computarizada por Rayos X/métodos , Enfermedades Musculoesqueléticas/diagnóstico por imagen , Imagen Radiográfica por Emisión de Doble Fotón/métodos , Sistema Musculoesquelético/diagnóstico por imagen , AlgoritmosRESUMEN
Artificial intelligence (AI) has demonstrated great potential in a wide variety of applications in interventional radiology (IR). Support for decision-making and outcome prediction, new functions and improvements in fluoroscopy, ultrasound, computed tomography, and magnetic resonance imaging, specifically in the field of IR, have all been investigated. Furthermore, AI represents a significant boost for fusion imaging and simulated reality, robotics, touchless software interactions, and virtual biopsy. The procedural nature, heterogeneity, and lack of standardisation slow down the process of adoption of AI in IR. Research in AI is in its early stages as current literature is based on pilot or proof of concept studies. The full range of possibilities is yet to be explored.Relevance statement Exploring AI's transformative potential, this article assesses its current applications and challenges in IR, offering insights into decision support and outcome prediction, imaging enhancements, robotics, and touchless interactions, shaping the future of patient care.Key points⢠AI adoption in IR is more complex compared to diagnostic radiology.⢠Current literature about AI in IR is in its early stages.⢠AI has the potential to revolutionise every aspect of IR.
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Inteligencia Artificial , Radiología Intervencionista , Humanos , Radiología Intervencionista/métodosRESUMEN
The posteromedial corner (PMC) of the knee is an anatomical region formed by ligamentous structures (medial collateral ligament, posterior oblique ligament, oblique popliteal ligament), the semimembranosus tendon and its expansions, the posteromedial joint capsule, and the posterior horn of the medial meniscus. Injuries to the structures of the PMC frequently occur in acute knee trauma in association with other ligamentous or meniscal tears. The correct assessment of PMC injuries is crucial because the deficiency of these supporting structures can lead to anteromedial rotation instability or the failure of cruciate ligaments grafts. This article reviews the anatomy and biomechanics of the PMC to aid radiologists in identifying injuries potentially involving PMC components.
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Traumatismos de la Rodilla , Ligamentos Articulares , Humanos , Traumatismos de la Rodilla/diagnóstico por imagen , Ligamentos Articulares/diagnóstico por imagen , Ligamentos Articulares/lesiones , Imagen por Resonancia Magnética/métodos , Articulación de la Rodilla/diagnóstico por imagen , Fenómenos BiomecánicosRESUMEN
OBJECTIVES: To collect real-world data about the knowledge and self-perception of young radiologists concerning the use of contrast media (CM) and the management of adverse drug reactions (ADR). METHODS: A survey (29 questions) was distributed to residents and board-certified radiologists younger than 40 years to investigate the current international situation in young radiology community regarding CM and ADRs. Descriptive statistics analysis was performed. RESULTS: Out of 454 respondents from 48 countries (mean age: 31.7 ± 4 years, range 25-39), 271 (59.7%) were radiology residents and 183 (40.3%) were board-certified radiologists. The majority (349, 76.5%) felt they were adequately informed regarding the use of CM. However, only 141 (31.1%) received specific training on the use of CM and 82 (18.1%) about management ADR during their residency. Although 266 (58.6%) knew safety protocols for handling ADR, 69.6% (316) lacked confidence in their ability to manage CM-induced ADRs and 95.8% (435) expressed a desire to enhance their understanding of CM use and handling of CM-induced ADRs. Nearly 300 respondents (297; 65.4%) were aware of the benefits of contrast-enhanced ultrasound, but 249 (54.8%) of participants did not perform it. The preferred CM injection strategy in CT parenchymal examination and CT angiography examination was based on patient's lean body weight in 318 (70.0%) and 160 (35.2%), a predeterminate fixed amount in 79 (17.4%) and 116 (25.6%), iodine delivery rate in 26 (5.7%) and 122 (26.9%), and scan time in 31 (6.8%) and 56 (12.3%), respectively. CONCLUSION: Training in CM use and management ADR should be implemented in the training of radiology residents. CRITICAL RELEVANCE STATEMENT: We highlight the need for improvement in the education of young radiologists regarding contrast media; more attention from residency programs and scientific societies should be focused on training about contrast media use and the management of adverse drug reactions. KEY POINTS: ⢠This survey investigated training of young radiologists about use of contrast media and management adverse reactions. ⢠Most young radiologists claimed they did not receive dedicated training. ⢠An extreme heterogeneity of responses was observed about contrast media indications/contraindications and injection strategy.
