The Role of Artificial Intelligence in the Identification and Evaluation of Bone Fractures.

Artificial intelligence (AI), particularly deep learning, has made enormous strides in medical imaging analysis. In the field of musculoskeletal radiology, deep-learning models are actively being developed for the identification and evaluation of bone fractures. These methods provide numerous benefits to radiologists such as increased diagnostic accuracy and efficiency while also achieving standalone performances comparable or superior to clinician readers. Various algorithms are already commercially available for integration into clinical workflows, with the potential to improve healthcare delivery and shape the future practice of radiology. In this systematic review, we explore the performance of current AI methods in the identification and evaluation of fractures, particularly those in the ankle, wrist, hip, and ribs. We also discuss current commercially available products for fracture detection and provide an overview of the current limitations of this technology and future directions of the field.

A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation.

Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with applications in disease diagnostics, intervention, and treatment planning. Accurate MRI segmentation is critical for diagnosing abnormalities, monitoring diseases, and deciding on a course of treatment. With the advent of advanced deep learning frameworks, fully automated and accurate MRI segmentation is advancing. Traditional supervised deep learning techniques have advanced tremendously, reaching clinical-level accuracy in the field of segmentation. However, these algorithms still require a large amount of annotated data, which is oftentimes unavailable or impractical. One way to circumvent this issue is to utilize algorithms that exploit a limited amount of labeled data. This paper aims to review such state-of-the-art algorithms that use a limited number of annotated samples. We explain the fundamental principles of self-supervised learning, generative models, few-shot learning, and semi-supervised learning and summarize their applications in cardiac, abdomen, and brain MRI segmentation. Throughout this review, we highlight algorithms that can be employed based on the quantity of annotated data available. We also present a comprehensive list of notable publicly available MRI segmentation datasets. To conclude, we discuss possible future directions of the field-including emerging algorithms, such as contrastive language-image pretraining, and potential combinations across the methods discussed-that can further increase the efficacy of image segmentation with limited labels.

Interstitial lung disease diagnosis and prognosis using an AI system integrating longitudinal data.

For accurate diagnosis of interstitial lung disease (ILD), a consensus of radiologic, pathological, and clinical findings is vital. Management of ILD also requires thorough follow-up with computed tomography (CT) studies and lung function tests to assess disease progression, severity, and response to treatment. However, accurate classification of ILD subtypes can be challenging, especially for those not accustomed to reading chest CTs regularly. Dynamic models to predict patient survival rates based on longitudinal data are challenging to create due to disease complexity, variation, and irregular visit intervals. Here, we utilize RadImageNet pretrained models to diagnose five types of ILD with multimodal data and a transformer model to determine a patient's 3-year survival rate. When clinical history and associated CT scans are available, the proposed deep learning system can help clinicians diagnose and classify ILD patients and, importantly, dynamically predict disease progression and prognosis.

Muscle recovery after total hip arthroplasty: prospective MRI comparison of anterior and posterior approaches.

INTRODUCTION: The direct anterior approach (DAA) and the posterior approach (PA) are 2 common total hip arthroplasty (THA) exposures. This prospective study quantitatively compared changes in periarticular muscle volume after DAA and PA THA. MATERIALS: 19 patients undergoing THA were recruited prospectively from the practices of 3 fellowship-trained hip surgeons. Each surgeon performed a single approach, DAA or PA. Enrolled patients underwent a preoperative MRI of the affected hip and two subsequent postoperative MRIs at around 6 weeks and 6 months after surgery. Clinical evaluations were done by Harris Hip Score at each follow-up interval. RESULTS: MRIs or 10 DAA and 9 PA patients were analysed. Groups did not differ significantly with regard to BMI, age, or preoperative muscle volume. 1 DAA patient suffered a periprosthetic fracture and was excluded from the study. DAA hips showed significant atrophy in the obturator internus (-37.3%) muscle at early follow-up, with persistent atrophy of this muscle at the final follow-up. PA hips showed significant atrophy in the obturator internus (-46.8%) and externus (-16.0%), piriformis (-8.12%), and quadratus femoris muscles (-13.1%) at early follow-up, with persistent atrophy of these muscles at final follow-up. Loss of anterior capsular integrity was present at final follow-up in 2/10 DAA hips while loss of posterior capsular integrity was present in 5/9 PA hips. There was no difference in clinical outcomes. DISCUSSION: This study demonstrates that DAA showed less persistent muscular atrophy than PA. Regardless of surgical approach, a muscle whose tendon is detached from its insertion is likely to demonstrate persistent atrophy 6 months following THA. Although the study was not powered to compare clinical outcomes, it should be noted that no significant difference in patient outcomes was observed.

