Threshold-based quantification of fatty degeneration in the supraspinatus muscle on MRI as an alternative method to Goutallier classification and single-voxel MR spectroscopy

Subscapularis impairment on magnetic resonance imaging is correlated with functional limitations in neonatal brachial plexus palsy

PURPOSE

The relationship between functional shoulder deficits in children with neonatal brachial plexus palsy (NBPP) and magnetic resonance imaging (MRI) shoulder abnormalities was evaluated.

METHODS

Shoulder function was assessed in 16 children (mean age: 5.8 years; range: 3-12 years) with NBPP based on shoulder rotator muscle strength, as measured using an isokinetic dynamometer and the modified Mallet score. The thickness and fatty infiltration of the subscapularis and infraspinatus muscles, and the morphology of the glenoid on MRI, were also determined.

RESULTS

The highest subscapularis fatty infiltration subgroup of NBPP patients promoted the highest alteration muscle thickness and modified Mallet score.

CONCLUSIONS

In NBPP children, subscapularis impairments play a major role in the functional limitations. This study of pediatric NBPP patients highlighted the value of adding an examination of the muscles to routine MRI assessment of bone parameters in the shoulders of NBPP children.

TRIAL REGISTRATION

NCT03440658.

Statin use and longitudinal changes in quantitative MRI-based biomarkers of thigh muscle quality: data from Osteoarthritis Initiative

OBJECTIVE

To assess whether changes in MRI-based measures of thigh muscle quality associated with statin use in participants with and without/at-risk of knee osteoarthritis.

METHODS

This retrospective cohort study used data from the Osteoarthritis Initiative study. Statin users and non-users were matched for relevant covariates using 1:1 propensity-score matching. Participants were further stratified according to baseline radiographic knee osteoarthritis status. We used a validated deep-learning method for thigh muscle MRI segmentation and calculation of muscle quality biomarkers at baseline, 2nd, and 4th visits. Mean difference and 95% confidence intervals (CI) in longitudinal 4-year measurements of muscle quality biomarkers, including cross-sectional area, intramuscular adipose tissue, contractile percent, and knee extensors and flexors maximum and specific contractile force (force/muscle area) were the outcomes of interest.

RESULTS

After matching, 3772 thighs of 1910 participants were included (1886 thighs of statin-users: 1886 of non-users; age: 62 ± 9 years (average ± standard deviation), range: 45-79; female/male: 1). During 4 years, statin use was associated with a slight decrease in muscle quality, indicated by decreased knee extension maximum (mean-difference, 95% CI: - 1.85 N/year, - 3.23 to - 0.47) and specific contractile force (- 0.04 N/cm2/year, - 0.07 to - 0.01), decreased thigh muscle contractile percent (- 0.03%/year, - 0.06 to - 0.01), and increased thigh intramuscular adipose tissue (3.06 mm2/year, 0.53 to 5.59). Stratified analyses showed decreased muscle quality only in participants without/at-risk of knee osteoarthritis but not those with established knee osteoarthritis.

CONCLUSIONS

Statin use is associated with a slight decrease in MRI-based measures of thigh muscle quality over 4 years. However, considering statins' substantial cardiovascular benefits, these slight muscle changes may be relatively less important in overall patient care.

Impact of Deltoid Computer Tomography Image Data on the Accuracy of Machine Learning Predictions of Clinical Outcomes after Anatomic and Reverse Total Shoulder Arthroplasty

Background: Despite the importance of the deltoid to shoulder biomechanics, very few studies have quantified the three-dimensional shape, size, or quality of the deltoid muscle, and no studies have correlated these measurements to clinical outcomes after anatomic (aTSA) and/or reverse (rTSA) total shoulder arthroplasty in any statistically/scientifically relevant manner. Methods: Preoperative computer tomography (CT) images from 1057 patients (585 female, 469 male; 799 primary rTSA and 258 primary aTSA) of a single platform shoulder arthroplasty prosthesis (Equinoxe; Exactech, Inc., Gainesville, FL) were analyzed in this study. A machine learning (ML) framework was used to segment the deltoid muscle for 1057 patients and quantify 15 different muscle characteristics, including volumetric (size, shape, etc.) and intensity-based Hounsfield (HU) measurements. These deltoid measurements were correlated to postoperative clinical outcomes and utilized as inputs to train/test ML algorithms used to predict postoperative outcomes at multiple postoperative timepoints (1 year, 2-3 years, and 3-5 years) for aTSA and rTSA. Results: Numerous deltoid muscle measurements were demonstrated to significantly vary with age, gender, prosthesis type, and CT image kernel; notably, normalized deltoid volume and deltoid fatty infiltration were demonstrated to be relevant to preoperative and postoperative clinical outcomes after aTSA and rTSA. Incorporating deltoid image data into the ML models improved clinical outcome prediction accuracy relative to ML algorithms without image data, particularly for the prediction of abduction and forward elevation after aTSA and rTSA. Analyzing ML feature importance facilitated rank-ordering of the deltoid image measurements relevant to aTSA and rTSA clinical outcomes. Specifically, we identified that deltoid shape flatness, normalized deltoid volume, deltoid voxel skewness, and deltoid shape sphericity were the most predictive image-based features used to predict clinical outcomes after aTSA and rTSA. Many of these deltoid measurements were found to be more predictive of aTSA and rTSA postoperative outcomes than patient demographic data, comorbidity data, and diagnosis data. Conclusions: While future work is required to further refine the ML models, which include additional shoulder muscles, like the rotator cuff, our results show promise that the developed ML framework can be used to evolve traditional CT-based preoperative planning software into an evidence-based ML clinical decision support tool.

