影像学诊断质量评价和管理研究

影像学检查手段的多样化及其广泛应用一方面使得临床诊断的准确率得到大大提高,另一方面却使得影像学检查和诊断中存在的低效率和低效能的状况凸显;与此同时,影像学诊断质量的管理与快速发展的影像学技术手段相比则显得明显滞后。影像学诊断质量评价和管理研究的方法学的提出,为下一步进行疾病的影像学诊断质量评价与管理研究提供必要的理论指导。     

影像学诊断质量评价和管理研究

影像学检查手段的多样化及其广泛应用一方面使得临床诊断的准确率得到大大提高,另一方面却使得影像学检查和诊断中存在的低效率和低效能的状况凸显;与此同时,影像学诊断质量的管理与快速发展的影像学技术手段相比则显得明显滞后.影像学诊断质量评价和管理研究的方法学的提出,为下一步进行疾病的影像学诊断质量评价与管理研究提供必要的理论指导.     

CT 血流动力学用于乳腺癌诊断的受试者工作特性曲线分析

目的 应用临床流行病学受试者工作特性曲线(ROC)对CT组织灌注用于乳腺癌的诊断价值进行评估. 资料与方法 对81例(84个)体检或钼靶发现乳腺占位性病变者行MSCT组织灌注扫描,由去卷积法得出血流动力学参数[血流量(BF),平均通过时间(MTT),血容量(BV)],按病理结果 的良、恶性分组,行统计学检验.比较BF、MTT、BV相应的ROC特征,确定各参数的诊断价值. 结果 乳癌组的BF为(0.735±0.440)ml·min-1·ml-1,MTT为(22.771±7.647)s,BV为0.234±0.082;良性组的BF为(0.466±0.527)ml·min-1·ml-1,MTT为(26.712±12.934)s,BV为0.179±0.117.BF、BV在乳腺癌和良性病灶之间的差异有统计学意义.BF在判断乳腺良恶性病变时曲线下面积(AUCROC)最大,为0.832±0.086,BV的AUCROC为0.695±0.092,两者差异无统计学意义.MTT的AUCROC最小,为0.473.BF临界值为0.381 ml·min-1·ml-1 时,诊断乳腺癌的敏感性为82.3%,特异性为73.2%,阳性似然比为3.071,阴性似然比为0.242;BV临界值为0.190时,敏感性为73.3%,特异性为56.5%,阳性似然比为1.685,阴性似然比为0.473. 结论 CT 血流动力学参数(BF\BV)对乳腺癌的诊断有应用价值,但尚不能作为单一指标肯定或否定乳腺癌的诊断.     

MRI联合多层螺旋CT在脊柱转移瘤患者中的辅助诊断价值及与肿瘤标志物的相关性研究

目的 探讨MRI联合多层螺旋CT在脊柱转移瘤患者中的辅助诊断价值及与肿瘤标志物的相关性.方法 选取2017年6月～2020年8月疑似脊柱转移瘤患者112例,均以病理组织检查结果作为金标准,病理检查前均行MRI及多层螺旋CT检查,并将MRI与多层螺旋CT结果与金标准进行比较,分析其影像学特点;绘制ROC曲线,分析MR...     

