Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary findings.

BACKGROUND: Radiomic analysis is defined as computationally extracting features from radiographic images for quantitatively characterizing disease patterns. There has been recent interest in examining the use of MRI for identifying prostate cancer (PCa) aggressiveness in patients on active surveillance (AS). PURPOSE: To evaluate the performance of MRI-based radiomic features in identifying the presence or absence of clinically significant PCa in AS patients. STUDY TYPE: Retrospective. SUBJECTS MODEL: MRI/TRUS (transperineal grid ultrasound) fusion-guided biopsy was performed for 56 PCa patients on AS who had undergone prebiopsy. FIELD STRENGTH/SEQUENCE: 3T, T2 -weighted (T2 w) and diffusion-weighted (DW) MRI. ASSESSMENT: A pathologist histopathologically defined the presence of clinically significant disease. A radiologist manually delineated lesions on T2 w-MRs. Then three radiologists assessed MRIs using PIRADS v2.0 guidelines. Tumors were categorized into four groups: MRI-negative-biopsy-negative (Group 1, N = 15), MRI-positive-biopsy-positive (Group 2, N = 16), MRI-negative-biopsy-positive (Group 3, N = 10), and MRI-positive-biopsy-negative (Group 4, N = 15). In all, 308 radiomic features (First-order statistics, Gabor, Laws Energy, and Haralick) were extracted from within the annotated lesions on T2 w images and apparent diffusion coefficient (ADC) maps. The top 10 features associated with clinically significant tumors were identified using minimum-redundancy-maximum-relevance and used to construct three machine-learning models that were independently evaluated for their ability to identify the presence and absence of clinically significant disease. STATISTICAL TESTS: Wilcoxon rank-sum tests with P < 0.05 considered statistically significant. RESULTS: Seven T2 w-based (First-order Statistics, Haralick, Laws, and Gabor) and three ADC-based radiomic features (Laws, Gradient and Sobel) exhibited statistically significant differences (P < 0.001) between malignant and normal regions in the training groups. The three constructed models yielded overall accuracy improvement of 33, 60, 80% and 30, 40, 60% for patients in testing groups, when compared to PIRADS v2.0 alone. DATA CONCLUSION: Radiomic features could help in identifying the presence and absence of clinically significant disease in AS patients when PIRADS v2.0 assessment on MRI contradicted pathology findings of MRI-TRUS prostate biopsies. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Combination of Peri-Tumoral and Intra-Tumoral Radiomic Features on Bi-Parametric MRI Accurately Stratifies Prostate Cancer Risk: A Multi-Site Study.

Background: Prostate cancer (PCa) influences its surrounding habitat, which tends to manifest as different phenotypic appearances on magnetic resonance imaging (MRI). This region surrounding the PCa lesion, or the peri-tumoral region, may encode useful information that can complement intra-tumoral information to enable better risk stratification. Purpose: To evaluate the role of peri-tumoral radiomic features on bi-parametric MRI (T2-weighted and Diffusion-weighted) to distinguish PCa risk categories as defined by D'Amico Risk Classification System. Materials and Methods: We studied a retrospective, HIPAA-compliant, 4-institution cohort of 231 PCa patients (n = 301 lesions) who underwent 3T multi-parametric MRI prior to biopsy. PCa regions of interest (ROIs) were delineated on MRI by experienced radiologists following which peri-tumoral ROIs were defined. Radiomic features were extracted within the intra- and peri-tumoral ROIs. Radiomic features differentiating low-risk from: (1) high-risk (L-vs.-H), and (2) (intermediate- and high-risk (L-vs.-I + H)) lesions were identified. Using a multi-institutional training cohort of 151 lesions (D1, N = 116 patients), machine learning classifiers were trained using peri- and intra-tumoral features individually and in combination. The remaining 150 lesions (D2, N = 115 patients) were used for independent hold-out validation and were evaluated using Receiver Operating Characteristic (ROC) analysis and compared with PI-RADS v2 scores. Results: Validation on D2 using peri-tumoral radiomics alone resulted in areas under the ROC curve (AUCs) of 0.84 and 0.73 for the L-vs.-H and L-vs.-I + H classifications, respectively. The best combination of intra- and peri-tumoral features resulted in AUCs of 0.87 and 0.75 for the L-vs.-H and L-vs.-I + H classifications, respectively. This combination improved the risk stratification results by 3-6% compared to intra-tumoral features alone. Our radiomics-based model resulted in a 53% accuracy in differentiating L-vs.-H compared to PI-RADS v2 (48%), on the validation set. Conclusion: Our findings suggest that peri-tumoral radiomic features derived from prostate bi-parametric MRI add independent predictive value to intra-tumoral radiomic features for PCa risk assessment.