Does the Fatty Infiltration Influence the Re-tear Rate and Functional Outcome After Rotator Cuff Repair? A Systematic Review and Meta-analysis

Purpose

Fatty infiltration (FI) of the rotator cuff muscles occurs after rotator cuff tears (RCTs), which may affect the outcome of the repair procedure. This study aimed to determine the relationship between preoperative FI and the rate of re-tear and functional outcomes after rotator cuff repair.

Methods

Computerized databases, including PubMed, EMBASE, Web of Science, and Cochrane Library database were searched for studies published from the inception date to January 2022. Two reviewers independently screened the titles and abstracts using prespecified criteria. Articles were included if they clearly stated the effect of varying degrees of FI on the outcome after shoulder cuff repair. Comparison was performed by different degrees of FI analysis: no FI is grade 0-1, FI is grade 2 and above. Statistical analysis was performed using Review Manager 5.4.1 software.

Results

A total of 16 articles involving 1383 patients from 8 countries were included. The follow-up period ranged from 8 to 121 months. In terms of re-tear rate: patients with preoperative FI had significantly higher rates of re-tear compared with patients without FI (OR 4.60, 95% CI 2.22-9.54, p < 0.0001), supraspinatus FI VS no FI (OR 2.06, 95% CI 1.00-4.24, p = 0.05), infraspinatus FI VS no FI (OR 2.42, 95% CI 1.19-4.91, p = 0.01). In terms of functional scoring: patients without FI had higher postoperative Constant-Murley (Constant) scores than those with FI (MD - 5.06, 95% CI - 9.40 to - 0.72, p = 0.02), there was no clear evidence that preoperative FI was related to postoperative American Society of shoulder and elbow physicians scores and the University of California at Los Angeles scores and range of motion.

Conclusion

FI after RCTs significantly increases the risk of postoperative re-tear and leads to worse functional scores, especially FI of the infraspinatus muscle. However, FI does not seem to reduce postoperative range of motion.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43465-022-00807-0.

Proton density fat fraction measurements of rotator cuff muscles: Accuracy, repeatability, and reproducibility across readers and scanners

PURPOSE

To determine the accuracy, repeatability, and reproducibility of magnetic resonance imaging-based proton density fat fraction (MRI-PDFF) measurements of rotator cuff muscles between two readers and three different scanners.

METHODS

Thirty-one volunteers underwent serial shoulder MRI examinations of both left and right sides on one 1.5-T MRI scanner and two 3.0-T MRI scanners. Two independent readers measured muscular PDFF of the supraspinatus, infraspinatus/teres minor muscle, and subscapularis. MR spectroscopy-based proton density fat fraction (MRS-PDFF) was regarded as the reference standard for assessing accuracy. A "coffee break" examination method was used to test the repeatability of each scanner. Bland-Altman plots, Pearson correlation, and linear regression analysis were used to assess bias and linearity. The Wilcoxon signed-rank test and Friedman test were applied to evaluate repeatability and reproducibility.

RESULTS

MRI-PDFF measurements indicated strong linearity (R² = 0.749) and small bias (-0.18%) in comparison with the MRS-PDFF measurements. A very strong positive Pearson correlation (r = 0.955-0.986) between the PDFF estimates of the two repeat scans indicated excellent repeatability. The PDFF measurements showed high reproducibility, with a strong positive Pearson correlation (r = 0.668-0.698) and a small mean bias (-0.04 to -0.10%) across different scanners.

CONCLUSION

MRI-PDFF measurements of rotator cuff muscles were highly accurate, repeatable, and reproducible across different readers and scanners, leading us to the conclusion that PDFF can be a reliable and robust quantitative imaging biomarker for longitudinal or multi-center studies.

Advantages of 3-dimensional Measurements for Supraspinatus Intramuscular Fatty Evaluation in Patients With Medium to Massive Rotator Cuff Tears: Comparison With a Single Sagittal Slice

BACKGROUND

Fatty infiltration of the rotator cuff muscles is highly related to poor outcomes after rotator cuff tears. Fat fraction (FF) based on traditional 2-dimensional measurements (2D-FF) from a single sagittal Y-view slice cannot determine intramuscular FF in the rotator cuff muscles; the newly developed 3-dimensional method (3D-FF) is supposed to precede 2D measurements for intramuscular FF evaluation in accuracy and reliability.

PURPOSE

(1) To measure 3D-FF and (2) to compare 3D-FF and 2D-FF in terms of quantitative values and intra- and interobserver agreement.

STUDY DESIGN

Cohort study (diagnosis); Level of evidence, 2.