RadImageNet: An Open Radiologic Deep Learning Research Dataset for Effective Transfer Learning.

Purpose: To demonstrate the value of pretraining with millions of radiologic images compared with ImageNet photographic images on downstream medical applications when using transfer learning. Materials and Methods: This retrospective study included patients who underwent a radiologic study between 2005 and 2020 at an outpatient imaging facility. Key images and associated labels from the studies were retrospectively extracted from the original study interpretation. These images were used for RadImageNet model training with random weight initiation. The RadImageNet models were compared with ImageNet models using the area under the receiver operating characteristic curve (AUC) for eight classification tasks and using Dice scores for two segmentation problems. Results: The RadImageNet database consists of 1.35 million annotated medical images in 131 872 patients who underwent CT, MRI, and US for musculoskeletal, neurologic, oncologic, gastrointestinal, endocrine, abdominal, and pulmonary pathologic conditions. For transfer learning tasks on small datasets-thyroid nodules (US), breast masses (US), anterior cruciate ligament injuries (MRI), and meniscal tears (MRI)-the RadImageNet models demonstrated a significant advantage (P < .001) to ImageNet models (9.4%, 4.0%, 4.8%, and 4.5% AUC improvements, respectively). For larger datasets-pneumonia (chest radiography), COVID-19 (CT), SARS-CoV-2 (CT), and intracranial hemorrhage (CT)-the RadImageNet models also illustrated improved AUC (P < .001) by 1.9%, 6.1%, 1.7%, and 0.9%, respectively. Additionally, lesion localizations of the RadImageNet models were improved by 64.6% and 16.4% on thyroid and breast US datasets, respectively. Conclusion: RadImageNet pretrained models demonstrated better interpretability compared with ImageNet models, especially for smaller radiologic datasets.Keywords: CT, MR Imaging, US, Head/Neck, Thorax, Brain/Brain Stem, Evidence-based Medicine, Computer Applications-General (Informatics) Supplemental material is available for this article. Published under a CC BY 4.0 license.See also the commentary by Cadrin-Chênevert in this issue.

Use of Extracellular Matrix Cartilage Allograft May Improve Infill of the Defects in Bone Marrow Stimulation for Osteochondral Lesions of the Talus.

PURPOSE: To evaluate the effectiveness of extracellular matrix cartilage allograft (EMCA) as an adjuvant to bone marrow stimulation (BMS) compared with BMS alone in the treatment of osteochondral lesions of the talus. METHODS: A retrospective cohort study comparing patients treated with BMS with EMCA (BMS-EMCA group) and BMS alone (BMS group) between 2013 and 2019 was undertaken. Clinical outcomes were evaluated with the Foot and Ankle Outcome Score (FAOS) preoperatively and postoperatively. Postoperative magnetic resonance imaging (MRI) scans were evaluated using the modified Magnetic Resonance Observation of Cartilage Repair Tissue score. Comparisons between groups were made with the Mann-Whitney U test for continuous variables and the Fisher exact test for categorical variables. RESULTS: Twenty-four patients underwent BMS with EMCA (BMS-EMCA group), and 24 patients underwent BMS alone (BMS group). The mean age was 40.8 years (range, 19-60 years) in the BMS-EMCA group and 47.8 years (range, 24-60 years) in the BMS group (P = .060). The mean follow-up time was 20.0 months (range, 12-36 months) in the BMS-EMCA group and 26.9 months (range, 12-55 months) in the BMS group (P = .031). Both groups showed significant improvements in all FAOS subscales. No significant differences between groups were found in all postoperative FAOS values. The mean Magnetic Resonance Observation of Cartilage Repair Tissue score in the BMS-EMCA group was higher (76.3 vs 66.3) but not statistically significant (P = .176). The MRI analysis showed that 87.5% of the BMS-EMCA patients had complete infill of the defect with repair tissue; however, fewer than half of the BMS patients (46.5%) had complete infill (P = .015). CONCLUSIONS: BMS with EMCA is an effective treatment strategy for osteochondral lesions of the talus and provides better cartilage infill in the defect on MRI. However, this did not translate to improved functional outcomes compared with BMS alone in the short term. Additionally, according to analysis of the minimal clinically important difference, there was no significant difference in clinical function scoring between the 2 groups postoperatively. LEVEL OF EVIDENCE: Level III, retrospective comparative study.

