In Vivo Assessment of Exercise-Induced Glenohumeral Cartilage Strain

Design and validation of a semi-automatic bone segmentation algorithm from MRI to improve research efficiency

Segmentation of medical images into different tissue types is essential for many advancements in orthopaedic research; however, manual segmentation techniques can be time- and cost-prohibitive. The purpose of this work was to develop a semi-automatic segmentation algorithm that leverages gradients in spatial intensity to isolate the patella bone from magnetic resonance (MR) images of the knee that does not require a training set. The developed algorithm was validated in a sample of four human participants (in vivo) and three porcine stifle joints (ex vivo) using both magnetic resonance imaging (MRI) and computed tomography (CT). We assessed the repeatability (expressed as mean ± standard deviation) of the semi-automatic segmentation technique on: (1) the same MRI scan twice (Dice similarity coefficient = 0.988 ± 0.002; surface distance = − 0.01 ± 0.001 mm), (2) the scan/re-scan repeatability of the segmentation technique (surface distance = − 0.02 ± 0.03 mm), (3) how the semi-automatic segmentation technique compared to manual MRI segmentation (surface distance = − 0.02 ± 0.08 mm), and (4) how the semi-automatic segmentation technique compared when applied to both MRI and CT images of the same specimens (surface distance = − 0.02 ± 0.06 mm). Mean surface distances perpendicular to the cartilage surface were computed between pairs of patellar bone models. Critically, the semi-automatic segmentation algorithm developed in this work reduced segmentation time by approximately 75%. This method is promising for improving research throughput and potentially for use in generating training data for deep learning algorithms.

3-T T2 mapping magnetic resonance imaging for biochemical assessment of normal and damaged glenoid cartilage: a prospective arthroscopy-controlled study

This study evaluated the ability of T2 mapping to assess the glenoid cartilage using arthroscopy as the gold standard. Eighteen consecutive patients (mean age: 52.4 ± 14.72 years, including 12 men) with shoulder pain underwent T2 mapping at 3-T with subsequent shoulder arthroscopy. With correlation to cartilage-sensitive morphologic sequences regions-of-interest were placed in the corresponding T2 maps both in normal-appearing cartilage and focal cartilage lesions using a quadrant-wise approach. Inter-reader and intra-reader correlation coefficients (ICCs) between two independent radiologists as well as cut-off values with their sensitivities/specificities for the detection of cartilage damage were calculated. The mean T2 value for healthy cartilage was 23.0 ± 3 ms with significantly higher values in the superior quadrants compared to the inferior quadrants (p < 0.0001). In 5 patients with focal cartilage damage significantly higher T2 values of 44.7 ± 3.7 ms (P < 0.01) were observed. The maximum T2 value in normal cartilage (27.3 ms) was lower than the minimum value in damaged cartilage (40.8 ms) resulting in perfect sensitivities/specificities of 100% (95% confidence-interval 47.8-100.0) for all cut-off values between 27.3-40.8 ms. ICCs ranged between 0.63 and 0.99. In conclusion, T2 mapping can evaluate biochemical cartilage integrity and discriminates arthroscopy-proven healthy and damaged glenoid cartilage with high diagnostic performance.

Editorial Commentary: Advances in 3-Dimensional Imaging are the Key to Improving our Surgical Precision in Hip Arthroscopy and Beyond

Advances in high-resolution magnetic resonance imaging have driven a wealth of knowledge in orthopaedic basic science. The application of these novel techniques to clinical practice is the next logical step for enhancing our understanding of intra-articular pathology and morphology. The specific diagnostic challenge presented by hip labral and chondral pathology is a particular point of interest, given the increasing popularity of hip arthroscopy. As our field continues to progress in complexity, the integration of new, higher-resolution imaging sequences such as multiple-echo recombined gradient echo and double-echo steady state provide the potential to enhance preoperative planning and ultimately the effectiveness of our arthroscopic techniques.