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Computed tomography (CT) arthrography is a quickly available imaging modality to investigate elbow disorders. Its excellent spatial resolution enables the detection of subtle pathologic changes of intra-articular structures, which makes this technique extremely valuable in a joint with very tiny chondral layers and complex anatomy of articular capsule and ligaments. Radiation exposure has been widely decreased with the novel CT scanners, thereby increasing the indications of this examination. The main applications of CT arthrography of the elbow are the evaluation of capsule, ligaments, and osteochondral lesions in both the settings of acute trauma, degenerative changes, and chronic injury due to repeated microtrauma and overuse. In this review, we discuss the normal anatomic findings, technical tips for injection and image acquisition, and pathologic findings that can be encountered in CT arthrography of the elbow, shedding light on its role in the diagnosis and management of different orthopedic conditions. We aspire to offer a roadmap for the integration of elbow CT arthrography into routine clinical practice, fostering improved patient outcomes and a deeper understanding of elbow pathologies.
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Artrografía , Codo , Humanos , Tomografía Computarizada por Rayos X , Tomógrafos Computarizados por Rayos X , RadiólogosRESUMEN
Segmentation and image intensity discretization impact on radiomics workflow. The aim of this study is to investigate the influence of interobserver segmentation variability and intensity discretization methods on the reproducibility of MRI-based radiomic features in lipoma and atypical lipomatous tumor (ALT). Thirty patients with lipoma or ALT were retrospectively included. Three readers independently performed manual contour-focused segmentation on T1-weighted and T2-weighted sequences, including the whole tumor volume. Additionally, a marginal erosion was applied to segmentations to evaluate its influence on feature reproducibility. After image pre-processing, with included intensity discretization employing both fixed bin number and width approaches, 1106 radiomic features were extracted from each sequence. Intraclass correlation coefficient (ICC) 95% confidence interval lower bound ≥ 0.75 defined feature stability. In contour-focused vs. margin shrinkage segmentation, the rates of stable features extracted from T1-weighted and T2-weighted images ranged from 92.68 to 95.21% vs. 90.69 to 95.66% after fixed bin number discretization and from 95.75 to 97.65% vs. 95.39 to 96.47% after fixed bin width discretization, respectively, with no difference between the two segmentation approaches (p ≥ 0.175). Higher stable feature rates and higher feature ICC values were found when implementing discretization with fixed bin width compared to fixed bin number, regardless of the segmentation approach (p < 0.001). In conclusion, MRI radiomic features of lipoma and ALT are reproducible regardless of the segmentation approach and intensity discretization method, although a certain degree of interobserver variability highlights the need for a preliminary reliability analysis in future studies.
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Lipoma , Imagen por Resonancia Magnética , Variaciones Dependientes del Observador , Humanos , Lipoma/diagnóstico por imagen , Lipoma/patología , Imagen por Resonancia Magnética/métodos , Femenino , Masculino , Reproducibilidad de los Resultados , Persona de Mediana Edad , Estudios Retrospectivos , Anciano , Adulto , Procesamiento de Imagen Asistido por Computador/métodos , RadiómicaRESUMEN
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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BACKGROUND: The aim of this systematic review is to evaluate the diagnostic performance of Artificial Intelligence (AI) models designed for the detection of caries lesion (CL). MATERIALS AND METHODS: An electronic literature search was conducted on PubMed, Web of Science, SCOPUS, LILACS and Embase databases for retrospective, prospective and cross-sectional studies published until January 2023, using the following keywords: artificial intelligence (AI), machine learning (ML), deep learning (DL), artificial neural networks (ANN), convolutional neural networks (CNN), deep convolutional neural networks (DCNN), radiology, detection, diagnosis and dental caries (DC). The quality assessment was performed using the guidelines of QUADAS-2. RESULTS: Twenty articles that met the selection criteria were evaluated. Five studies were performed on periapical radiographs, nine on bitewings, and six on orthopantomography. The number of imaging examinations included ranged from 15 to 2900. Four studies investigated ANN models, fifteen CNN models, and two DCNN models. Twelve were retrospective studies, six cross-sectional and two prospective. The following diagnostic performance was achieved in detecting CL: sensitivity from 0.44 to 0.86, specificity from 0.85 to 0.98, precision from 0.50 to 0.94, PPV (Positive Predictive Value) 0.86, NPV (Negative Predictive Value) 0.95, accuracy from 0.73 to 0.98, area under the curve (AUC) from 0.84 to 0.98, intersection over union of 0.3-0.4 and 0.78, Dice coefficient 0.66 and 0.88, F1-score from 0.64 to 0.92. According to the QUADAS-2 evaluation, most studies exhibited a low risk of bias. CONCLUSION: AI-based models have demonstrated good diagnostic performance, potentially being an important aid in CL detection. Some limitations of these studies are related to the size and heterogeneity of the datasets. Future studies need to rely on comparable, large, and clinically meaningful datasets. PROTOCOL: PROSPERO identifier: CRD42023470708.
