Generalizability of Deep Learning Segmentation Algorithms for Automated Assessment of Cartilage Morphology and MRI Relaxometry.

BACKGROUND: Deep learning (DL)-based automatic segmentation models can expedite manual segmentation yet require resource-intensive fine-tuning before deployment on new datasets. The generalizability of DL methods to new datasets without fine-tuning is not well characterized. PURPOSE: Evaluate the generalizability of DL-based models by deploying pretrained models on independent datasets varying by MR scanner, acquisition parameters, and subject population. STUDY TYPE: Retrospective based on prospectively acquired data. POPULATION: Overall test dataset: 59 subjects (26 females); Study 1: 5 healthy subjects (zero females), Study 2: 8 healthy subjects (eight females), Study 3: 10 subjects with osteoarthritis (eight females), Study 4: 36 subjects with various knee pathology (10 females). FIELD STRENGTH/SEQUENCE: A 3-T, quantitative double-echo steady state (qDESS). ASSESSMENT: Four annotators manually segmented knee cartilage. Each reader segmented one of four qDESS datasets in the test dataset. Two DL models, one trained on qDESS data and another on Osteoarthritis Initiative (OAI)-DESS data, were assessed. Manual and automatic segmentations were compared by quantifying variations in segmentation accuracy, volume, and T2 relaxation times for superficial and deep cartilage. STATISTICAL TESTS: Dice similarity coefficient (DSC) for segmentation accuracy. Lin's concordance correlation coefficient (CCC), Wilcoxon rank-sum tests, root-mean-squared error-coefficient-of-variation to quantify manual vs. automatic T2 and volume variations. Bland-Altman plots for manual vs. automatic T2 agreement. A P value < 0.05 was considered statistically significant. RESULTS: DSCs for the qDESS-trained model, 0.79-0.93, were higher than those for the OAI-DESS-trained model, 0.59-0.79. T2 and volume CCCs for the qDESS-trained model, 0.75-0.98 and 0.47-0.95, were higher than respective CCCs for the OAI-DESS-trained model, 0.35-0.90 and 0.13-0.84. Bland-Altman 95% limits of agreement for superficial and deep cartilage T2 were lower for the qDESS-trained model, ±2.4 msec and ±4.0 msec, than the OAI-DESS-trained model, ±4.4 msec and ±5.2 msec. DATA CONCLUSION: The qDESS-trained model may generalize well to independent qDESS datasets regardless of MR scanner, acquisition parameters, and subject population. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Validation of watershed-based segmentation of the cartilage surface from sequential CT arthrography scans.

BACKGROUND: This study investigated the utility of a 2-dimensional watershed algorithm for identifying the cartilage surface in computed tomography (CT) arthrograms of the knee up to 33 minutes after an intra-articular iohexol injection as boundary blurring increased. METHODS: A 2D watershed algorithm was applied to CT arthrograms of 3 bovine stifle joints taken 3, 8, 18, and 33 minutes after iohexol injection and used to segment tibial cartilage. Thickness measurements were compared to a reference standard thickness measurement and the 3-minute time point scan. RESULTS: 77.2% of cartilage thickness measurements were within 0.2 mm (1 voxel) of the thickness calculated in the reference scan at the 3-minute time point. 42% fewer voxels could be segmented from the 33-minute scan than the 3-minute scan due to diffusion of the contrast agent out of the joint space and into the cartilage, leading to blurring of the cartilage boundary. The traced watershed lines were closer to the location of the cartilage surface in areas where tissues were in direct contact with each other (cartilage-cartilage or cartilage-meniscus contact). CONCLUSIONS: The use of watershed dam lines to guide cartilage segmentation shows promise for identifying cartilage boundaries from CT arthrograms in areas where soft tissues are in direct contact with each other.

Open Source Software for Automatic Subregional Assessment of Knee Cartilage Degradation Using Quantitative T2 Relaxometry and Deep Learning.