Artificial intelligence-enabled rapid diagnosis of COVID-19 patients.

For diagnosis of COVID-19, a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to two days to complete, serial testing may be required to rule out the possibility of false negative results, and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of COVID-19 patients. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiologic findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history, and laboratory testing to rapidly diagnose COVID-19 positive patients. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an AUC of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of RT-PCR positive COVID-19 patients who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.

Artificial intelligence-enabled rapid diagnosis of patients with COVID-19.

For diagnosis of coronavirus disease 2019 (COVID-19), a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to 2 d to complete, serial testing may be required to rule out the possibility of false negative results and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of patients with COVID-19. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiological findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history and laboratory testing to rapidly diagnose patients who are positive for COVID-19. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an area under the curve of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of patients who were positive for COVID-19 via RT-PCR who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.

Deep neural networks could differentiate Bethesda class III versus class IV/V/VI.

BACKGROUND: Ultrasound (US) is the most commonly used radiologic modality to identify and characterize thyroid nodules. Many nodules subsequently undergo fine needle aspiration to further characterize the nodule and determine appropriate treatment. The fine needle aspirate is most commonly classified using the Bethesda System for Reporting Thyroid Cytology (TBSRTC). It can sometimes be difficult to differentiate Bethesda class III lesions (atypia of undetermined significance/follicular lesion of undetermined significance) from Bethesda class IV, V and VI (malignant nodules). However, differentiation is important as clinical management differs between the two groups. The purpose of this study was to introduce machine learning methods to help radiologists differentiate Bethesda class III from Bethesda class VI, V and VI lesions. METHODS: The authors collected 467 thyroid nodules with cytopathology results. US features were summarized using the 2017 ACR (American College of Radiology) Thyroid Imaging Reporting And Data System (TIRADS). Machine learning models [logistic regression, gradient boost, support vector machine (SVM), random forest and deep neural networks (DNN)] were created to classify Bethesda class III vs class IV/V/VI. RESULTS: DNN outperformed other machine learning classifiers and obtained the highest accuracy and specificity to classify thyroid nodules as either Bethesda III or IV/V/VI nodules using multiple US features. CONCLUSIONS: Machine learning/deep learning approaches could help differentiate Bethesda III nodules from IV/V/VI using US features which may benefit treatment decisions.

Concentrated Bone Marrow Aspirate May Decrease Postoperative Cyst Occurrence Rate in Autologous Osteochondral Transplantation for Osteochondral Lesions of the Talus.

