Cervical lesion assessment using real-time microendoscopy image analysis in Brazil: The CLARA study.
Cervical lesion assessment using real-time microendoscopy image analysis in Brazil: The CLARA study.
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DOI：
10.1002/ijc.33543
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发表时间：
2021-07-15
影响因子：
6.4
通讯作者：
Richards-Kortum R
中科院分区：
文献类型：
--
作者：
Hunt B;Fregnani JHTG;Brenes D;Schwarz RA;Salcedo MP;Possati-Resende JC;Antoniazzi M;de Oliveira Fonseca B;Santana IVV;de Macêdo Matsushita G;Castle PE;Schmeler KM;Richards-Kortum R
我们对高分辨率显微内镜（HRME）检测筛查试验异常妇女宫颈上皮内瘤变（CIN）的诊断性能进行了前瞻性评价。研究参与者接受阴道镜检查、HRME和宫颈活检。将使用自动形态学图像分析算法的HRME的前瞻性诊断性能与使用CIN的组织病理学检测作为金标准的阴道镜检查进行比较。为了评估进一步提高HRME图像分析性能的潜力，我们还进行了一项回顾性分析，评估了多任务卷积神经网络对HRME图像进行分割和分类的性能。1，486例受试者完成了研究; 435例（29%）受试者诊断为CIN 2级或更严重（CIN 2+）。HRME结合形态学图像分析检测CIN 3级或更严重诊断（CIN 3+）的敏感性（95.6% vs. 96.2%，p=0.81）和特异性（56.6% vs. 58.7%，p=0.18）与阴道镜相似。HRME结合形态学图像分析检测CIN 2+的敏感性（91.7% vs. 95.6%，p<0.01）和特异性（59.7% vs. 63.4%，p=0.02）略低于阴道镜。来自870名受试者的图像用于训练基于多任务卷积神经网络的算法，其余616名受试者的图像用于验证其性能。神经网络分析HRME与阴道镜检测CIN 2+或CIN 3+的敏感性和特异性无显著差异。使用基于神经网络的算法，HRME在检测CIN 2+方面具有与阴道镜相当的灵敏度和特异性。HRME可以提供一种低成本的，护理点替代阴道镜检查和活检预防宫颈癌。
We conducted a prospective evaluation of the diagnostic performance of high-resolution microendoscopy (HRME) to detect cervical intraepithelial neoplasia (CIN) in women with abnormal screening tests. Study participants underwent colposcopy, HRME, and cervical biopsy. The prospective diagnostic performance of HRME using an automated morphologic image analysis algorithm was compared to colposcopy using histopathologic detection of CIN as the gold standard. To assess the potential to further improve performance of HRME image analysis, we also conducted a retrospective analysis assessing performance of a multi-task convolutional neural network to segment and classify HRME images. 1,486 subjects completed the study; 435 (29%) subjects had CIN grade 2 or more severe (CIN2+) diagnosis. HRME with morphologic image analysis for detection of CIN grade 3 or more severe diagnoses (CIN3+) was similarly sensitive (95.6% vs. 96.2%, p=0.81) and specific (56.6% vs. 58.7%, p=0.18) as colposcopy. HRME with morphologic image analysis for detection of CIN2+ was slightly less sensitive (91.7% vs. 95.6%, p<0.01) and specific (59.7% vs. 63.4%, p=0.02) than colposcopy. Images from 870 subjects were used to train a multi-task convolutional neural network-based algorithm and images from the remaining 616 were used to validate its performance. There were no significant differences in the sensitivity and specificity of HRME with neural network analysis vs. colposcopy for detection of CIN2+ or CIN3+. Using a neural network-based algorithm, HRME has comparable sensitivity and specificity to colposcopy for detection of CIN2+. HRME could provide a low-cost, point-of-care alternative to colposcopy and biopsy in the prevention of cervical cancer.
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影响因子：
7.7
作者：
Quang, Timothy;Schwarz, Richard A.;Richards-Kortum, Rebecca
通讯作者：
Richards-Kortum, Rebecca
DOI：
10.3233/978-1-61499-234-9-235
发表时间：
2013-01-01
期刊：
BIOPHOTONICS IN PATHOLOGY: PATHOLOGY AT THE CROSSROADS
影响因子：
--
作者：
Liu, Jonathan T. C.;Loewke, Nathan O.;Contag, Christopher H.
通讯作者：
Contag, Christopher H.
DOI：
10.1158/1940-6207.capr-12-0221
发表时间：
2012-11
期刊：
Cancer prevention research (Philadelphia, Pa.)
影响因子：
--
作者：
Pierce MC;Guan Y;Quinn MK;Zhang X;Zhang WH;Qiao YL;Castle P;Richards-Kortum R
通讯作者：
Richards-Kortum R
影响因子：
34.3
作者：
Arbyn, Marc;Weiderpass, Elisabete;Bray, Freddie
通讯作者：
Bray, Freddie
影响因子：
3.3
作者：
Hunt, Brady;Tavares Guerreiro Fregnani, Jose Humberto;Richards-Kortum, Rebecca
通讯作者：
Richards-Kortum, Rebecca