评价计算机辅助诊断乳腺MR成像工作站样机的临床乳腺MR成像:阅片者研究

目的对计算机辅助诊断(CADx)系统的动态对比增强MR成像进行评价,并与当前所使用的用于显示乳腺MR成像表现的临床方法(包括采用商用自动匹配软件)进行     

计算机辅助检测在结肠低剂量多层螺旋CT成像中的应用

目的 评估计算机辅助检测系统(CAD)设置不同的检测过滤器数值(SFV)时,在低剂量MSCT成像中对结肠病变的检测能力.方法 56例结肠癌和(或)结肠息肉患者行MSCT结肠成像扫描,依据结肠镜和外科手术结果,将病变分为4组:结肠癌、最长径≥10.0mm息肉、最长径5.1～9.9 mm息肉和最长径≤5.0 mm息肉,之后确定病变在CT图像上的部位及大小,作为评估结肠CAD系统检测病变的金标准.将CAD系统的SFV设为0.25、0.50、0.75和1.00共4个等级,分别检测CT结肠成像图像,记录CAD标注出的病灶的部位和大小,根据上述金标准评估CAD系统对结肠病变的检出率,采用x2检验比较不同SFV设置时CAD对各组病变的检出率.结果 56例患者共有159个阳性病灶,其中结肠癌为44个,最长径≥10.0mm息肉45个,最长径5.1～9.9 mm息肉32个,最长径≤5.0 mm息肉38个.将结肠CAD系统SFV分别设置为0.25、0.50、0.75和1.00时,病灶的检出率分别85.5%(136/159)、85.5%(136/159)、79.2%(126/159)和56.0%(89/159).SFV为0.25和0.50时,与SFV为1.00时,CAD对病灶检出率的差异有统计学意义(P＜0.05).随着SFV数值的减低,病灶的检出率增高,假阳性数增加,但91.4%(138/151)～93.9%(31/33)的假阳性病灶很容易识别,仅有6.1%(2/33)～8.6%(13/151)的假阳性病灶,需借助MPR和3D仿真内镜识别.结论 在低剂量MSCT结肠成像中,结肠CAD系统可获得满意的病灶检出率,可调节CAD系统SFV数值,以便满足不同经验阅片者的需求.     

Colonic polyps: complementary role of computer-aided detection in CT colonography

PURPOSE: To apply a computer-aided detection (CAD) algorithm to supine and prone multisection helical computed tomographic (CT) colonographic images to confirm if there is any added benefit provided by CAD over that of standard clinical interpretation. MATERIALS AND METHODS: CT colonography (with patients in both supine and prone positions) was performed with a multisection helical CT scanner in 40 asymptomatic high-risk patients. There were two consecutive series of patients, 20 of whom had at least one polyp 1.0 cm in size or larger and 20 of whom had normal colons at conventional colonoscopy performed the same day. The CT colonographic images were interpreted with an automated CAD algorithm and by two radiologists who were blinded to colonoscopy findings. RESULTS: For 25 polyps at least 1.0 cm in size ("large" polyps), sensitivity for detection by at least one radiologist was 48% (12 of 25). The sensitivity of CAD for detecting large polyps was also 48% (12 of 25), but the CAD algorithm detected four of 13 large polyps that were not detected by either radiologist (31%, 95% two-sided CI: 9, 61), increasing the potential sensitivity to 64% (16 of 25). For polyps identifiable retrospectively, sensitivity of CAD was 67% (12 of 18), and sensitivity of the combination of detection with the CAD algorithm or by at least one radiologist was 89% (16 of 18). There were an average of 11 false-positive detections per patient for CAD. CONCLUSION: In this series of patients in whom radiologists had difficulties detecting polyps (compared with sensitivities of 75%-90% reported in the literature), this CAD algorithm played a complementary role to conventional interpretation of CT colonographic images by detecting a number of large polyps missed by trained observers.     

CT colonography: computer-aided detection of morphologically flat T1 colonic carcinoma

The purpose was to evaluate the ability of computer-aided detection (CAD) software to detect morphologically flat early colonic carcinoma using CT colonography (CTC). Twenty-four stage T1 colonic carcinomas endoscopically classified as flat (width over twice height) were accrued from patients undergoing staging CTC. Tumor location was annotated by three experienced radiologists in consensus aided by the endosocpic report. CAD software was then applied at three settings of sphericity (0, 0.75, and 1). Computer prompts were categorized as either true positive (overlapping tumour boundary) or false positive. True positives were subclassified as focal or non focal. The 24 cancers were endoscopically classified as type IIa (n=11) and type IIa+IIc (n=13). Mean size (range) was 27 mm (7-70 mm). CAD detected 20 (83.3%), 17 (70.8%), and 13 (54.1%) of the 24 cancers at filter settings of 0, 0.75, and 1, respectively with 3, 4, and 8 missed cancers of type IIa, respectively. The mean total number of false-positive CAD marks per patient at each filter setting was 36.5, 21.1, and 9.5, respectively, excluding polyps. At all settings, >96.1% of CAD true positives were classified as focal. CAD may be effective for the detection of morphologically flat cancer, although minimally raised laterally spreading tumors remain problematic.     

