Health-related quality of life after isolated limb perfusion compared to extended resection,or amputation for locally advanced extremity sarcoma: Is a limb salvage strategy worth the effort?

IntroductionThe aim of this study was to compare long-term patient reported outcomes (PROs) in patients with locally advanced extremity soft tissue sarcoma (eSTS) after isolated limb perfusion followed by resection (IR), compared to extended resection (ER), primary amputation (A) or secondary amputation after IR (IR-A).MethodsPatients were selected from the respondents of a multi-institutional cross-sectional cohort survivorship study (SURVSARC) conducted among sarcoma survivors registered in the Netherlands Cancer Registry (NCR), 2–10 years after diagnosis. Used PROs were the EORTC QLQ-C30, the Cancer worry scale (CWS), the Hospital Anxiety and Depression Scale (HADS), and the Toronto Extremity Salvage Score (TESS).ResultsWe identified 97 eSTS survivors: IR = 20, ER = 49, A = 20, IR-A = 8. While there were no differences in PROs between IR and ER, results showed better functioning and functionality in both groups versus the amputation groups. The amputation groups scored significantly lower on physical functioning (A = 62.7, IR-A = 65.7 versus IR = 78.0, ER = 82.7, p = 0.001) and role functioning (A = 67.5, IR-A = 52.8 versus IR = 79.2, ER = 80.6, p = 0.039), both EORTC QLQ-C30 scales. Also for the TESS, the scores were significantly lower for the amputation groups compared to the limb sparing groups (upper extremity p = 0.007 with A = 68.9, IR-A = 71.6 versus IR = 93.3, ER = 91.1; lower extremity p < 0.001 with A = 72.2, IR-A50.9 versus IR = 84.5 and ER = 85.5). There were no significant differences between the groups on cancer worry, anxiety and depression.ConclusionHRQoL in eSTS survivors treated with IR or ER is equal; for maintenance of physical functioning and functionality IR and ER outperform an amputation.     

凉血通瘀方干预高血压大鼠急性脑出血模型对脑组织中差异miRNA表达的影响＊

目的 研究凉血通瘀方对高血压大鼠急性脑出血模型脑组织miRNA表达的影响，对差异表达的miRNA靶基因进行分析，探索凉血通瘀方可能的药效机制。方法 将自发性高血压大鼠随机分成对照组（B）和实验组（C）。适应性饲养一周后，C组灌胃凉血通瘀方，B组灌胃等体积生理盐水，连续5天，每天1次。构建脑出血模型后收集脑组织，借助全转录组测序技术获得miRNA表达量，与miRBase数据库比对获取已知miRNA，使用miRDeep2预测新miRNA。差异分析软件为DESeq2，筛选阈值为|log₂FC| ≥1 并且P <0.05。对显著差异表达的miRNA进行靶基因预测，对靶基因进行GO功能、KEGG通路富集和PPI网络分析。结果 实验组和对照组对比，共发现21个显著差异表达的miRNA，上调有9个，下调有12个，共预测得到1243个有统计学意义的靶基因。GO富集分析发现，生物过程中突触囊泡分泌的调节、神经递质分泌的调节和神经递质运输的调节占前三位，神经元投射终点、全膜、质膜区域和细胞投射则是主要的细胞成分。分子功能分别为小GTPase绑定、底物特异性跨膜转运蛋白活性和离子跨膜转运体活性。通路分析结果显示，靶基因在癌证通路、pI3K-Akt信号通路、人类乳头瘤病毒感染、神经活性配体-受体相互作用和MAPK通路等分布广泛。采用STRING网站和Cytoscape软件，根据MCC算法筛选出ADRA2C、CASR、CCL28、CCR1、DRD2、GNAT3、GRM2、DYNC1LI1、GABBR1、GNAI1等核心靶基因。结论 凉血通瘀方对脑出血急性期鼠脑组织内miRNA的表达有重要影响；显著差异表达miRNAs可能通过靶向核心基因调控凉血通瘀方干预急性脑出血的病理过程及预后。     

Phase 0 Study of Vandetanib-Eluting Radiopaque Embolics as a Preoperative Embolization Treatment in Patients with Resectable Liver Malignancies