OBJECTIVE: We evaluated a fully automated femoral cartilage segmentation model for measuring T2 relaxation values and longitudinal changes using multi-echo spin-echo (MESE) magnetic resonance imaging (MRI). We open sourced this model and developed a web app available at https://kl.stanford.edu into which users can drag and drop images to segment them automatically. DESIGN: We trained a neural network to segment femoral cartilage from MESE MRIs. Cartilage was divided into 12 subregions along medial-lateral, superficial-deep, and anterior-central-posterior boundaries. Subregional T2 values and four-year changes were calculated using a radiologist's segmentations (Reader 1) and the model's segmentations. These were compared using 28 held-out images. A subset of 14 images were also evaluated by a second expert (Reader 2) for comparison. RESULTS: Model segmentations agreed with Reader 1 segmentations with a Dice score of 0.85 ± 0.03. The model's estimated T2 values for individual subregions agreed with those of Reader 1 with an average Spearman correlation of 0.89 and average mean absolute error (MAE) of 1.34 ms. The model's estimated four-year change in T2 for individual subregions agreed with Reader 1 with an average correlation of 0.80 and average MAE of 1.72 ms. The model agreed with Reader 1 at least as closely as Reader 2 agreed with Reader 1 in terms of Dice score (0.85 vs. 0.75) and subregional T2 values. CONCLUSIONS: Assessments of cartilage health using our fully automated segmentation model agreed with those of an expert as closely as experts agreed with one another. This has the potential to accelerate osteoarthritis research.

Effects of the Competitive Season and Off-Season on Knee Articular Cartilage in Collegiate Basketball Players Using Quantitative MRI: A Multicenter Study.

BACKGROUND: Injuries to the articular cartilage in the knee are common in jumping athletes, particularly high-level basketball players. Unfortunately, these are often diagnosed at a late stage of the disease process, after tissue loss has already occurred. PURPOSE/HYPOTHESIS: To evaluate longitudinal changes in knee articular cartilage and knee function in National Collegiate Athletic Association (NCAA) basketball players and their evolution over the competitive season and off-season. STUDY TYPE: Longitudinal, multisite cohort study. POPULATION: Thirty-two NCAA Division 1 athletes: 22 basketball players and 10 swimmers. FIELD STRENGTH/SEQUENCE: Bilateral magnetic resonance imaging (MRI) using a combined T1ρ and T2 magnetization-prepared angle-modulated portioned k-space spoiled gradient-echo snapshots (MAPSS) sequence at 3T. ASSESSMENT: We calculated T2 and T1ρ relaxation times to compare compositional cartilage changes between three timepoints: preseason 1, postseason 1, and preseason 2. Knee Osteoarthritis Outcome Scores (KOOS) were used to assess knee health. STATISTICAL TESTS: One-way variance model hypothesis test, general linear model, and chi-squared test. RESULTS: In the femoral articular cartilage of all athletes, we saw a global decrease in T2 and T1ρ relaxation times during the competitive season (all P < 0.05) and an increase in T2 and T1ρ relaxation times during the off-season (all P < 0.05). In the basketball players' femoral cartilage, the anterior and central compartments respectively had the highest T2 and T1ρ relaxation times following the competitive season and off-season. The basketball players had significantly lower KOOS measures in every domain compared with the swimmers: Pain (P < 0.05), Symptoms (P < 0.05), Function in Daily Living (P < 0.05), Function in Sport/Recreation (P < 0.05), and Quality of Life (P < 0.05). CONCLUSION: Our results indicate that T2 and T1ρ MRI can detect significant seasonal changes in the articular cartilage of basketball players and that there are regional differences in the articular cartilage that are indicative of basketball-specific stress on the femoral cartilage. This study demonstrates the potential of quantitative MRI to monitor global and regional cartilage health in athletes at risk of developing cartilage problems. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 2.

Characterizing the transient response of knee cartilage to running: Decreases in cartilage T2 of female recreational runners.

