Arthroscopic single-bundle anterior cruciate ligament reconstruction with six-strand hamstring tendon allograft versus bone-patellar tendon-bone allograft.

PURPOSE: The aim of this study was to compare the clinical outcomes of arthroscopic single-bundle anterior cruciate ligament (ACL) reconstruction with six-strand hamstring tendon (HT) allograft versus bone-patellar tendon-bone (BPTB) allograft. METHODS: The prospective randomized controlled trial was included 129 patients. Sixty-nine patients received reconstruction with six-strand HT allografts (HT group), whereas 60 patients with BPTB allografts (BPTB group). Outcome assessment included re-rupture findings, International Knee Documentation Committee (IKDC) scores, Lysholm scores, KT-1000 arthrometer, Lachman test, pivot-shift test, range of motion (ROM) and single-leg hop test. RESULTS: At a mean follow-up of 52 months, 113 patients (HT group, 61 patients; BPTB group, 52 patients) completed a minimum 4-year follow-up. Four patients in HT group and six in BPTB group experienced ACL re-rupture (6.2 vs. 10.3 %) and received revision surgery. Significant between-group differences were observed in KT-1000 outcomes and pivot-shift test 1 (1.2 ± 1.5 vs. 1.8 ± 1.3, p = 0.025; positive rate 6.5 vs. 18.9 %, p = 0.036), 2 (1.1 ± 1.4 vs. 1.6 ± 1.2, p = 0.044; 8.1 vs. 20.7 %, p = 0.039), 4 (1.1 ± 1.5 vs. 1.7 ± 1.4, p = 0.031; 9.7 vs. 25 %, p = 0.012) years postoperatively. The outcomes between the two groups were comparable in terms of IKDC scores, Lysholm scores, Lachman test, ROM and single-leg hop test. CONCLUSIONS: Six-strand HT allograft achieved superior anteroposterior and rotational stability after single-bundle ACL reconstruction. It is a reasonable graft substitute for ACL reconstruction. LEVEL OF EVIDENCE: II.

Femoral trochlear groove development after patellar subluxation and early reduction in growing rabbits.

PURPOSE: This animal study aimed to investigate whether early reduction in patellar subluxation could minimize femoral trochlear dysplasia in growing rabbits. METHODS: Sixty rabbits were divided into four groups (N = 30 knees/group). The control group underwent no surgical procedures. The rabbits in the three experimental groups underwent surgical patellar subluxation. Those in the early-reduced group underwent reduction surgery 1 month after patellar subluxation. The late-reduced group underwent reduction surgery 2 months after patellar subluxation. The rabbits in the non-reduced group underwent no reduction surgery. CT scans were performed monthly to measure the sulcus angle and trochlear width and depth. Gross specimen examination and histological observation were performed to investigate anatomical configuration and changes in the trochlear groove cartilage. RESULTS: CT scans demonstrated significant differences in the sulcus angle, trochlear width and trochlear depth by 6 months after subluxation surgery in the late-reduced and non-reduced groups. No obvious differences in these parameters were seen in the early-reduced group compared with the control group. Gross specimen examination and histological investigations showed degenerative changes in the femoral trochlear groove and cartilage by 6 months after subluxation surgery in the late-reduced and non-reduced groups. No degenerative changes were found in the early-reduced group, compared with the control group. CONCLUSION: Our results indicate that patellar subluxation or dislocation early in an animal's development can lead to femoral trochlear dysplasia or flattening and that early relocation of the patella can prevent femoral trochlear dysplasia in growing rabbits.

S100A4 promotes liver fibrosis via activation of hepatic stellate cells.

BACKGROUND & AIMS: S100A4 has been linked to the fibrosis of several organs due to its role as a fibroblast-specific marker. However, the role of S100A4 itself in the development of fibrosis has not been much investigated. Here, we determined whether S100A4 regulates liver fibrogenesis and examined its mechanism by focusing on the activation of hepatic stellate cells (HSCs). METHODS: S100A4 deficient mice were used to determine the role of S100A4 in liver fibrogenesis. The effect of S100A4 on HSC activation was estimated by using primary mouse HSCs and the human HSC cell line LX-2. Serum levels of S100A4 in cirrhotic patients were determined by ELISA. RESULTS: S100A4 was found to be secreted by a subpopulation of macrophages and to promote the development of liver fibrosis. It accumulated in the liver during the progression of liver fibrosis and activated HSCs in mice. In vitro studies demonstrated that S100A4 induced the overexpression of alpha-smooth muscle actin through c-Myb in HSCs. Both, the selective depletion of S100A4-expressing cells and knockdown of S100A4 in the liver by RNA interference, resulted in a reduction of liver fibrosis following injury. Importantly, increased S100A4 levels in both the liver tissue and serum correlated positively with liver fibrosis in humans. CONCLUSIONS: S100A4 promotes liver fibrosis by activating HSCs, which may represent a potential target for anti-fibrotic therapies.

Suggestive annotation of brain MR images with gradient-guided sampling.

