Implementing ABCD studyⓇ MRI sequences for multi-site cohort studies: Practical guide to necessary steps, preprocessing methods, and challenges.

Large multi-site studies that combine magnetic resonance imaging (MRI) data across research sites present exceptional opportunities to advance neuroscience research. However, scanner or site variability and non-standardised image acquisition protocols, data processing and analysis pipelines can adversely affect the reliability and repeatability of MRI derived brain measures. We implemented a standardised MRI protocol based on that used in the Adolescent Brain Cognition Development (ABCD)Ⓡ study in two sites, and across four MRI scanners. Twice repeated measurements of a single healthy volunteer were obtained in two sites and in four 3T MRI scanners (vendors: Siemens, Philips, and GE). Imaging data included anatomical scans (T1 weighted, T2 weighted), diffusion weighted imaging (DWI) and resting state functional MRI (rs-fMRI). Standardised containerized pipelines were utilised to pre-process the data and different image quality metrics and test-retest variability of different brain metrics were evaluated. The implementation of the MRI protocols was possible with minor adjustments in acquisition (e.g. repetition time (TR), higher b-values) and exporting (DICOM formats) of images due to different technical performance of the scanners. This study provides practical insights into the implementation of standardised sequences and data processing for multisite studies, showcase the benefits of containerised preprocessing tools, and highlights the need for careful optimisation of multisite image acquisition.

X-ray scatter in projection radiography.

Projection radiography is the most common radiological modality, and radiation safety of it concerns both radiation workers and the public. We measured and generated a series of scattered radiation maps for projection radiography and estimated effective doses of the supporting person during exposure. Measured adult patient protocols included chest posterior-anterior, chest lateral, pelvis anterior-posterior (AP), abdomen AP and bedside chest AP. Maps concretise spatial distribution and the scattered radiation dose rates in different imaging protocols. Highest and lowest rates were measured in abdomen AP and bedside chest AP protocols, respectively. The effective dose of supporting person in abdomen AP examination at distance of 0.5 m was 300 nSv and in bedside supine chest AP examination at distance of 0.7 m was 0.5 nSv. The estimated annual effective dose of emergency unit radiographer was 0.11 mSv. The obtained effective dose values are small compared to annual dose limits of radiation workers and the public.

Predicting osteoarthritis onset and progression with 3D texture analysis of cartilage MRI DESS: 6-Year data from osteoarthritis initiative.

In this study, we developed a gray level co-occurrence matrix-based 3D texture analysis method for dual-echo steady-state (DESS) magnetic resonance (MR) images to be used for knee cartilage analysis in osteoarthritis (OA) studies and use it to study changes in articular cartilage between different subpopulations based on their rate of progression into radiographically confirmed OA. In total, 642 series of right knee DESS MR images at 3T were obtained from baseline, 36- and 72-month follow-ups from the OA Initiative database. At baseline, all 214 subjects included in the study had Kellgren-Lawrence (KL) grade <2. Three groups were defined, based on time of progression into radiographic OA (ROA) (KL grades ≥2): control (no progression), fast progressor (ROA at 36 months), and slow progressor (ROA at 72 months) groups. 3D texture analysis was used to extract textural features for femoral and tibial cartilages. All textural features, in both femur and tibia, showed significant longitudinal changes across all groups and tissue layers. Most of the longitudinal changes were observed in progressors, but significant changes were observed also in controls. Differences between groups were mostly seen at baseline and 72 months. The method is sensitive to cartilage changes before and after ROA. It was able to detect longitudinal changes in controls and progressors and to distinguish cartilage alterations due to OA and aging. Moreover, it was able to distinguish controls and different progressor groups before any radiographic signs of OA and during OA. Thus, texture analysis could be used as a marker for the onset and progression of OA.

Characterizing Vocal Tract Dimensions in the Vocal Modes Using Magnetic Resonance Imaging.