Cartilage transmits and redistributes biomechanical loads in the knee joint during exercise. Exercise-induced loading alters cartilage hydration and is detectable using quantitative magnetic resonance imaging (MRI), where T2 relaxation time (T2 ) is influenced by cartilage collagen composition, fiber orientation, and changes in the extracellular matrix. This study characterized short-term transient responses of healthy knee cartilage to running-induced loading using bilateral scans and image registration. Eleven healthy female recreational runners (33.73 ± 4.22 years) and four healthy female controls (27.25 ± 1.38 years) were scanned on a 3T GE MRI scanner with quantitative 3D double-echo in steady-state before running over-ground (runner group) or resting (control group) for 40 min. Subjects were scanned immediately post-activity at 5-min intervals for 60 min. T2 times were calculated for femoral, tibial, and patellar cartilage at each time point and analyzed using a mixed-effects model and Bonferroni post hoc. There were immediate decreases in T2 (mean ± SEM) post-run in superficial femoral cartilage of at least 3.3% ± 0.3% (p = .002) between baseline and Time 0 that remained for 25 min, a decrease in superficial tibial cartilage T2 of 2.9% ± 0.4% (p = .041) between baseline and Time 0, and a decrease in superficial patellar cartilage T2 of 3.6% ± 0.3% (p = .020) 15 min post-run. There were decreases in the medial posterior region of superficial femoral cartilage T2 of at least 5.3 ± 0.2% (p = .022) within 5 min post-run that remained at 60 min post-run. These results increase understanding of transient responses of healthy cartilage to repetitive, exercise-induced loading and establish preliminary recommendations for future definitive studies of cartilage response to running.

The prevalence of femoroacetabular impingement anatomy in Division 1 aquatic athletes who tread water.

Femoroacetabular impingement (FAI) is a disorder that causes hip pain and disability in young patients, particularly athletes. Increased stress on the hip during development has been associated with increased risk of cam morphology. The specific forces involved are unclear, but may be due to continued rotational motion, like the eggbeater kick. The goal of this prospective cohort study was to use magnetic resonance imaging (MRI) to identify the prevalence of FAI anatomy in athletes who tread water and compare it to the literature on other sports. With university IRB approval, 20 Division 1 water polo players and synchronized swimmers (15 female, 5 male), ages 18-23 years (mean age 20.7 ± 1.4), completed the 33-item International Hip Outcome Tool and underwent non-contrast MRI scans of both hips using a 3 Tesla scanner. Recruitment was based on sport, with both symptomatic and asymptomatic individuals included. Cam and pincer morphology were identified. The Wilcoxon Signed-Rank/Rank Sum tests were used to assess outcomes. Seventy per cent (14/20) of subjects reported pain in their hips yet only 15% (3/20) sought clinical evaluation. Cam morphology was present in 67.5% (27/40) of hips, while 22.5% (9/40) demonstrated pincer morphology. The prevalence of cam morphology in water polo players and synchronized swimmers is greater than that reported for the general population and at a similar level as some other sports. From a clinical perspective, acknowledgment of the high prevalence of cam morphology in water polo players and synchronized swimmers should be considered when these athletes present with hip pain.

The effect of wedge and tibial slope angles on knee contact pressure and kinematics following medial opening-wedge high tibial osteotomy.

BACKGROUND: High tibial osteotomy is a surgical procedure to treat medial compartment osteoarthritis in varus knees. The reported success rates of the procedure are inconsistent, which may be due to sagittal plane alignment of the osteotomy. The objective of this study was to determine the effect of changing tibial slope, for a range of tibial wedge angles in high tibial osteotomy, on knee joint contact pressure location and kinematics during continuous loaded flexion/extension. METHODS: Seven cadaveric knee specimens were cycled through flexion and extension in an Oxford knee-loading rig. The osteotomy on each specimen was adjusted to seven clinically relevant wedge and slope combinations. We used pressure sensors to determine the position of the centre of pressure in each compartment of the tibial plateau and infrared motion capture markers to determine tibiofemoral and patellofemoral kinematics. FINDINGS: In early knee flexion, a 5° increase in tibial slope shifted the centre of pressure in the medial compartment anteriorly by 4.5mm (P≤0.001), (from the neutral slope/wedge position). Increasing the tibial slope also resulted in the tibia translating anteriorly (P≤0.001). INTERPRETATION: Changes to the tibial slope during high tibial osteotomy for all tested wedge angles shifted the centre of pressure in both the medial and lateral compartments substantially and altered knee kinematics. Tibial slope should be controlled during high tibial osteotomy to prevent unwanted changes in tibial plateau contact loads.