Resistive Exercise for Arthritic Cartilage Health (REACH): a randomized double-blind, sham-exercise controlled trial.

BACKGROUND: This article provides the rationale and methodology, of the first randomised controlled trial to our knowledge designed to assess the efficacy of progressive resistance training on cartilage morphology in women with knee osteoarthritis.Development and progression of osteoarthritis is multifactorial, with obesity, quadriceps weakness, joint malalignment, and abnormal mechanical joint forces particularly relevant to this study. Progressive resistance training has been reported to improve pain and disability in osteoarthritic cohorts. However, the disease-modifying potential of progressive resistance training for the articular cartilage degeneration characteristic of osteoarthritis is unknown. Our aim was to investigate the effect of high intensity progressive resistance training on articular cartilage degeneration in women with knee osteoarthritis. METHODS: Our cohort consisted of women over 40 years of age with primary knee osteoarthritis, according to the American College of Rheumatology clinical criteria. Primary outcome was blinded measurement of cartilage morphology via magnetic resonance imaging scan of the tibiofemoral joint. Secondary outcomes included walking endurance, balance, muscle strength, endurance, power, and velocity, body composition, pain, disability, depressive symptoms, and quality of life.Participants were randomized into a supervised progressive resistance training or sham-exercise group. The progressive resistance training group trained muscles around the hip and knee at 80% of their peak strength and progressed 3% per session, 3 days per week for 6 months. The sham-exercise group completed all exercises except hip adduction, but without added resistance or progression. Outcomes were repeated at 3 and 6 months, except for the magnetic resonance imaging scan, which was only repeated at 6 months. DISCUSSION: Our results will provide an evaluation of the disease-modifying potential of progressive resistance training for osteoarthritis. TRIAL REGISTRATION: ANZCTR Reference No. 12605000116628.

Memory training alters hippocampal neurochemistry in healthy elderly.

Accumulating epidemiological evidence supports the notion of brain reserve, but there has been no investigation of neurobiological change associated with brief mental activation training in humans. Healthy older individuals were therefore investigated with magnetic resonance spectroscopy (MRS) in different brain regions before and after 5 weeks of focused memory training. Recall of a test-word list of > 23 items was achieved accompanied by elevation of creatine and choline signals in the hippocampus. Those at risk for neural dysfunction, as indicated by lower neurometabolites at baseline, demonstrated the largest MRS increases after training. Biochemical changes related to cellular energy and cell-membrane turnover were found to increase after structured memory exercises and were limited to the medial temporal lobe.

Rotator cuff tear in an elderly woman performing progressive resistance training: case report from a randomized controlled trial.

The purpose of this article is to document a rotator cuff tear sustained by an elderly woman performing progressive resistance training (PRT) in a recent randomized controlled clinical trial. The patient was a sedentary 73-y-old Caucasian woman. Investigation revealed an acute, full-thickness tear of the right supraspinatus secondary to performing a shoulder press exercise. Further investigation via MRI revealed degenerative disease of the acromioclavicular joint including lateral downsloping of the acromion and an anteroinferior acromial spur, which would presdispose to impingement. Conservative management was implemented in this case for over 6 months with minimal success. The patient remained functionally limited in virtually all activities of daily living. Given the medical history, health status, physical condition, and age of our patient, it is probable that degenerative changes predisposed the patient to the injury. To our knowledge this is the first published report of an older adult sustaining a rotator cuff tear during PRT.

A fiber-optic system for recording skin conductance in the MRI scanner.

The acquisition of the skin conductance response (SCR) during functional magnetic resonance imaging (fMRI) raises significant safety issues, as well as practical ones, which need to be addressed in order for these experiments to be conducted safely and successfully. Metallic and conductive wires in the presence of time-varying gradient magnetic fields such as those present in fMRI experiments may induce heating, as well as electric fields, in these components and, if in contact with the subject, could produce severe burns and electric shocks. Moreover, these metallic and conductive components can significantly distort the magnetic field, resulting in image artifacts. A system for recording the SCR in humans simultaneously with fMRI is presented. The device is a fiber-optic-based transducer, which records the SCR from two fingers of the same hand, using electrodes containing inline radio frequency (RF) suppression filters and protective resistive loads. The fiber-optic SCR transducer was tested using 1.5 and 3.0 Tesla MRI scanners running EPI sequences. This system was able to safely record SCRs free of RF interference during an fMRI experiment, and the fiber-optic design of the transducer eliminated any artifacts on the MRI scan.