Deformable registration of radiation isodose lines to delayed contrast-enhanced magnetic resonance images for assessment of myocardial lesion formation following proton beam therapy

2018 ◽  
Author(s):  
Maryam E. Rettmann ◽  
Helge Lehmann ◽  
Atsushi Suzuki ◽  
Amanda Deisher ◽  
Songyun Wang ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Proton Beam ◽  
Proton Beam Therapy ◽  
Magnetic Resonance Images ◽  
Deformable Registration ◽  
Lesion Formation ◽  
Myocardial Lesion ◽  
Contrast Enhanced

scholarly journals Detection and Diagnosis of Breast Cancer Using Artificial Intelligence Based Assessment of Maximum Intensity Projection Dynamic Contrast-Enhanced Magnetic Resonance Images

Diagnostics ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 330
Author(s):  
Mio Adachi ◽  
Tomoyuki Fujioka ◽  
Mio Mori ◽  
Kazunori Kubota ◽  
Yuka Kikuchi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Magnetic Resonance ◽  
Diagnostic Performance ◽  
Maximum Intensity Projection ◽  
Breast Mri ◽  
Magnetic Resonance Images ◽  
Maximum Intensity ◽  
Validation Data ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

We aimed to evaluate an artificial intelligence (AI) system that can detect and diagnose lesions of maximum intensity projection (MIP) in dynamic contrast-enhanced (DCE) breast magnetic resonance imaging (MRI). We retrospectively gathered MIPs of DCE breast MRI for training and validation data from 30 and 7 normal individuals, 49 and 20 benign cases, and 135 and 45 malignant cases, respectively. Breast lesions were indicated with a bounding box and labeled as benign or malignant by a radiologist, while the AI system was trained to detect and calculate possibilities of malignancy using RetinaNet. The AI system was analyzed using test sets of 13 normal, 20 benign, and 52 malignant cases. Four human readers also scored these test data with and without the assistance of the AI system for the possibility of a malignancy in each breast. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were 0.926, 0.828, and 0.925 for the AI system; 0.847, 0.841, and 0.884 for human readers without AI; and 0.889, 0.823, and 0.899 for human readers with AI using a cutoff value of 2%, respectively. The AI system showed better diagnostic performance compared to the human readers (p = 0.002), and because of the increased performance of human readers with the assistance of the AI system, the AUC of human readers was significantly higher with than without the AI system (p = 0.039). Our AI system showed a high performance ability in detecting and diagnosing lesions in MIPs of DCE breast MRI and increased the diagnostic performance of human readers.

Temporal covariance analysis of first-pass contrast-enhanced myocardial magnetic resonance images

2001 ◽  
Vol 31 (2) ◽  
pp. 133-142 ◽  
Author(s):  
Abdel-Ouahab Boudraa ◽  
Faiza Behloul ◽  
Marc Janier ◽  
Emmanuelle Canet ◽  
Jacques Champier ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Magnetic Resonance Images ◽  
Covariance Analysis ◽  
Contrast Enhanced ◽  
First Pass

scholarly journals Effusion attenuates the effect of synovitis on radiographic progression in patients with hand osteoarthritis: a longitudinal magnetic resonance imaging study

2020 ◽  
Vol 40 (1) ◽  
pp. 315-319
Author(s):  
W. Damman ◽  
R. Liu ◽  
M. Reijnierse ◽  
F. R. Rosendaal ◽  
J. L. Bloem ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Radiographic Progression ◽  
Imaging Study ◽  
Magnetic Resonance Images ◽  
High Signal ◽  
Hand Osteoarthritis ◽  
Mr Images ◽  
Contrast Enhanced ◽  
Key Points

AbstractAn exploratory study to determine the role of effusion, i.e., fluid in the joint, in pain, and radiographic progression in patients with hand osteoarthritis. Distal and proximal interphalangeal joints (87 patients, 82% women, mean age 59 years) were assessed for pain. T2-weighted and Gd-chelate contrast-enhanced T1-weighted magnetic resonance images were scored for enhanced synovial thickening (EST, i.e., synovitis), effusion (EST and T2-high signal intensity [hsi]) and bone marrow lesions (BMLs). Effusion was defined as follows: (1) T2-hsi > 0 and EST = 0; or 2) T2-hsi = EST but in different joint locations. Baseline and 2-year follow-up radiographs were scored following Kellgren-Lawrence, increase ≥ 1 defined progression. Associations between the presence of effusion and pain and radiographic progression, taking into account EST and BML presence, were explored on the joint level. Effusion was present in 17% (120/691) of joints, with (63/120) and without (57/120) EST. Effusion on itself was not associated with pain or progression. The association with pain and progression, taking in account other known risk factors, was stronger in the absence of effusion (OR [95% CI] 1.7 [1.0–2.9] and 3.2 [1.7–5.8]) than in its presence (1.6 [0.8–3.0] and 1.3 [0.5–3.1]). Effusion can be assessed on MR images and seems not to be associated with pain or radiographic progression but attenuates the association between synovitis and progression. Key Points• Effusion is present apart from synovitis in interphalangeal joints in patients with hand OA.• Effusion in finger joints can be assessed as a separate feature on MR images.• Effusion seems to be of importance for its attenuating effect on the association between synovitis and radiographic progression.

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