PURPOSE: To clarify if the use of concentrated bone marrow aspirate (CBMA) would affect both postoperative functional outcomes and magnetic resonance imaging (MRI) outcomes compared with those of autologous osteochondral transplantation (AOT) alone; in addition, to assess the efficacy of CBMA reducing the presence of postoperative cyst formation following AOT in the treatment of osteochondral lesions of the talus. METHODS: Fifty-four (92%) of 59 eligible patients who underwent AOT between 2004 and 2008 were retrospectively assessed at a minimum of 5-year follow-up. Twenty-eight patients were treated with AOT and CBMA (AOT/CBMA group) and 26 patients were treated with AOT alone (AOT-alone group). Clinical outcomes were evaluated using the Foot and Ankle Outcome Scores (FAOS) and Short-Form 12 (SF-12) preoperatively and at final follow-up. Postoperative MRI was evaluated with the modified Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) scoring system. Cyst formation was also evaluated on postoperative MRI. RESULTS: The mean FAOS and SF-12 significantly improved in both the AOT/CBMA and AOT-alone groups, but there were no statistical differences between groups in FAOS (80.5 vs 75.5, P = .225) and SF-12 (71.1 vs 69.6, P = .756) at final follow-up. Additionally, there was no difference in the mean MOCART score (80.4 vs 84.3, P = .484); however, AOT/CBMA did result in a statistically lower rate of cyst formation (46.4% vs 76.9%, P = .022). No significant differences were found in the mean postoperative FAOS and SF-12 between patients with and without cysts postoperatively. CONCLUSIONS: CBMA reduced postoperative cyst occurrence rate in patients treated with AOT; however, CBMA did not result in significant differences in medium term functional outcomes and MOCART score in patients who underwent AOT. LEVEL OF EVIDENCE: Level III, retrospective comparative trial.

Allograft Compared with Autograft in Osteochondral Transplantation for the Treatment of Osteochondral Lesions of the Talus.

BACKGROUND: There is a paucity of clinical studies that compare the efficacy of autograft and allograft in osteochondral transplantation for treatment of osteochondral lesions of the talus (OLT). The purpose of the present study was to compare the clinical and radiographic outcomes following osteochondral transplantation with autograft or allograft for OLT. METHODS: A retrospective analysis comparing patients treated with autograft or allograft for OLT was performed. Clinical outcomes were evaluated with use of the Foot and Ankle Outcome Score (FAOS) and the Short Form-12 (SF-12) score. Magnetic resonance imaging (MRI) was evaluated with use of the Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) score. The rates of cyst occurrence, graft degradation, graft failure, and revision surgeries were also evaluated. RESULTS: Twenty-five nonrandomized patients with autograft and 16 with allograft were included, with a mean follow-up of 26 months in the autograft group and 22 months in the allograft group. There were no significant differences among all demographic variables between the autograft and allograft groups. The mean postoperative FAOS was significantly higher in the autograft group (81.9; 95% confidence interval [CI]: 78.6 to 85.2) than in the allograft group (70.1; 95% CI: 63.7 to 76.5; p = 0.006). Similarly, the mean postoperative SF-12 scores were significantly higher in the autograft group (74.7; 95% CI: 71.0 to 78.4) than in the allograft group (66.1; 95% CI: 61.2 to 71.0; p = 0.021). MOCART scores were significantly better in the autograft group (87.1) than in the allograft group (75.5; p = 0.005). The rate of chondral wear on MRI was higher in the allograft group (53%) than in the autograft group (4%; p < 0.001). Cyst formation in the graft itself was more likely to occur in the allograft group (47%) than in the autograft group (8%; p = 0.017). The rate of secondary procedures for the graft was higher in the allograft group (25%) than in the autograft group (0%; p = 0.009). CONCLUSIONS: In this small nonrandomized cohort study, the procedures performed with use of an autograft provided better clinical and MRI outcomes than the allograft procedures. The rate of chondral wear on MRI was higher with allograft than with autograft, and allograft-treated patients had a higher rate of clinical failure. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Incidence of Coexisting Talar and Tibial Osteochondral Lesions Correlates With Patient Age and Lesion Location.