Machine learning has been widely adopted for medical image analysis in recent years given its promising performance in image segmentation and classification tasks. The success of machine learning, in particular supervised learning, depends on the availability of manually annotated datasets. For medical imaging applications, such annotated datasets are not easy to acquire, it takes a substantial amount of time and resource to curate an annotated medical image set. In this paper, we propose an efficient annotation framework for brain MR images that can suggest informative sample images for human experts to annotate. We evaluate the framework on two different brain image analysis tasks, namely brain tumour segmentation and whole brain segmentation. Experiments show that for brain tumour segmentation task on the BraTS 2019 dataset, training a segmentation model with only 7% suggestively annotated image samples can achieve a performance comparable to that of training on the full dataset. For whole brain segmentation on the MALC dataset, training with 42% suggestively annotated image samples can achieve a comparable performance to training on the full dataset. The proposed framework demonstrates a promising way to save manual annotation cost and improve data efficiency in medical imaging applications.

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results.

Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder translating DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties could enable clinical review of the most uncertain regions, thereby building trust and paving the way toward clinical translation. Several uncertainty estimation methods have recently been introduced for DL medical image segmentation tasks. Developing scores to evaluate and compare the performance of uncertainty measures will assist the end-user in making more informed decisions. In this study, we explore and evaluate a score developed during the BraTS 2019 and BraTS 2020 task on uncertainty quantification (QU-BraTS) and designed to assess and rank uncertainty estimates for brain tumor multi-compartment segmentation. This score (1) rewards uncertainty estimates that produce high confidence in correct assertions and those that assign low confidence levels at incorrect assertions, and (2) penalizes uncertainty measures that lead to a higher percentage of under-confident correct assertions. We further benchmark the segmentation uncertainties generated by 14 independent participating teams of QU-BraTS 2020, all of which also participated in the main BraTS segmentation task. Overall, our findings confirm the importance and complementary value that uncertainty estimates provide to segmentation algorithms, highlighting the need for uncertainty quantification in medical image analyses. Finally, in favor of transparency and reproducibility, our evaluation code is made publicly available at https://github.com/RagMeh11/QU-BraTS.

S100A4 Protects Myeloid-Derived Suppressor Cells from Intrinsic Apoptosis via TLR4-ERK1/2 Signaling.

Myeloid-derived suppressor cells (MDSCs) often expand during cancer or chronic inflammation and dampen immune responses. However, mechanisms underlying their capacity to escape intrinsic apoptosis in the inflammatory environment are still largely unknown. In this study, we investigated this in mouse tumor models with MDSC accumulation. Spontaneous rejection of tumors implanted into mice deficient for the small Ca2+-binding protein S100A4 (S100A4-/-) was accompanied by low numbers of peripheral MDSCs. This was independent of S100A4 expression on tumor cells. In contrast, MDSCs from S100A4-/- tumor-bearing mice showed a diminished resistance to the induction of intrinsic apoptosis. Further studies demonstrated that S100A4 protects MDSCs from apoptosis through toll-like receptor-4/extracellular signal-regulated kinase-dependent caspase-9 inhibition. The finding that S100A4 is critical for MDSC survival in inflammatory environments might have important implications for the clinical treatment of cancer or inflammation-related diseases.

S100A4 blockage alleviates agonistic anti-CD137 antibody-induced liver pathology without disruption of antitumor immunity.

Liver-related autoimmune toxicities triggered by agonistic anti-CD137 antibodies have greatly limited their use in clinical applications. Here, we found that anti-CD137 monoclonal antibody (mAb) treatment in mice induced the infiltration of a large number of S100A4+ macrophages into the liver. Depletion of these cells or deficiency of S100A4 decreased inflammatory cytokine profiles and drastically reduced the number of liver pathogenic CD8+ T cells. Mechanistically, soluble S100A4 directly activated the Akt pathway and specifically prolonged CD8+ T cell survival. Interestingly, one S100A4 neutralizing mAb selectively alleviated liver abnormalities but did not affect the antitumor immunity induced by anti-CD137 mAb therapy. Thus, our study presents a novel molecular link to the liver pathology induced by an immune stimulatory antibody and proposes that combinational immunotherapies targeting those pathways could potentially elicit optimal antitumor immunity with minimal side effects.

Tie2 Expression on Macrophages Is Required for Blood Vessel Reconstruction and Tumor Relapse after Chemotherapy.

Tumor relapse after chemotherapy is a major hurdle for successful cancer therapy. Chemotherapeutic drugs select for resistant tumor cells and reshape tumor microenvironment, including the blood supply system. Using animal models, we observed on macrophages in tumor tissue a close correlation between upregulated Tie2 expression and tumor relapse upon chemotherapy. Conditional deletion of Tie2 expression in macrophages significantly prohibited blood supply and regrowth of tumors. Tie2+ macrophages were derived from tumor-infiltrating Tie2-CD11b+ cells and hypoxia-induced Tie2 expression on these cells. Mechanistically, expression of Tie2 prevented macrophages from apoptosis in stress conditions via the AKT-dependent signaling pathway. Together, these results demonstrate that Tie2 expression by macrophages is necessary and sufficient to promote the reconstruction of blood vessels after chemotherapy, shedding new light on developing novel strategies to inhibit tumor relapse. Cancer Res; 76(23); 6828-38. ©2016 AACR.