VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images

Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly available data. Addressing these limitations, the Large Scale Vertebrae Segmentation Challenge (VerSe) was organised in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2019 and 2020, with a call for algorithms tackling the labelling and segmentation of vertebrae. Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel level by a human-machine hybrid algorithm (https://osf.io/nqjyw/, https://osf.io/t98fz/). A total of 25 algorithms were benchmarked on these datasets. In this work, we present the results of this evaluation and further investigate the performance variation at the vertebra level, scan level, and different fields of view. We also evaluate the generalisability of the approaches to an implicit domain shift in data by evaluating the top-performing algorithms of one challenge iteration on data from the other iteration. The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations. The VerSe content and code can be accessed at: https://github.com/anjany/verse.     

肝脏转移瘤消融术后疗效的影像学评价进展

肝转移瘤消融术后边缘局部残留或复发很常见。MRI功能成像包括扩散加权成像(diffusion weighted imaging,DWI)、多b值DWI、动态对比增强(dynamic contrast enhanced,DCE)成像、影像组学等在消融后早期显示病灶残留、鉴别术后炎症增生改变与残留或复发灶等方面的价值较大。该文就上述影像学方法在肝脏转移瘤消融术后疗效评价中的应用作一综述。     

2015—2018年浙江省12家医院肿瘤患者抗凝药物的使用情况分析

目的 分析2015-2018年浙江省12家医院肿瘤患者抗凝药物的使用现状及其用药特点和趋势。方法 对2015-2018年浙江省12家医院肿瘤患者使用的抗凝药物的用药金额、用药频度（DDDs）、限定日费用（DDC）及排序比（B/A）等情况进行统计分析。结果 2015-2018年肿瘤患者抗凝药物的用药总金额呈上升趋势,2018年比2015年上涨2倍左右;其中肝素类抗凝药的DDDs和DDC排名较前,肝素钠类B/A大于或接近于1,肝素钙类B/A小于1;新型口服抗凝药利伐沙班片、阿哌沙班片和达比加群酯胶囊的DDDs逐年上涨,但排名仍较后,且DDC较高,B/A接近于1;纤溶药的DDDs轻微上升,但DDC较为稳定,B/A小于1;华法林的DDDs稳定,DDC低廉,B/A大于1。结论 2015-2018年浙江省12家医院肿瘤患者抗凝药物的使用基本合理,基本无滥用情况。     

基于主成分分析的不受睡眠姿势影响的呼吸容积动态监测方法

目的探究基于主成分分析(PCA)的不受睡眠姿势影响的呼吸容积动态监测方法。方法利用2014年6月采集到的10名健康男性大学生平静呼吸时在仰卧、左侧卧和右侧卧位下的呼吸流速(PNT)信号及胸腔阻抗(IPTH)、左肺阻抗(IPL)和右肺阻抗(IPR)信号,通过对PNT信号进行积分运算得到呼吸容积(VPNT)信号作为金标准,使用基于PCA的数据融合算法从左肺和右肺的呼吸信号中获取融合的容积信号(VIPLR)。结果VIPLR与VPNT的相关系数(r)高达0.9501,且与经典的胸腔阻抗容积(VIPTH)比较,容积平均绝对误差(MAE)下降了25%。结论基于PCA的睡眠呼吸容积评估方法是一种可信度较高的睡眠呼吸容积动态监测新方法,能够最大限度地克服睡眠姿势变换对监测结果的影响。