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Inteligencia Artificial , Caries Dental , Humanos , Caries Dental/diagnóstico por imagen , Redes Neurales de la Computación , Radiografía Dental/métodos , Aprendizaje Profundo , Sensibilidad y EspecificidadRESUMEN
BACKGROUND: Atypical cartilaginous tumour (ACT) and high-grade chondrosarcoma (CS) of long bones are respectively managed with active surveillance or curettage and wide resection. Our aim was to determine diagnostic performance of X-rays radiomics-based machine learning for classification of ACT and high-grade CS of long bones. METHODS: This retrospective, IRB-approved study included 150 patients with surgically treated and histology-proven lesions at two tertiary bone sarcoma centres. At centre 1, the dataset was split into training (n = 71 ACT, n = 24 high-grade CS) and internal test (n = 19 ACT, n = 6 high-grade CS) cohorts, respectively, based on the date of surgery. At centre 2, the dataset constituted the external test cohort (n = 12 ACT, n = 18 high-grade CS). Manual segmentation was performed on frontal view X-rays, using MRI or CT for preliminary identification of lesion margins. After image pre-processing, radiomic features were extracted. Dimensionality reduction included stability, coefficient of variation, and mutual information analyses. In the training cohort, after class balancing, a machine learning classifier (Support Vector Machine) was automatically tuned using nested 10-fold cross-validation. Then, it was tested on both the test cohorts and compared to two musculoskeletal radiologists' performance using McNemar's test. FINDINGS: Five radiomic features (3 morphology, 2 texture) passed dimensionality reduction. After tuning on the training cohort (AUC = 0.75), the classifier had 80%, 83%, 79% and 80%, 89%, 67% accuracy, sensitivity, and specificity in the internal (temporally independent) and external (geographically independent) test cohorts, respectively, with no difference compared to the radiologists (p ≥ 0.617). INTERPRETATION: X-rays radiomics-based machine learning accurately differentiates between ACT and high-grade CS of long bones. FUNDING: AIRC Investigator Grant.
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Neoplasias Óseas , Condrosarcoma , Humanos , Estudios Retrospectivos , Rayos X , Radiómica , Neoplasias Óseas/diagnóstico por imagen , Neoplasias Óseas/patología , Condrosarcoma/diagnóstico por imagen , Condrosarcoma/patología , Imagen por Resonancia Magnética/métodos , Aprendizaje AutomáticoRESUMEN
This narrative review focuses on clinical applications of artificial intelligence (AI) in musculoskeletal imaging. A range of musculoskeletal disorders are discussed using a clinical-based approach, including trauma, bone age estimation, osteoarthritis, bone and soft-tissue tumors, and orthopedic implant-related pathology. Several AI algorithms have been applied to fracture detection and classification, which are potentially helpful tools for radiologists and clinicians. In bone age assessment, AI methods have been applied to assist radiologists by automatizing workflow, thus reducing workload and inter-observer variability. AI may potentially aid radiologists in identifying and grading abnormal findings of osteoarthritis as well as predicting the onset or progression of this disease. Either alone or combined with radiomics, AI algorithms may potentially improve diagnosis and outcome prediction of bone and soft-tissue tumors. Finally, information regarding appropriate positioning of orthopedic implants and related complications may be obtained using AI algorithms. In conclusion, rather than replacing radiologists, the use of AI should instead help them to optimize workflow, augment diagnostic performance, and keep up with ever-increasing workload.Relevance statement This narrative review provides an overview of AI applications in musculoskeletal imaging. As the number of AI technologies continues to increase, it will be crucial for radiologists to play a role in their selection and application as well as to fully understand their potential value in clinical practice. Key points ⢠AI may potentially assist musculoskeletal radiologists in several interpretative tasks.⢠AI applications to trauma, age estimation, osteoarthritis, tumors, and orthopedic implants are discussed.⢠AI should help radiologists to optimize workflow and augment diagnostic performance.