BACKGROUND: The incidence of coexisting osteochondral lesions (OCLs) of the tibia and talus has been negatively correlated with successful clinical outcomes, yet these lesions have not been extensively characterized. PURPOSE: To determine the incidence of coexisting tibial and talar OCLs, assess the morphologic characteristics of these lesions, and evaluate whether these characteristics are predictive of outcome. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: A total of 83 patients who underwent surgery for a talar OCL were evaluated for coexisting OCLs of the distal tibia with preoperative magnetic resonance images. Size, location, containment, International Cartilage Repair Society (ICRS) grade, patient age, and patient sex were analyzed for predictors of coexisting lesions or patient outcome. The talar and tibial surfaces were each divided into 9 zones, with 1 corresponding to the most anteromedial region and proceeding laterally and then posteriorly. The Foot and Ankle Outcome Score (FAOS) was evaluated pre- and postoperatively. RESULTS: Twenty-six patients (31%) had coexisting tibial and talar OCLs, with 9 (35%) identified as kissing lesions. Age correlated with coexisting lesion incidence, as older patients were more likely to have a coexisting tibial OCL (P = .038). More than half of talar OCLs were found in zone 4 (61%), whereas the majority of tibial OCLs were located in zones 2, 4, and 5 (19% each). Patients with coexisting lesions were more likely to have a lateral talar OCL (P = .028), while those without a coexisting tibial lesion were more likely to have a talar OCL in zone 4 (P = .016). There was no difference in FAOS result or lesion size between patients with and without coexisting OCLs, but patients with coexisting lesions were more likely to have an ICRS grade 4 talar OCL (P = .034). For patients with coexisting lesions, kissing lesions were more likely to be located in zone 6 (P = .043). There was no difference in OCL size or containment between kissing and nonkissing coexisting OCLs. CONCLUSION: The incidence of coexisting talar and tibial OCLs may be more prevalent than what previous reports have suggested, with older patients being more likely to present with this pathology. The location of a talar OCL correlates with the incidence of a coexisting tibial OCL.

The Presence and Degree of Bone Marrow Edema Influence Midterm Clinical Outcomes After Microfracture for Osteochondral Lesions of the Talus.

BACKGROUND: Subchondral bone marrow edema (BME) has been associated with articular cartilage loss, with the potential to be a negative prognostic indicator for clinical outcomes after microfracture. However, no single study has investigated the association between BME and clinical outcomes after microfracture for osteochondral lesions of the talus (OLTs) at midterm follow-up. PURPOSE: To clarify the association between postoperative subchondral BME and clinical outcomes in patients treated with microfracture for OLTs at both short-term and midterm follow-up using a grading system that classified the extent of BME of the talus. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Patients who underwent microfracture between 2008 and 2013 were assessed at 2- and 4-year postoperative follow-up. BME was evaluated using magnetic resonance imaging, and the presence of subchondral BME was determined with fat-suppressed T2-weighted sequences. Clinical outcomes were evaluated using the Foot and Ankle Outcome Score (FAOS). P < .05 was considered to be statistically significant. RESULTS: Forty-three (83%) of 52 eligible patients were included. No significant differences were found in the FAOS between the BME and no BME groups at 2-year follow-up (83.1 ± 6.5 vs 88.6 ± 8.0, respectively; P = .109), but there was a significant difference at 4-year follow-up (77.5 ± 11.1 vs 84.7 ± 8.4, respectively; P = .041). A significant difference was found among BME grades at 4-year follow-up (grade 0: 84.7 ± 7.4, grade 1: 80.1 ± 10.5, grade 2: 74.0 ± 10.3, and grade 3: 67.5 ± 7.1; P = .035). A post hoc analysis showed significant differences between grades 0 and 2, 0 and 3, and 1 and 3 ( P = .041, .037, and .048, respectively). In addition, at 4-year follow-up, a significant correlation was noted between the FAOS and BME grade ( r = -0.453, P = .003) but not at 2-year follow-up ( r = -0.212, P = .178). Seventy-four percent of patients still had subchondral BME at 4-year follow-up after microfracture for OLTs. CONCLUSION: Patients with subchondral BME at midterm follow-up after microfracture for OLTs had worse clinical outcomes than those without subchondral BME. In addition, the degree of subchondral BME at midterm follow-up was correlated with clinical outcomes. However, at short-term follow-up, there were no significant differences in clinical outcomes based on both the presence and degree of BME, and no correlation was found between clinical outcomes and the degree of BME. The current study suggests that BME at short-term follow-up is a normal physiological reaction. However, BME at midterm follow-up after microfracture for OLTs may be pathological and is associated with poorer clinical outcomes.

Effect of the Containment Type on Clinical Outcomes in Osteochondral Lesions of the Talus Treated With Autologous Osteochondral Transplantation.

