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Magnetic resonance imaging characteristics in patients with histopathologically proven fibrous dysplasia-a systematic review.

ABSTRACT: OBJECTIVE:To examine the demographics, lesion location, and characteristic magnetic resonance imaging (MRI) findings in patients with histopathologically proven fibrous dysplasia (FD). MATERIALS AND METHODS:A systematic literature search of the MRI findings in patients with histologically proven FD was performed. Altogether, 76 articles with 136 patients were evaluated. RESULTS:The mean age of the patients was 35.0?+?-?18.5 years (range 1 month-75 years). Fifty-eight of the cases were females, 51 males, and in 27 gender was not defined. The most common locations were craniofacial (n?=?55 (40%)), long bones (n?=?31 (23%)), and spine (n?=?24 (18%)). The monostotic form of FD was the most common. Signal intensities (SI) on T1-weighted images were predominantly hypointense (n?=?46 (37%)). The SI was highly variable on T2-weighted images with hyperintensity being most common (n?=?22 (18%)). Contrast enhancement was found in 75 (55%) FD patients. Secondary aneurysmal bone cysts (ABCs) and malignant transformation in patients without prior radiotherapy was found in some patients. CONCLUSION:Current knowledge of the MRI findings in patients with FD is based mainly on case reports. SI in patients with FD is variable and contrast enhancement is common. FD may explain etiology of spinal bone tumor in some patients. FD with malignant transformation should be considered also in patients without prior radiotherapy. Further studies are needed to clarify if FD displays specific characteristics allowing it to be distinguished from other bone tumors.

SUBMITTER: Kinnunen AR

PROVIDER: S-EPMC7170814 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Magnetic resonance imaging characteristics in patients with histopathologically proven fibrous dysplasia-a systematic review.

Kinnunen Anna-Reetta AR Sironen Reijo R Sipola Petri P

Skeletal radiology 20200210 6

<h4>Objective</h4>To examine the demographics, lesion location, and characteristic magnetic resonance imaging (MRI) findings in patients with histopathologically proven fibrous dysplasia (FD).<h4>Materials and methods</h4>A systematic literature search of the MRI findings in patients with histologically proven FD was performed. Altogether, 76 articles with 136 patients were evaluated.<h4>Results</h4>The mean age of the patients was 35.0 + - 18.5 years (range 1 month-75 years). Fifty-eight of the ...[more]

PMID: 32040603

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Project description:(1) Background: Transfer learning refers to machine learning techniques that focus on acquiring knowledge from related tasks to improve generalization in the tasks of interest. In magnetic resonance imaging (MRI), transfer learning is important for developing strategies that address the variation in MR images from different imaging protocols or scanners. Additionally, transfer learning is beneficial for reutilizing machine learning models that were trained to solve different (but related) tasks to the task of interest. The aim of this review is to identify research directions, gaps in knowledge, applications, and widely used strategies among the transfer learning approaches applied in MR brain imaging; (2) Methods: We performed a systematic literature search for articles that applied transfer learning to MR brain imaging tasks. We screened 433 studies for their relevance, and we categorized and extracted relevant information, including task type, application, availability of labels, and machine learning methods. Furthermore, we closely examined brain MRI-specific transfer learning approaches and other methods that tackled issues relevant to medical imaging, including privacy, unseen target domains, and unlabeled data; (3) Results: We found 129 articles that applied transfer learning to MR brain imaging tasks. The most frequent applications were dementia-related classification tasks and brain tumor segmentation. The majority of articles utilized transfer learning techniques based on convolutional neural networks (CNNs). Only a few approaches utilized clearly brain MRI-specific methodology, and considered privacy issues, unseen target domains, or unlabeled data. We proposed a new categorization to group specific, widely-used approaches such as pretraining and fine-tuning CNNs; (4) Discussion: There is increasing interest in transfer learning for brain MRI. Well-known public datasets have clearly contributed to the popularity of Alzheimer's diagnostics/prognostics and tumor segmentation as applications. Likewise, the availability of pretrained CNNs has promoted their utilization. Finally, the majority of the surveyed studies did not examine in detail the interpretation of their strategies after applying transfer learning, and did not compare their approach with other transfer learning approaches.

Project description:Purpose To evaluate whether there is a correlation between the position of the patella and trochlear morphology in patients with and without patellar instability using exclusively MRI measurements. Methods MRI scans of knees in patients with patellofemoral instability and knees of patients with an ACL (anterior cruciate ligament) tear as a control group were reviewed. Measurements of patellar position (Canton-Deschamps ratio, Patellar Trochlear Index, and lateral patellar inclination) and trochlear morphology (lateral trochlear inclination and sulcus angle) were obtained from each scan. Bivariate and multivariate analysis was performed to identify correlations between study group, demographics, and patellofemoral joint measurements. Results There were 70 knees in the patellofemoral instability group and 60 knees in the control group. Bivariate analysis showed a significant difference in all measurements between the patellar instability group and the control group. Multivariate analysis showed modest correlations between patellar position and trochlear morphology. The Caton-Deschamps (CD) ratio correlated with patellar trochlear index (P < .001) and lateral trochlear inclination (P < .001). The respective R-square goodness of fit was 41.1%. Patellar trochlear index correlated with CD ratio (P < .001), lateral trochlear inclination (P < .001), lateral patellar inclination (P < .001), and patellar instability group (P = .011). The R-sq goodness of fit was 37.3%. Lateral patellar inclination correlated with patellar trochlear index (P < .001), Lateral trochlear inclination (P < .001), and age at first dislocation or injury (P = .02). The R-sq goodness of fit was 68.56%. Conclusions Using MRI-based measurements of the patellofemoral joint, we identified modest, but significant, correlations between measures of patellar height (patellar trochlear index, CD ratio, and lateral patellar inclination) and trochlear dysplasia. This correlation is unclear and is likely multifactorial, but on the basis of this work, a causal relationship between trochlear dysplasia and patella alta cannot be established. Clinical Relevance Radiographic evaluation of the patella and how it relates to the surrounding boney anatomy provides important information regarding our understanding of patella instability and its treatment.

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Dataset Information

Magnetic resonance imaging characteristics in patients with histopathologically proven fibrous dysplasia-a systematic review.

Publications

Magnetic resonance imaging characteristics in patients with histopathologically proven fibrous dysplasia-a systematic review.

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