Long Hallucal Tendon Force Vectors and First Metatarsophalangeal Deformity After Hallux Valgus Surgery.

BACKGROUND: Recurrence is one of the most common complications following hallux valgus surgery. Moreover, hallux varus occurs in cases of overcorrection. We aimed to quantitatively measure, using radiographic examination, the dynamics of the soft tissues that act on deformities (recurrence of valgus and occurrence of varus) after the surgery. METHODS: This retrospective single-institution study included 60 patients (98 feet) who underwent hallux valgus surgery between 2009 and 2018. According to radiographic findings of the foot under weightbearing conditions at postoperative month 1, we examined the tendons' pathway and calculated the forces on the first metatarsophalangeal joint, which we termed the deformity force angle (DFA). We compared whether there was a significant difference in DFAs between the groups in which deformities occurred and those in which deformities did not occur after correction. In addition, the DFA was compared to known radiographic measurements of hallux valgus recurrence (hallux valgus angle, distal metatarsal articular angle, intermetatarsal angle, and sesamoid position) to assess association with recurrence. RESULTS: We observed a significant difference in the DFA between patients with and without hallux valgus recurrence (P < .001) and between those with and without hallux varus (P < .001) based on standing radiographs taken at a minimum of 6 months postoperation. For predicting the deformities, the areas under the curve were 0.863 (hallux valgus recurrence) and 0.831 (hallux varus occurrence), respectively, which was greater than other factors evaluated. The DFA values greater than 9.5 degrees and less than 5.5 degrees were associated with the recurrence of valgus and occurrence of varus, respectively. CONCLUSION: In our study, DFA was associated with hallux valgus recurrence when it exceeded 9.5 degrees and hallux varus when it was less than 5.5 degrees. Moreover, in the hallux valgus surgery we performed, a DFA from 5.5 to 9.5 degrees appeared to be a "safe zone" for preventing early deformity after surgery. LEVEL OF EVIDENCE: Level III, prognostic.

Localization-adjusted diagnostic performance and assistance effect of a computer-aided detection system for pneumothorax and consolidation.

While many deep-learning-based computer-aided detection systems (CAD) have been developed and commercialized for abnormality detection in chest radiographs (CXR), their ability to localize a target abnormality is rarely reported. Localization accuracy is important in terms of model interpretability, which is crucial in clinical settings. Moreover, diagnostic performances are likely to vary depending on thresholds which define an accurate localization. In a multi-center, stand-alone clinical trial using temporal and external validation datasets of 1,050 CXRs, we evaluated localization accuracy, localization-adjusted discrimination, and calibration of a commercially available deep-learning-based CAD for detecting consolidation and pneumothorax. The CAD achieved image-level AUROC (95% CI) of 0.960 (0.945, 0.975), sensitivity of 0.933 (0.899, 0.959), specificity of 0.948 (0.930, 0.963), dice of 0.691 (0.664, 0.718), moderate calibration for consolidation, and image-level AUROC of 0.978 (0.965, 0.991), sensitivity of 0.956 (0.923, 0.978), specificity of 0.996 (0.989, 0.999), dice of 0.798 (0.770, 0.826), moderate calibration for pneumothorax. Diagnostic performances varied substantially when localization accuracy was accounted for but remained high at the minimum threshold of clinical relevance. In a separate trial for diagnostic impact using 461 CXRs, the causal effect of the CAD assistance on clinicians' diagnostic performances was estimated. After adjusting for age, sex, dataset, and abnormality type, the CAD improved clinicians' diagnostic performances on average (OR [95% CI] = 1.73 [1.30, 2.32]; p < 0.001), although the effects varied substantially by clinical backgrounds. The CAD was found to have high stand-alone diagnostic performances and may beneficially impact clinicians' diagnostic performances when used in clinical settings.

Computerized Bone Age Estimation Using Deep Learning Based Program: Evaluation of the Accuracy and Efficiency.

OBJECTIVE: The purpose of this study is to evaluate the accuracy and efficiency of a new automatic software system for bone age assessment and to validate its feasibility in clinical practice. MATERIALS AND METHODS: A Greulich-Pyle method-based deep-learning technique was used to develop the automatic software system for bone age determination. Using this software, bone age was estimated from left-hand radiographs of 200 patients (3-17 years old) using first-rank bone age (software only), computer-assisted bone age (two radiologists with software assistance), and Greulich-Pyle atlas-assisted bone age (two radiologists with Greulich-Pyle atlas assistance only). The reference bone age was determined by the consensus of two experienced radiologists. RESULTS: First-rank bone ages determined by the automatic software system showed a 69.5% concordance rate and significant correlations with the reference bone age (r = 0.992; p < 0.001). Concordance rates increased with the use of the automatic software system for both reviewer 1 (63.0% for Greulich-Pyle atlas-assisted bone age vs 72.5% for computer-assisted bone age) and reviewer 2 (49.5% for Greulich-Pyle atlas-assisted bone age vs 57.5% for computer-assisted bone age). Reading times were reduced by 18.0% and 40.0% for reviewers 1 and 2, respectively. CONCLUSION: Automatic software system showed reliably accurate bone age estimations and appeared to enhance efficiency by reducing reading times without compromising the diagnostic accuracy.

Antiviral protection against enterovirus 71 mediated by autophagy induction following FLICE-inhibitory protein inactivation.

Even with the recent awareness of enterovirus 71 (EV71) as a major public health issue, there are no preventive or therapeutic agents that are effective against EV71 infection. Although FLICE-like inhibitory protein (FLIP) has been identified as a factor that modulates virus pathogenesis, there are no reports regarding its effects on EV71 infection. The aim of the present study was to identify whether FLIP influences EV71 pathogenesis and to understand the underlying mechanisms. Virus replication was markedly reduced in MRC5 cells preincubated with anti-FLIP peptides, and infected cells were rescued from the cytopathic effects of the virus. The anti-FLIP peptides induced autophagy by disrupting intrinsic FLIP functions. The antiviral activity of these peptides was reduced when autophagy was inhibited by treatment with siRNA targeted to beclin-1. Thus, the present study provides evidence that anti-FLIP peptides induce autophagy by inactivating cFLIP, and that this is associated with antiviral effects against EV71.