BACKGROUND: Uncontained-type osteochondral lesions of the talus (OLTs) have been shown to have inferior clinical outcomes after treatment with bone marrow stimulation. While autologous osteochondral transplantation (AOT) is indicated for larger lesions, no study has reported on the prognostic significance of the containment of OLTs treated with the AOT procedure. PURPOSE: To clarify the effect of the containment of OLTs on clinical and radiological outcomes in patients who underwent AOT for OLTs. STUDY DESIGN: Case control study; Level of evidence, 3. METHODS: A retrospective cohort study comparing patients with contained-type and uncontained-type OLTs was undertaken to include all patients who underwent AOT for the treatment of OLTs between 2006 and 2014. Analyses were performed by grouping the patients according to the containment type. Clinical outcomes were evaluated using the Foot and Ankle Outcome Score (FAOS) and the 12-Item Short Form Health Survey (SF-12) preoperatively and at final follow-up. Magnetic resonance imaging (MRI) at 2 years' follow-up was evaluated with the modified magnetic resonance observation of cartilage repair tissue (MOCART) score. Multivariate regression models were used to evaluate factors affecting postoperative FAOS, SF-12, and MOCART scores. RESULTS: Ninety-four patients were included: 31 patients with a contained-type OLT and 63 patients with an uncontained-type OLT. The median patient age was 34 years (interquartile range [IQR], 28-48 years) in the contained-type group and 36 years (IQR, 27-46 years) in the uncontained-type group. The median follow-up time was 45 months (IQR, 38-63 months) in the contained-type group and 52 months (IQR, 40-66 months) in the uncontained-type group. The median FAOS and SF-12 scores improved significantly after surgery in both contained-type and uncontained-type lesions ( P < .001). The median postoperative FAOS score of patients with contained-type OLTs was higher than that of patients with uncontained-type OLTs (91.7 vs 85.0, respectively; P = .009), but no significant differences were found between the contained-type and uncontained-type groups for postoperative SF-12 and MOCART scores. The multivariate regression models showed that patients with contained-type OLTs had an approximately 10-point better score on the FAOS compared with patients with uncontained-type OLTs ( P = .006). There was a nonsignificant trend for the rate of cystic occurrence in uncontained-type OLTs to be higher than that of contained-type OLTs (55.6% vs 38.7%, respectively; P = .125). CONCLUSION: Patients with contained-type OLTs experienced better clinical outcomes than those with uncontained-type OLTs after AOT for the treatment of OLTs. However, the AOT procedure still provided good clinical and MRI outcomes in both contained-type and uncontained-type OLTs at midterm follow-up.

Predicting malignancy of pulmonary ground-glass nodules and their invasiveness by random forest.

BACKGROUND: The purpose of this study was to develop a predictive model that could accurately predict the malignancy of the pulmonary ground-glass nodules (GGNs) and the invasiveness of the malignant GGNs. METHODS: The authors built two binary classification models that could predict the malignancy of the pulmonary GGNs and the invasiveness of the malignant GGNs. RESULTS: Results of our developed model showed random forest could achieve 95.1% accuracy to predict the malignancy of GGNs and 83.0% accuracy to predict the invasiveness of the malignant GGNs. CONCLUSIONS: The malignancy and invasiveness of pulmonary GGNs could be predicted by random forest.

Subchondral Bone Degradation After Microfracture for Osteochondral Lesions of the Talus: An MRI Analysis.