PurposeTo assess the safety and tolerability of a vandetanib-eluting radiopaque embolic (BTG-002814) for transarterial chemoembolization (TACE) in patients with resectable liver malignancies.Materials and MethodsThe VEROnA clinical trial was a first-in-human, phase 0, single-arm, window-of-opportunity study. Eligible patients were aged ≥18 years and had resectable hepatocellular carcinoma (HCC) (Child-Pugh A) or metastatic colorectal cancer (mCRC). Patients received 1 mL of BTG-002814 transarterially (containing 100 mg of vandetanib) 7–21 days prior to surgery. The primary objectives were to establish the safety and tolerability of BTG-002814 and determine the concentrations of vandetanib and the N-desmethyl vandetanib metabolite in the plasma and resected liver after treatment. Biomarker studies included circulating proangiogenic factors, perfusion computed tomography, and dynamic contrast-enhanced magnetic resonance imaging.ResultsEight patients were enrolled: 2 with HCC and 6 with mCRC. There was 1 grade 3 adverse event (AE) before surgery and 18 after surgery; 6 AEs were deemed to be related to BTG-002814. Surgical resection was not delayed. Vandetanib was present in the plasma of all patients 12 days after treatment, with a mean maximum concentration of 24.3 ng/mL (standard deviation ± 13.94 ng/mL), and in resected liver tissue up to 32 days after treatment (441–404,000 ng/g). The median percentage of tumor necrosis was 92.5% (range, 5%–100%). There were no significant changes in perfusion imaging parameters after TACE.ConclusionsBTG-002814 has an acceptable safety profile in patients before surgery. The presence of vandetanib in the tumor specimens up to 32 days after treatment suggests sustained anticancer activity, while the low vandetanib levels in the plasma suggest minimal release into the systemic circulation. Further evaluation of this TACE combination is warranted in dose-finding and efficacy studies.     

Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning

Arterial spin labeling (ASL) imaging is a powerful magnetic resonance imaging technique that allows to quantitatively measure blood perfusion non-invasively, which has great potential for assessing tissue viability in various clinical settings. However, the clinical applications of ASL are currently limited by its low signal-to-noise ratio (SNR), limited spatial resolution, and long imaging time. In this work, we propose an unsupervised deep learning-based image denoising and reconstruction framework to improve the SNR and accelerate the imaging speed of high resolution ASL imaging. The unique feature of the proposed framework is that it does not require any prior training pairs but only the subject's own anatomical prior, such as T1-weighted images, as network input. The neural network was trained from scratch in the denoising or reconstruction process, with noisy images or sparely sampled k-space data as training labels. Performance of the proposed method was evaluated using in vivo experiment data obtained from 3 healthy subjects on a 3T MR scanner, using ASL images acquired with 44-min acquisition time as the ground truth. Both qualitative and quantitative analyses demonstrate the superior performance of the proposed txtc framework over the reference methods. In summary, our proposed unsupervised deep learning-based denoising and reconstruction framework can improve the image quality and accelerate the imaging speed of ASL imaging.     

浅谈脑梗死的中医病因病机与中医药治疗近况

脑梗死是缺血性卒中之一,随着人口老龄化发展趋势,目前已越居我国居民致残和死亡的首要病因。中医药治疗脑梗死有着重要特色和优势,目前在医学领域中仍占着不可动摇的地位,现就针对古代医家及近现代医家对中风病中医病因病机认识,以及中医药治疗方面针对经典方、经验方、中成药、中医外治等方面进行总结综述。     

DEep learning-based rapid Spiral Image REconstruction (DESIRE) for high-resolution spiral first-pass myocardial perfusion imaging

The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) technique for high-resolution spiral first-pass myocardial perfusion imaging with whole-heart coverage, to provide fast and accurate image reconstruction for both single-slice (SS) and simultaneous multislice (SMS) acquisitions. Three-dimensional U-Net–based image enhancement architectures were evaluated for high-resolution spiral perfusion imaging at 3 T. The SS and SMS MB = 2 networks were trained on SS perfusion images from 156 slices from 20 subjects. Structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and normalized root mean square error (NRMSE) were assessed, and prospective images were blindly graded by two experienced cardiologists (5: excellent; 1: poor). Excellent performance was demonstrated for the proposed technique. For SS, SSIM, PSNR, and NRMSE were 0.977 [0.972, 0.982], 42.113 [40.174, 43.493] dB, and 0.102 [0.080, 0.125], respectively, for the best network. For SMS MB = 2 retrospective data, SSIM, PSNR, and NRMSE were 0.961 [0.950, 0.969], 40.834 [39.619, 42.004] dB, and 0.107 [0.086, 0.133], respectively, for the best network. The image quality scores were 4.5 [4.1, 4.8], 4.5 [4.3, 4.6], 3.5 [3.3, 4], and 3.5 [3.3, 3.8] for SS DESIRE, SS L1-SPIRiT, MB = 2 DESIRE, and MB = 2 SMS-slice-L1-SPIRiT, respectively, showing no statistically significant difference (p = 1 and p = 1 for SS and SMS, respectively) between L1-SPIRiT and the proposed DESIRE technique. The network inference time was ~100 ms per dynamic perfusion series with DESIRE, while the reconstruction time of L1-SPIRiT with GPU acceleration was ~ 30 min. It was concluded that DESIRE enabled fast and high-quality image reconstruction for both SS and SMS MB = 2 whole-heart high-resolution spiral perfusion imaging.