Evaluating the Impact of High Intensity Interval Training on Axial Psoriatic Arthritis Based on MR Images.

High intensity interval training (HIIT) has been shown to benefit patients with psoriatic arthritis (PsA). However, magnetic resonance (MR) imaging has uncovered bone marrow edema (BME) in healthy volunteers after vigorous exercise. The purpose of this study was to investigate MR images of the spine of PsA patients for changes in BME after HIIT. PsA patients went through 11 weeks of HIIT (N = 19, 4 men, median age 52 years) or no change in physical exercise habits (N = 20, 8 men, median age 45 years). We acquired scores for joint affection and pain and short tau inversion recovery (STIR) and T1-weighted MR images of the spine at baseline and after 11 weeks. MR images were evaluated for BME by a trained radiologist, by SpondyloArthritis Research Consortium of Canada (SPARCC) scoring, and by extraction of textural features. No significant changes of BME were detected in MR images of the spine after HIIT. This was consistent for MR image evaluation by a radiologist, by SPARCC, and by texture analysis. Values of textural features were significantly different in BME compared to healthy bone marrow. In conclusion, BME in spine was not changed after HIIT, supporting that HIIT is safe for PsA patients.

Feasibility of contrast-enhanced MRI derived textural features to predict overall survival in locally advanced breast cancer.

BACKGROUND: The prognosis for women with locally advanced breast cancer (LABC) is poor and there is a need for better treatment stratification. Gray-level co-occurrence matrix (GLCM) texture analysis of magnetic resonance (MR) images has been shown to predict pathological response and could become useful in stratifying patients to more targeted treatments. PURPOSE: To evaluate the ability of GLCM textural features obtained before neoadjuvant chemotherapy to predict overall survival (OS) seven years after diagnosis of patients with LABC. MATERIAL AND METHODS: This retrospective study includes data from 55 patients with LABC. GLCM textural features were extracted from segmented tumors in pre-treatment dynamic contrast-enhanced 3-T MR images. Prediction of OS by GLCM textural features was assessed and compared to predictions using traditional clinical variables. RESULTS: Linear mixed-effect models showed significant differences in five GLCM features (f1, f2, f5, f10, f11) between survivors and non-survivors. Using discriminant analysis for prediction of survival, GLCM features from 2 min post-contrast images achieved a classification accuracy of 73% (P < 0.001), whereas traditional prognostic factors resulted in a classification accuracy of 67% (P = 0.005). Using a combination of both yielded the highest classification accuracy (78%, P < 0.001). Median values for features f1, f2, f10, and f11 provided significantly different survival curves in Kaplan-Meier analysis. CONCLUSION: This study shows a clear association between textural features from post-contrast images obtained before neoadjuvant chemotherapy and OS seven years after diagnosis. Further studies in larger cohorts should be undertaken to investigate how this prognostic information can be used to benefit treatment stratification.

Quantifying bone marrow inflammatory edema in the spine and sacroiliac joints with thresholding.

BACKGROUND: Psoriatic Arthritis (PsA) is a chronic inflammatory arthritis that develops in patients with psoriasis. Inflammatory edema in the spine may reflect subclinical disease activity and be a predictor of radiographic progression. A semi-quantitative method established by the spondyloarthritis research consortium of Canada (SPARCC) is commonly used to assess the disease activity in MR images of the spine. This study aims to evaluate thresholding for quantification of subtle bone marrow inflammation in the spine and the sacroiliac (SI) joints of patients with PsA and compare it with the SPARCC scoring system. METHODS: Short tau inversion recovery (STIR) MR images of the spine (N = 85) and the SI joints (N = 95) of patients with PsA (N = 41) were analyzed. A threshold was applied to visible bone marrow in order to mask areas with higher signal intensity, which are consistent with inflammation. These areas were considered as inflammatory lesions. The volume and relative signal intensity of the lesions were calculated. Results from thresholding were compared to SPARCC scores using linear mixed-effects models. The specificity and sensitivity of thresholding were also calculated. RESULTS: A significant positive correlation between the volumes and mean relative signal intensities, which were calculated by thresholding analysis, and the SPARCC scores was detected for both spine (p < 0.001) and SI joints (p < 0.001). For the spine, thresholding had sensitivity and specificity of 83% and 76% respectively, while for the SI joints the values were 51% and 88% respectively. CONCLUSIONS: Thresholding allows quantification of subtle bone marrow inflammatory edema in patients with psoriatic arthritis, and could support SPARCC scoring of the spine. Improved image processing and inclusion of automatic segmentation are required for thresholding of STIR images to become a rapid and reliable method for quantitative measures of inflammation. TRIAL REGISTRATION: NCT02995460 (December 14, 2016) - Retrospectively registered.

Impacts of MR spectroscopic imaging on glioma patient management.

Magnetic resonance (MR) modalities are routine imaging tools in the diagnosis and management of gliomas. MR spectroscopic imaging (MRSI), which relies on the metabolic characteristics of tissues, has been developed to accelerate the understanding of gliomas and to aid in effective clinical decision making and development of targeted therapies. In this review, the potentials and practical challenges to frequently use this technique in clinical management of gliomas are discussed. The applications of new biomarkers detectable by MRSI in differential glioma diagnosis, pre- and post-treatment evaluations, and neurosurgery are also addressed.