BACKGROUND: Microfracture is the most common cartilage-reparative procedure for the treatment of osteochondral lesions of the talus (OLTs). Damage to the subchondral bone (SCB) during microfracture may irreversibly change the joint-loading support of the ankle, leading to reparative fibrocartilage degradation over time. PURPOSE: To investigate the morphological change in the SCB after microfracture for OLT by developing a novel magnetic resonance imaging (MRI) scoring system specifically for evaluating the SCB. Furthermore, this study assesses the influence of the morphological changes of the SCB on clinical outcomes based on the new score. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: Forty-two patients who underwent microfracture for OLT were included. An SCB Health (SCBH) scoring system was developed according to the amount of edema, subchondral cyst diameter, and qualitative and thickness change in the SCB, with a total score of 12 indicating normal SCB. MRI was obtained postoperatively from 6 months to 1 year, 1 to 2 years, 2 to 4 years, and 4 to 6 years. The Foot and Ankle Outcome Score (FAOS) was evaluated preoperatively and at 2 years and final follow-up. RESULTS: The mean patient age was 38.4 ± 15.6 years, with a mean follow-up of 51.7 ± 22.8 months. The mean FAOS improved significantly from 57.8 ± 14.4 preoperatively to 84.3 ± 7.2 at 24 months ( P < .001) and decreased to a final mean value of 77.1 ± 12.6 ( P < .001). The mean SCBH score decreased from 8.6 ± 1.9 preoperatively to 7.1 ± 1.8 on the first follow-up MRI ( P < .001) and significantly decreased to 5.9 ± 2.3 on the fourth follow-up MRI ( P < .001). Subchondral cysts were noticeably worse at the fourth follow-up MRI than at the first and second ( P < .001, P = .006, respectively). There was a positive correlation between the final FAOS and the SCBH score on the third and fourth follow-up MRI ( r = 0.55, P < .001; r = 0.70, P < .001, respectively), but no correlation was found on the first and second follow-up. CONCLUSION: The SCBs following microfracture for OLT were not restored at midterm follow-up. There was a significant decrease of the overall SCBH score over time. Noticeably, subchondral cysts deteriorated over time consistently. In addition, the SCBH score at midterm follow-up was positively correlated with clinical outcomes. Lasting morphological changes in the SCB may be indicative of longer-term failure of the microfracture procedure.

Magnetic Resonance Imaging Evidence of Postoperative Cyst Formation Does Not Appear to Affect Clinical Outcomes After Autologous Osteochondral Transplantation of the Talus.

PURPOSE: To identify potential cysts using magnetic resonance imaging (MRI) after autologous osteochondral transplantation (AOT) for osteochondral lesions of the talus (OLTs) as well as to determine the effect of cysts on short-term clinical outcomes. METHODS: Eighty-nine MRI scans of 37 patients who had AOT for an OLT were evaluated. Radiographic variables examined included cyst presence, cyst location, bone edema, and cartilage integrity. Patient clinical variables recorded and examined for association with the presence of a cyst included gender, age, preoperative lesion size, size and number of osteochondral graft used, symptoms reported, and pre- and postoperative Foot and Ankle Outcome Score (FAOS) and Short Form-12 (SF-12) scores measured at final follow-up. RESULTS: Twenty-four patients (64.8%) had MRI evidence of cystic change after AOT for an OLT at a mean MRI follow-up time of 15 months after surgery (range 2-54). Patients with presence of a cyst after surgery were older (mean age, 42.7 years) than those without cysts (mean age, 32.7 years) (P = .041), and among patients with a cyst, older patients more often had involvement of the subchondral plate (57.3 v 36.7 years) (P < .001). No other variables associated with cyst formation had statistical significance. Mean patient FAOS scores increased from 50 (±19) preoperatively to 87 (±8) postoperatively. Mean SF-12 scores increased from 52 (±18) preoperatively to 85 (±6) postoperatively. Patients not identified as having a cyst had lower SF-12 (P = .028) and FAOS (P = .032) preoperative scores and more improvement in SF-12 (P = .006) and FAOS (P = .016) scores than patients with cysts. CONCLUSIONS: Postoperative cyst formation on MRI was found to be a common occurrence after AOT for OLT. Although increasing age was related to increased cyst prevalence, the clinical impact of cyst formation was not found to be significant at short-term follow-up. Continued long-term longitudinal follow-up of postoperative cysts is needed. LEVEL OF EVIDENCE: Level IV, prognostic case series.

Clinical and MRI Donor Site Outcomes Following Autologous Osteochondral Transplantation for Talar Osteochondral Lesions.