Virtual colon dissection with CT colonography compared with axial interpretation and conventional colonoscopy: preliminary results

OBJECTIVE: The aim of this study was to determine whether a new virtual colon dissection 3D visualization technique for CT colonography has a shorter analysis time and better sensitivity for detection of colonic polyps than interpretation of axial CT images. SUBJECTS AND METHODS. CT colonography was performed in 22 patients using 4-MDCT followed by conventional colonoscopy on the same day. The CT colonography data sets were analyzed by virtual colon dissection, which virtually bisects and unfolds the colon along its longitudinal axis to inspect the inner colonic surface for polyps. The same CT data sets were independently evaluated using axial interpretation. All data sets were independently interpreted by two radiologists in a blinded manner. RESULTS: Conventional colonoscopy revealed 31 colonic lesions in 20 patients. Twenty two of the lesions were smaller than 10 mm; nine were 10 mm or larger. Two of the original 22 patients were excluded, one because of residual stool and fluid and the other because of an impassable stenosing rectal wall cancer. For virtual colon dissection, the per-lesion sensitivity was 42% for observer 1 and 68% for observer 2; for axial interpretation, the respective sensitivities were 48% and 61%. For polyps 10 mm or larger, the respective sensitivities were 67% and 89% for virtual colon dissection and 89% and 100% for axial interpretation. The average time for reconstruction and analysis of virtual colon dissection was 36.8 min versus 29.2 min for axial images. Virtual colon dissection was feasible in both the supine and the prone positions in 45.5% of colonic segments, in either the supine or the prone position in 24.5%, and in neither position in 30% of segments. CONCLUSION: Although virtual colon dissection may facilitate detection of colonic polyps in isolated cases, its detection rate is not superior to axial interpretation, which is mainly attributable to failed rendering of insufficiently distended colonic segments or regions with residual feces. Virtual colon dissection is also the more time-consuming of the two procedures. With further improvement of path-finding and image segmentation, however, virtual colon dissection has the potential to be a useful interpretation tool for CT colonography.     

CT colonography: effect of computer-aided detection of colonic polyps as a second and concurrent reader for general radiologists with moderate experience in CT colonography

Objectives

To assess the effectiveness of computer-aided detection (CAD) as a second reader or concurrent reader in helping radiologists who are moderately experienced in computed tomographic colonography (CTC) to detect colorectal polyps.

Methods

Seventy CTC datasets (34 patients: 66 polyps ≥6 mm; 36 patients: no abnormalities) were retrospectively reviewed by seven radiologists with moderate CTC experience. After primary unassisted evaluation, a CAD second read and, after a time interval of ≥4 weeks, a CAD concurrent read were performed. Areas under the receiver operating characteristic (ROC) curve (AUC), along with per-segment, per-polyp and per-patient sensitivities, and also reading times, were calculated for each reader with and without CAD.

Results

Of seven readers, 86 % and 71 % achieved a higher accuracy (segment-level AUC) when using CAD as second and concurrent reader respectively. Average segment-level AUCs with second and concurrent CAD (0.853 and 0.864) were significantly greater (p?<?0.0001) than average AUC in the unaided evaluation (0.781). Per-segment, per-polyp, and per-patient sensitivities for polyps ≥6 mm were significantly higher in both CAD reading paradigms compared with unaided evaluation. Second-read CAD reduced readers’ average segment and patient specificity by 0.007 and 0.036 (p?=?0.005 and 0.011), respectively.

Conclusions

CAD significantly improves the sensitivities of radiologists moderately experienced in CTC for polyp detection, both as second reader and concurrent reader.

Key Points

? CAD helps radiologists with moderate CTC experience to detect polyps ≥6 mm. ? Second and concurrent read CAD increase the radiologist’s sensitivity for detecting polyps ≥6 mm. ? Second read CAD slightly decreases specificity compared with an unassisted read. ? Concurrent read CAD is significantly more time-efficient than second read CAD.