METHODS

Six-point Dixon magnetic resonance imaging was performed in patients with full-thickness supraspinatus tears. 2D-FF was calculated on a single sagittal Y-view. Semiautomatic segmentation software (ITK-SNAP) was used to reconstruct 3D volumes of the supraspinatus muscle and fat. 3D-FF was obtained by dividing the fat volume by the total volume of the supraspinatus muscle. A paired t test was used to compare the individual differences between 2D-FF and 3D-FF results. Linear regression and Bland-Altman analyses were performed to determine the agreement between 2D-FF and 3D-FF. Intraclass correlation coefficients (ICCs) were calculated to determine intra- and interobserver agreement.

RESULTS

The 3D muscular and fatty models presented an inhomogeneous distribution of intramuscular fat in the supraspinatus, indicating the superiority of 3D-FF over 2D-FF in capturing all muscle morphologic information. 2D-FF was significantly higher than 3D-FF in the supraspinatus with large (19.5% ± 5.9% vs 16.2% ± 3.7%; P = .002) and massive (34.8% ± 13.3% vs 26.2% ± 9.4%; P < .001) rotator cuff tears. 2D-FF overestimated the FF compared with 3D-FF by >50% in 14.7% of all patients and by >15% in 67.6% of patients with large or massive RCTs. The discrepancy between 2D-FF and 3D-FF increased with increasing mean FF. The intra- and interobserver agreement of 3D-FF (ICCs, 0.89-0.99 and 0.89-0.95) was superior to that of 2D-FF (ICCs, 0.71-0.95 and 0.64-0.79).

CONCLUSION

3D-FF indicated an inhomogeneous distribution of intramuscular fat by capturing all muscle and fat morphologic information. In patients with large and massive rotator cuff tears, 2D-FF of the supraspinatus was significantly higher than 3D-FF. 3D-FF was more reliable than 2D-FF for estimating fatty infiltration in the supraspinatus, with better intra- and interobserver agreement.

Fatty degeneration of the rotator cuff: pathogenesis, clinical implications, and future treatment

Chronic rotator cuff pathology is often complicated by fatty degeneration of the rotator cuff (FDRC) muscles, an insidious process associated with poor prognosis with or without surgical intervention. Currently there is no treatment for FDRC, and many studies have described a natural course for this disease almost always resulting in further degeneration and morbidity. Recapitulating FDRC using animal injury models, and using imaging-based studies of human FDRC, the pathophysiology of this disease continues to be further characterized. Researchers studying mesenchymal stem cell-derived progenitor cells and known fibrogenic and adipogenic signaling pathways implicated in FDRC seek to clarify the underlying processes driving these changes. While new cell- and molecular-based therapies are being developed, currently the strongest available avenue for improved management of FDRC is the use of novel imaging techniques which allow for more accurate and personalized staging of fatty degeneration. This narrative review summarizes the evidence on the molecular and pathophysiologic mechanisms of FDRC and provides a clinical update on the diagnosis and management of this condition based on the existing knowledge. We also sought to examine the role of newer biologic therapies in the management of RC fatty degeneration and to identify areas of future research.

Deep-learning framework and computer assisted fatty infiltration analysis for the supraspinatus muscle in MRI

Occupation ratio and fatty infiltration are important parameters for evaluating patients with rotator cuff tears. We analyzed the occupation ratio using a deep-learning framework and studied the fatty infiltration of the supraspinatus muscle using an automated region-based Otsu thresholding technique. To calculate the amount of fatty infiltration of the supraspinatus muscle using an automated region-based Otsu thresholding technique. The mean Dice similarity coefficient, accuracy, sensitivity, specificity, and relative area difference for the segmented lesion, measuring the similarity of clinician assessment and that of a deep neural network, were 0.97, 99.84, 96.89, 99.92, and 0.07, respectively, for the supraspinatus fossa and 0.94, 99.89, 93.34, 99.95, and 2.03, respectively, for the supraspinatus muscle. The fatty infiltration measure using the Otsu thresholding method significantly differed among the Goutallier grades (Grade 0; 0.06, Grade 1; 4.68, Grade 2; 20.10, Grade 3; 42.86, Grade 4; 55.79, p < 0.0001). The occupation ratio and fatty infiltration using Otsu thresholding demonstrated a moderate negative correlation (ρ = - 0.75, p < 0.0001). This study included 240 randomly selected patients who underwent shoulder magnetic resonance imaging (MRI) from January 2015 to December 2016. We used a fully convolutional deep-learning algorithm to quantitatively detect the fossa and muscle regions by measuring the occupation ratio of the supraspinatus muscle. Fatty infiltration was objectively evaluated using the Otsu thresholding method. The proposed convolutional neural network exhibited fast and accurate segmentation of the supraspinatus muscle and fossa from shoulder MRI, allowing automatic calculation of the occupation ratio. Quantitative evaluation using a modified Otsu thresholding method can be used to calculate the proportion of fatty infiltration in the supraspinatus muscle. We expect that this will improve the efficiency and objectivity of diagnoses by quantifying the index used for shoulder MRI.