Five-minute knee MRI for simultaneous morphometry and T2 relaxometry of cartilage and meniscus and for semiquantitative radiological assessment using double-echo in steady-state at 3T.

BACKGROUND: Biomarkers for assessing osteoarthritis activity necessitate multiple MRI sequences with long acquisition times. PURPOSE: To perform 5-minute simultaneous morphometry (thickness/volume measurements) and T2 relaxometry of both cartilage and meniscus, and semiquantitative MRI Osteoarthritis Knee Scoring (MOAKS). STUDY TYPE: Prospective. SUBJECTS: Fifteen healthy volunteers for morphometry and T2 measurements, and 15 patients (five each Kellgren-Lawrence grades 0/2/3) for MOAKS assessment. FIELD STRENGTH/SEQUENCE: A 5-minute double-echo steady-state (DESS) sequence was evaluated for generating quantitative and semiquantitative osteoarthritis biomarkers at 3T. ASSESSMENT: Flip angle simulations evaluated tissue signals and sensitivity of T2 measurements. Morphometry and T2 reproducibility was compared against morphometry-optimized and relaxometry-optimized sequences. Repeatability was assessed by scanning five volunteers twice. MOAKS reproducibility was compared to MOAKS derived from a clinical knee MRI protocol by two readers. STATISTICAL TESTS: Coefficients of variation (CVs), concordance confidence intervals (CCI), and Wilcoxon signed-rank tests compared morphometry and relaxometry measurements with their reference standards. DESS MOAKS positive percent agreement (PPA), negative percentage agreement (NPA), and interreader agreement was calculated using the clinical protocol as a reference. Biomarker variations between Kellgren-Lawrence groups were evaluated using Wilcoxon rank-sum tests. RESULTS: Cartilage thickness (P = 0.65), cartilage T2 (P = 0.69), and meniscus T2 (P = 0.06) did not significantly differ from their reference standard (with a 20° DESS flip angle). DESS slightly overestimated meniscus volume (P < 0.001). Accuracy and repeatability CVs were <3.3%, except the meniscus T2 accuracy (7.6%). DESS MOAKS had substantial interreader agreement and high PPA/NPA values of 87%/90%. Bone marrow lesions and menisci had slightly lower PPAs. Cartilage and meniscus T2 , and MOAKS (cartilage surface area, osteophytes, cysts, and total score) was higher in Kellgren-Lawrence groups 2 and 3 than group 0 (P < 0.05). DATA CONCLUSION: The 5-minute DESS sequence permits MOAKS assessment for a majority of tissues, along with repeatable and reproducible simultaneous cartilage and meniscus T2 relaxometry and morphometry measurements. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1328-1341.

Making Safe Surgery Affordable: Design of a Surgical Drill Cover System for Scale.

Many surgeons in low-resource settings do not have access to safe, affordable, or reliable surgical drilling tools. Surgeons often resort to nonsterile hardware drills because they are affordable, robust, and efficient, but they are impossible to sterilize using steam. A promising alternative is to use a Drill Cover system (a sterilizable fabric bag plus surgical chuck adapter) so that a nonsterile hardware drill can be used safely for surgical bone drilling. Our objective was to design a safe, effective, affordable Drill Cover system for scale in low-resource settings. We designed our device based on feedback from users at Mulago Hospital (Kampala, Uganda) and focused on 3 main aspects. First, the design included a sealed barrier between the surgical field and hardware drill that withstands pressurized fluid. Second, the selected hardware drill had a maximum speed of 1050 rpm to match common surgical drills and reduce risk of necrosis. Third, the fabric cover was optimized for ease of assembly while maintaining a sterile technique. Furthermore, with the Drill Cover approach, multiple Drill Covers can be provided with a single battery-powered drill in a "kit," so that the drill can be used in back-to-back surgeries without requiring immediate sterilization. The Drill Cover design presented here provides a proof-of-concept for a product that can be commercialized, produced at scale, and used in low-resource settings globally to improve access to safe surgery.