Author's response to reviews Title: Quantification of Bone Marrow Lesion Volume and Volume Change Using Semi-automated Segmentation: Data from the Osteoarthritis Initiative Authors:

Quantification of bone marrow lesion volume and volume change using semi-automated segmentation: data from the osteoarthritis initiative

BACKGROUND To determine the validity of a semi-automated segmentation of bone marrow lesions (BMLs) in the knee. METHODS Construct validity of the semi-automated BML segmentation method was explored in two studies performed using sagittal intermediate weighted, turbo spine echo, fat-suppressed magnetic resonance imaging sequences obtained from the Osteoarthritis Initiative. The first study (n...

Author's response to reviews Title: Diagnostic performance and inter-observer concordance in lesion detection with the Automated Breast Volume Scanner (ABVS) Authors:

Measurement of bone marrow lesions by MR imaging in knee osteoarthritis using quantitative segmentation methods – a reliability and sensitivity to change analysis

BACKGROUND Longitudinal assessment of bone marrow lesions (BMLs) in knee osteoarthritis (KOA) by MRI is usually performed using semi-quantitative grading methods. Quantitative segmentation methods may be more sensitive to detect change over time. The purpose of this study was to evaluate and compare the validity and sensitivity to detect changes of two quantitative MR segmentation methods for m...

Magnetic Resonance Image Sequence Influences the Relationship between Bone Marrow Lesions Volume and Pain: Data from the Osteoarthritis Initiative

Subchondral bone marrow lesions (BMLs) are related to structural and symptomatic osteoarthritis progression. However, it is unclear how sequence selection influences a quantitative BML measurement and its construct validity. We compared quantitative assessment of BMLs on intermediate-weighted fat suppressed (IW FS) turbo spin echo and 3-dimensional dual echo steady state (3D DESS) sequences. We...

Automatic segmentation of high- and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative.

Clinical studies including thousands of magnetic resonance imaging (MRI) scans offer potential for pathogenesis research in osteoarthritis. However, comprehensive quantification of all bone, cartilage, and meniscus compartments is challenging. We propose a segmentation framework for fully automatic segmentation of knee MRI. The framework combines multiatlas rigid registration with voxel classif...