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Neoplasias , Osteoartritis , Humanos , Inteligencia Artificial , Algoritmos , PronósticoRESUMEN
OBJECTIVES: To investigate the efficacy and safety of ultrasound-guided percutaneous irrigation of calcific tendinopathy (US-PICT) applied out of the shoulder, comparing its effectiveness to US-PICT of the rotator cuff. METHODS: Patients subjected to US-PICT for extra-shoulder calcific tendinitis (Case Group) were compared to those subjected to US-PICT of the rotator cuff (Control Group). We had pre-procedure Visual Analogue Scale (VAS) pain score, 1- and 3-month VAS of patients of the Case Group, pre-procedure and 3-month VAS of patients of the Control Group. RESULTS: The Case Group consisted of 41 patients (27 women; mean age: 45 ± 9years): 26 gluteus medius, 5 patellar tendon, 3 rectus femoris, 2 gluteus maximus, 2 common extensor tendon, 1 extensor carpi radialis longus, 1 pes anserinus, and 1 peroneus longus. The Control Group included 41 patients (27 women; mean age: 47 ± 11 years). The mean pre-procedure VAS of the Case Group was 8.8 ± 0.7 with a significant (P < .001) drop at 1 month (4.5 ± 0.6) and 3 months (3.6 ± 0.6). The mean pre-procedure VAS of the Control Group was 8 ± 1.4 and dropped to 3.1 ± 1.6 after 3 months (P < .001). Post-treatment VAS at 3 months was not significantly different between two Groups (P = 0.134). Similarly, the decrease of VAS from baseline to 3 months was not significantly different between the two Groups (P = 0.264). CONCLUSIONS: US-PICT is a safe and effective procedure that can be used out of the shoulder. ADVANCES IN KNOWLEDGE: This study demonstrated the safety and effectiveness of US-PICT as a valuable therapeutic option for extra-shoulder calcific tendinitis, with similar clinical outcome to the same procedure performed in the rotator cuff. The technique must be adapted in some deeply located calcifications by means of the use of different needles and by thoroughly planning the access point for the procedure.
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Enfermedades Musculoesqueléticas , Hombro , Humanos , Femenino , Adulto , Persona de Mediana Edad , Manguito de los Rotadores , Agujas , Antebrazo , PiernaRESUMEN
PURPOSE: To compare pathologic and healthy tendons using shear-wave elastography (SWE). METHODS: A systematic review with meta-analysis was done searching Pubmed and EMBASE up to September 2022. Prospective, retrospective and cross-sectional studies that used SWE in the assessment of pathologic tendons versus control were included. Our primary outcome were SWE velocity (m/s) and stiffness (kPa). Methodological quality was assessed by the methodological index for non-randomized studies (MINORS). We used the mean difference (MD) with corresponding 95% confidence intervals (CIs) to quantify effects between groups. We performed sensitivity analysis in case of high heterogeneity, after excluding poor quality studies according to MINORS assessment. We used Grades of Recommendation, Assessment, Development and Evaluation to evaluate the certainty of evidence (CoE). RESULTS: Overall, 16 studies with 676 pathologic tendons (188 Achilles, 142 patellar, 96 supraspinatus, 250 mixed) and 723 control tendons (484 healthy; 239 contralateral tendon) were included. Five studies (31.3%) were judged as poor methodological quality. Shear-wave velocity and stiffness meta-analyses showed high heterogeneity. According to a sensitivity analysis, pathologic tendons had a lower shear wave velocity (MD of - 1.69 m/s; 95% CI 1.85; - 1.52; n = 274; I2 50%) compared to healthy tendons with very low CoE. Sensitivity analysis on stiffness still showed high heterogeneity. CONCLUSION: Pathological tendons may have reduced SWE velocity compared to controls, but the evidence is very uncertain. Future robust high-quality longitudinal studies and clear technical indications on the use of this tool are needed. PROTOCOL: PROSPERO identifier: CRD42023405410 CLINICAL RELEVANCE STATEMENT: SWE is a relatively recent modality that may increase sensitivity and diagnostic accuracy of conventional ultrasound imaging promoting early detection of tendinopathy. Non-negligible heterogeneity has been observed in included studies, so our findings may encourage the conduct of future high-quality longitudinal studies which can provide clear technical indications on the use of this promising tool in tendon imaging.