BACKGROUND: Autologous osteochondral transplantation (AOT) has an inherent risk of donor site morbidity (DSM). The reported rates of DSM vary from 0% to 50%, with few studies reporting clinical or imaging outcomes at the donor site as a primary outcome and even fewer report these outcomes when a biosynthetic plug backfill is employed. Although TruFit (Smith & Nephew, Andover, MA) plugs have been removed from the market for regulatory purposes, biphasic plugs (including TruFit plugs) have been used for several years and the evaluation of these is therefore pertinent. METHODS: Thirty-nine patients who underwent forty AOT procedures of the talus, with the donor graft being taken from the ipsilateral knee, were included. Postoperative magnetic resonance imaging (MRI) was used to assess the donor site graded with magnetic resonance observation of cartilage repair tissue (MOCART) scoring. Lysholm scores were collected preoperatively, at the time of magnetic resonance imaging (MRI), and again at 24 months and at final follow-up to assess clinical outcomes. Statistical analysis was performed to establish if there was any correlation between MRI assessment of the donor site and clinical outcomes. The mean patient age was 36.2 ± 15.7 years with a mean follow-up of 41.8 ± 16.7 months. RESULTS: All patient donor site defects were filled with OBI TruFit biphasic plugs. DSM was encountered in 12.5% of the patient cohort at 24 months, and in these patients, the Lysholm score was a mean 87.2 ± 5.0. At final follow-up, DSM was reduced to 5%. Lysholm scores for the entire cohort were 98.4 ± 4.6 and 99.4 ± 3.1 at 24 months and final follow-up, respectively. MRI of the donor sites were taken at an average of 18.1 ± 13.5 (range, 3-48) months postoperatively and the mean MOCART score was 60.0 ± 13.5. No correlation was found between the MOCART score and Lysholm outcomes at the donor knee (P = .43, r = 0.13). CONCLUSION: Low incidence of DSM and good functional outcomes were achieved with AOT. Additionally, MRI findings did not predict clinical outcomes in our study. LEVEL OF EVIDENCE: Level IV, retrospective case series.

Autologous Osteochondral Transplantation for Osteochondral Lesions of the Talus: Does Previous Bone Marrow Stimulation Negatively Affect Clinical Outcome?

PURPOSE: To determine if functional outcomes and magnetic resonance imaging (MRI) outcomes were significantly different between patients receiving primary autologous osteochondral transplantation (AOT) and patients receiving secondary AOT surgery after failed microfracture. METHODS: A group of 76 patients enrolled into the Foot and Ankle Service between 2006 and 2012 was retrospectively analyzed. Patient-reported outcomes were evaluated in 76 patients using the Foot and Ankle Outcome Score (FAOS). Superficial and deep tissues at the repaired defect site, as well as the adjacent normal cartilage, were analyzed using quantitative T2 mapping MRI. Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) allowed for morphological evaluation of the repair tissue. The mean clinical follow-up time was 51 ± 23 months (range, 12 to 97 months), and the mean MRI follow-up time was 26 months (range, 24 to 36 months). RESULTS: Twenty-two patients received primary AOT and 54 received secondary AOT after failed microfracture. Patient characteristics between groups were similar with regard to age, gender, lesion size, and follow-up time. The mean postoperative FAOS was 10 points higher in the primary AOT group (83.2 ± 17.0) compared with the secondary AOT group (72.4 ± 19.4) (P = .01). Regression analysis showed that secondary AOT patients preoperative to postoperative change in FAOS was 9 points lower than in primary AOT patients after adjustment for age, preoperative FAOS, and lesion size (P = .045). The mean MOCART score, superficial T2 and deep T2 values, and the difference between normal and repair cartilage T2 values were not significantly different between groups. Lesion size was negatively correlated with MOCART scores (ρ = -0.2, P = .04), but positively correlated with difference in T2 values between repair and adjacent normal cartilage in the superficial layer (ρ = 0.3, P = .045). CONCLUSIONS: Primary AOT shows better functional outcomes compared with secondary AOT after failed microfracture in patients with similar characteristics and lesion size. No significant differences in T2 mapping relaxation times and MOCART scores were identified. LEVEL OF EVIDENCE: Level III, case control study.