OBJECTIVE: The aim was to study vocal tract dimensions in four vocal modes - Neutral, Curbing, Overdrive and Edge - from Complete Vocal Technique (CVT) by means of magnetic resonance imaging (MRI). Furthermore, the purpose was to test the feasibility of MRI to assess CVT vocal modes. METHODS: Four nonclassical singers (two females, two males) trained in CVT were imaged with an MRI scanner while singing sustained vowels at same pitch (Bb4 for females, F4 for males) in all vocal modes. Audio signals were simultaneously recorded through a pipe for quality assurance purposes. Auditory evaluation was performed by three CVT teachers in the scanner control room via headphones, and by one CVT teacher inside the MRI room. Previously developed measurement models modified by the authors were used to measure vocal tract dimensions from sagittal MRI projections. Repeatability test was performed for all measurements. RESULTS: In all subjects, vocal tract dimensions displayed differences between the vocal modes. Edge stood out from other vocal modes by showing most laryngeal narrowing accompanied by shortest vocal tract and highest vertical laryngeal position. For Neutral, least mouth opening and shortest distance between tongue and palate were found. Curbing differed consistently from Edge and somewhat from Overdrive showing higher measured values for vocal fold length. Differences regarding vocal fold length were also detected between Neutral and Edge. As expected, differences in vocal tract dimensions were found between samples sung with different vowels. CONCLUSIONS: Vocal tract adjustments play a key role in the production of the vocal modes. The model used to measure vocal tract dimensions succeeded in finding significant differences between the vocal modes, also detecting differences between different vowel productions. The method used to characterize vocal tract dimensions seem promising and would be worthwhile to apply to a larger material.

Variable angle gray level co-occurrence matrix analysis of T2 relaxation time maps reveals degenerative changes of cartilage in knee osteoarthritis: Oulu knee osteoarthritis study.

BACKGROUND: Texture analysis methods based on gray level co-occurrence matrices (GLCM) can be optimized to probe the spatial correspondence information from knee MRI T2 maps and the changes caused by osteoarthritis, and thus possibly leading to a more sensitive characterization of osteoarthritic cartilage. Curvature of the cartilage surfaces combined with the low image resolution in relation to cartilage thickness set special requirements for an effective texture analysis tool. PURPOSE/HYPOTHESIS: To introduce a novel implementation of GLCM algorithm optimized for cartilage texture analysis; to evaluate the performance of the designed algorithm against mean T2 relaxation time analysis; and to identify the most suitable texture features for discerning osteoarthritic subjects and asymptomatic controls. STUDY TYPE: Case control. POPULATION/SUBJECTS/PHANTOM/SPECIMEN/ANIMAL MODEL: Eighty symptomatic osteoarthritis patients and 64 asymptomatic controls. FIELD STRENGTH/SEQUENCE: Multislice multiecho spin echo sequence on a 3T MRI system. ASSESSMENT: The T2 relaxation time maps were manually segmented by an operator trained for the task. Texture analysis was performed using an in-house algorithm developed in MATLAB. STATISTICAL TESTS: Symptomatic and asymptomatic subjects were compared using Mann-Whitney U-test. Repeatability of different features was addressed using the concordance correlation coefficient (CCC). Spearman's correlations between the features were determined. RESULTS: The algorithm displayed excellent performance in discerning symptomatic and asymptomatic subjects. Fifteen features provided a significant difference between the groups (P ≤ 0.05) and 12 of those had P values smaller than the mean T2 differences. Most of the studied texture features were highly repeatable with CCC over 90%. For the features with significant differences, correlation with mean T2 was low or moderate (|r| ≤ 0.5). DATA CONCLUSION: With careful parameter and feature selection and algorithm optimization, texture analysis provides a powerful tool for assessing knee osteoarthritis with more sensitive detection of cartilage degeneration compared to the mean value of the T2 relaxation times in an identical region of interest. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2018;47:1316-1327.