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Diagnóstico por Imagen de Elasticidad , Tendinopatía , Humanos , Diagnóstico por Imagen de Elasticidad/métodos , Estudios Prospectivos , Estudios Retrospectivos , Estudios TransversalesRESUMEN
PURPOSE: Scoliosis is a cause of loading imbalance between the lower limbs, which can result in BMD differences between the two femurs. We investigated the discrepancy in BMD values assessed by quantitative computed tomography (QCT) between femurs in patients with and without scoliosis, also assessing if this difference can be related to spine convexity. METHODS: Abdominal CT examinations were retrospectively reviewed. An ''asynchronous'' calibration of CT images was performed to obtain BMD values from QCT. Scoliosis was evaluated on the antero-posterior CT localizer to calculate the Cobb angle. Differences between aBMD and vBMD of femurs were assessed in both scoliotic and non-scoliotic subjects. RESULTS: Final study cohort consisted of 263 subjects, 225 of them without scoliosis (85.6%) and 38 with scoliosis (14.4%). No significant differences were found in the general population without scoliosis, except for vBMD at the neck. Comparison of femurs in scoliotic patients showed statistically significant differences at neck aBMD -0.028 g/cm2, p = 0.004), total femur aBMD (--0.032 g/cm2, p = 0.008) and total femur vBMD (--8.9 mg/cm3, p = 0.011), with lower BMD values on the convexity side. In 10 cases (26%) a change in the final T-score diagnosis was observed. CONCLUSION: QCT analysis demonstrated a difference in both areal and volumetric BMD between the two femurs of scoliotic patients, in relation to the side of the scoliotic curve. If these data will be confirmed by larger studies, bilateral femoral DXA acquisition may be proposed for these patients.
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Osteoporosis , Escoliosis , Humanos , Densidad Ósea , Escoliosis/diagnóstico por imagen , Escoliosis/complicaciones , Absorciometría de Fotón/efectos adversos , Absorciometría de Fotón/métodos , Estudios Retrospectivos , Osteoporosis/etiología , Cuello Femoral , Fémur/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodosRESUMEN
PURPOSE: To investigate the role of ultrasound (US) in the evaluation of intrinsic and extrinsic ligaments of the wrist with magnetic resonance arthrography (MRA) as the reference standard. MATERIALS AND METHODS: This prospective study included patients referred for MRA after wrist trauma. US examination was performed just before MRA. On the dorsal and palmar sides of the wrist, the intrinsic interosseus and midcarpal, extrinsic, and collateral ligaments were evaluated. MRA was performed on a 1.5-T unit. In the first 20 patients included, ligament thickness was independently assessed using US and MRA and thickness reproducibility was calculated. Ligament integrity was evaluated in all patients. RESULTS: 38 patients (22 men, 16 women; mean age: 38 years) were included. Ligament thickness reproducibility ranged between 44% for the palmar ulnocapitate ligament and 71% for the palmar scaphotriquetral ligament. US had a sensitivity, specificity, positive and negative predictive values, and accuracy of 100% in the identification of tears of the palmar (n=8) and dorsal (n=3) bands of the scapholunate ligament and the ulnar collateral ligament (n=3). It had a sensitivity of 100%, specificity of 97%, positive predictive value of 50%, negative predictive value of 100%, and accuracy of 97% in the identification of tears of the palmar ulnolunate ligament (n=1). CONCLUSION: Compared to MRA, US showed good reproducibility in the assessment of wrist ligament thickness and similar accuracy with respect to identifying tears of the scapholunate, palmar ulnolunate, and ulnar collateral ligaments.