Dataset Information

The use of chest magnetic resonance imaging in interstitial lung disease: a systematic review.

ABSTRACT: Thin-slices multi-detector computed tomography (MDCT) plays a key role in the differential diagnosis of interstitial lung disease (ILD). However, thin-slices MDCT has a limited ability to detect active inflammation, which is an important target of newly developed ILD drug therapy. Magnetic resonance imaging (MRI), thanks to its multi-parameter capability, provides better tissue characterisation than thin-slices MDCT.Our aim was to summarise the current status of MRI applications in ILD and to propose an ILD-MRI protocol. A systematic literature search was conducted for relevant studies on chest MRI in patients with ILD.We retrieved 1246 papers of which 55 original papers were selected for the review. We identified 24 studies comparing image quality of thin-slices MDCT and MRI using several MRI sequences. These studies described new MRI sequences to assess ILD parenchymal abnormalities, such as honeycombing, reticulation and ground-glass opacity. Thin-slices MDCT remains superior to MRI for morphological imaging. However, recent studies with ultra-short echo-time MRI showed image quality comparable to thin-slices MDCT. Several studies demonstrated the added value of chest MRI by using functional imaging, especially to detect and quantify inflammatory changes.We concluded that chest MRI could play a role in ILD patients to differentiate inflammatory and fibrotic changes and to assess efficacy of new ILD drugs.

SUBMITTER: Romei C

PROVIDER: S-EPMC9489061 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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The use of chest magnetic resonance imaging in interstitial lung disease: a systematic review.

Romei Chiara C Turturici Laura L Tavanti Laura L Miedema Jelle J Fiorini Sara S Marletta Massimo M Wielopolski Piotr P Tiddens Harm H Falaschi Fabio F Ciet Pierluigi P

European respiratory review : an official journal of the European Respiratory Society 20181219 150

Thin-slices multi-detector computed tomography (MDCT) plays a key role in the differential diagnosis of interstitial lung disease (ILD). However, thin-slices MDCT has a limited ability to detect active inflammation, which is an important target of newly developed ILD drug therapy. Magnetic resonance imaging (MRI), thanks to its multi-parameter capability, provides better tissue characterisation than thin-slices MDCT.Our aim was to summarise the current status of MRI applications in ILD and to pr ...[more]

PMID: 30567932

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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:BackgroundThe anterior chest wall (ACW) involvement is characteristic of synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome, yet little research has focused on its magnetic resonance imaging (MRI) findings.PurposeTo characterize the MRI features of the ACW in patients with SAPHO syndrome.MethodsSeventy-one patients with SAPHO syndrome and ACW involvement evidenced by bone scintigraphy were recruited in this cross-sectional study. The ACW region was scanned using sagittal, axial, and oblique coronal Dixon T2-weighted sequences and axial Dixon T1-weighted sequences. The characteristics of both active inflammatory and chronic structural lesions were evaluated.ResultsThe ACW lesions exhibited an asymmetrical distribution and a predilection for the sternocostoclavicular region (93.0%). Notably, 91.5% of the patients had lesions in the area of the anterior first ribs. Bone marrow edema (BME) was observed in 63 (88.7%) patients, which mainly affected the sternocostal joints (87.3%) and the manubrium sterni (84.5%). All of the BMEs were distributed under the articular surface or the bone cortex, consistent with the distribution of the ligaments and joint capsules. Synovitis was detected in 64 (90.1%) patients, with a predilection for the sternoclavicular joints (76.1%). A soft tissue mass or infiltration was found in all the patients who had bone marrow edema. Thirteen (18.3%) patients showed venous stenosis. Structural changes included bone bridge formation (80.3%), hyperostosis (43.7%), and fat infiltration (39.4%). Four common patterns of involvement were observed: the first rib area, the sternoclavicular area, the sternal angle area, and the areas of the second to sixth sternocostal joints.ConclusionThe ACW lesions of SAPHO syndrome demonstrated a triad of enthesitis, synovitis, and osteitis, suggesting complex interactions among the ligaments, synovium, and bones in the region. The inflammatory changes in the first rib area were highlighted in SAPHO syndrome.

Dataset Information

The use of chest magnetic resonance imaging in interstitial lung disease: a systematic review.

Publications

The use of chest magnetic resonance imaging in interstitial lung disease: a systematic review.

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