Morphologic pattern analysis of submucosal deformities identified by endoscopic ultrasonography for predicting the depth of invasion in early gastric cancer

Kim, Tae Young; Yi, Nam Hee; Hwang, Jin Won; Kim, Ji Hyun; Kim, Gwang Ha; Kang, Mi Seon

doi:10.1007/s00464-018-6496-2

Cited by 10 publications

(12 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several studies have mentioned the sensitivity for SM2 or deeper EGC by EUS ranging from 66.3% to 84.0%, 17 , 20 , 21 similar to the findings in our study.…”

Section: Discussionsupporting

confidence: 91%

See 1 more Smart Citation

Endoscopic Ultrasonography Miniature Probe Performance for Depth Diagnosis of Early Gastric Cancer with Suspected Submucosal Invasion

et al. 2020

View full text Add to dashboard Cite

Background/Aims: The accurate assessment of the depth of invasion of early gastric cancer (EGC) is critical to determine the most appropriate treatment option. However, it is difficult to distinguish shallow submucosal (SM1) invasion from deeper submucosal (SM2) invasion. We investigated the diagnostic performance of endoscopic ultrasonography (EUS) using a miniature probe for EGC with suspected SM invasion. Methods: From April 2008 to June 2018, EGCs with suspected SM invasion were analyzed retrospectively. The EGCs examined by a 20 MHz high-frequency miniature probe was included in our study. Esophago-gastric junction cancers and patients treated by chemotherapy before resection were excluded. The sensitivity and specificity for the detection of SM2 invasion by EUS were compared with those of white light imaging (WLI). Additionally, factors related to depth underestimation or overestimation were investigated using multivariate analysis. Results: A total of 278 EGCs in 259 patients were included in the final analysis. The sensitivity and specificity for SM2 or deeper by EUS were 73.7% (87/118) and 74.4% (119/160), respectively. The sensitivity and specificity by WLI were 47.5% (56/118) and 68.1% (109/160), respectively. The sensitivity of EUS was significantly superior to that of conventional endoscopy (p<0.01). Multivariate analysis revealed that an anterior location of the EGC was an independent risk factor for underestimation by EUS (odds ratio, 3.3; 95% confidence interval, 1.1 to 9.8; p=0.03). Conclusions: The depth diagnostic performance for EGCs with suspected SM invasion using EUS was satisfactory and superior to that of conventional endoscopy. Additionally, it is important to recognize factors that may lead to misdiagnosis in those lesions.

show abstract

“…Several studies have mentioned the sensitivity for SM2 or deeper EGC by EUS ranging from 66.3% to 84.0%, 17 , 20 , 21 similar to the findings in our study.…”

Section: Discussionsupporting

confidence: 91%

“…Therefore, uniform quality of diagnosis is ensured. 17 Thirdly, only EGCs suspicious for SM invasion were analyzed, potentially leading to selection bias. The primary aim of EUS examination for EGCs is to determine the depth of tumor invasion and therefore determine the appropriate treatment option.…”

Section: Discussionmentioning

confidence: 99%

Endoscopic Ultrasonography Miniature Probe Performance for Depth Diagnosis of Early Gastric Cancer with Suspected Submucosal Invasion

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Although previous studies have reported the clinical efficacy of EUS in T-staging of EGC, the results are conflicting [7,20,21,22]. Some studies have reported that conventional endoscopy is comparable to EUS for the T-staging of EGC [6,23].…”

Section: Discussionmentioning

confidence: 99%

A Lesion-Based Convolutional Neural Network Improves Endoscopic Detection and Depth Prediction of Early Gastric Cancer

Yoon

Kim

et al. 2019

JCM

118

104

View full text Add to dashboard Cite

In early gastric cancer (EGC), tumor invasion depth is an important factor for determining the treatment method. However, as endoscopic ultrasonography has limitations when measuring the exact depth in a clinical setting as endoscopists often depend on gross findings and personal experience. The present study aimed to develop a model optimized for EGC detection and depth prediction, and we investigated factors affecting artificial intelligence (AI) diagnosis. We employed a visual geometry group(VGG)-16 model for the classification of endoscopic images as EGC (T1a or T1b) or non-EGC. To induce the model to activate EGC regions during training, we proposed a novel loss function that simultaneously measured classification and localization errors. We experimented with 11,539 endoscopic images (896 T1a-EGC, 809 T1b-EGC, and 9834 non-EGC). The areas under the curves of receiver operating characteristic curves for EGC detection and depth prediction were 0.981 and 0.851, respectively. Among the factors affecting AI prediction of tumor depth, only histologic differentiation was significantly associated, where undifferentiated-type histology exhibited a lower AI accuracy. Thus, the lesion-based model is an appropriate training method for AI in EGC. However, further improvements and validation are required, especially for undifferentiated-type histology.

show abstract

“…Various reports on the diagnostic ability of endoscopic ultrasonography (EUS) have been published. However, most reports have examined the diagnostic ability of EUS that distinguishes T1 from T2 cancer [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]; several reports have examined its diagnostic ability that distinguishes T1a from T1b cancer [24][25][26][27][28][29][30][31] and T1a/T1b1 from T1b2 cancer [31][32][33][34][35][36][37][38][39]. In addition, the number of cases included in each study was up to several hundred at most.…”

Section: Introductionmentioning

confidence: 99%

Clinical significance of endoscopic ultrasonography in diagnosing invasion depth of early gastric cancer prior to endoscopic submucosal dissection

et al. 2020

View full text Add to dashboard Cite

Background and aim Endoscopic ultrasonography is a reliable diagnostic modality for determining indications of endoscopic submucosal dissection for early gastric cancer. We aimed to clarify the clinical significance of endoscopic ultrasonography in the invasion depth diagnosis of early gastric cancer. Methods We retrospectively assessed 1598 consecutive patients with 2001 early gastric cancers who underwent EUS before ESD or surgery between October 2010 and April 2019 at our institution. Lesions were classified according to endoscopic ultrasonography-determined invasion depth as EUS-M/SM1 (lesions confined to sonographic layers 1 and 2 or lesions with changes in sonographic layer 3; depth, < 1 mm) and EUS-SM2 (lesions with changes in sonographic layer 3; depth, ≥ 1 mm). We evaluated the invasion depth determination accuracy of endoscopic ultrasonography and analyzed the clinicopathological features of misdiagnosed early gastric cancer cases. Results The invasion depth determination accuracy was as follows: EUS-M/SM1: pathological T1a/T1b1 early gastric cancer, 97%; EUS-SM2: pathological T1b2 early gastric cancer, 79%. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 95%, 98%, 69%, 97%, and 79%, respectively. In EUS-M/SM1 early gastric cancer, tumor size of ≥ 15 mm, presence of ulceration, and undifferentiated histological type were significantly associated with endoscopic ultrasonography accuracy. In EUS-SM2 early gastric cancer, tumor size of ≥ 30 mm was significantly associated with endoscopic ultrasonography accuracy. Conclusions Endoscopic ultrasonography is a useful modality in accurately determining the invasion depth of early gastric cancer before endoscopic submucosal dissection.

show abstract

Morphologic pattern analysis of submucosal deformities identified by endoscopic ultrasonography for predicting the depth of invasion in early gastric cancer

Cited by 10 publications

References 37 publications

Endoscopic Ultrasonography Miniature Probe Performance for Depth Diagnosis of Early Gastric Cancer with Suspected Submucosal Invasion

Endoscopic Ultrasonography Miniature Probe Performance for Depth Diagnosis of Early Gastric Cancer with Suspected Submucosal Invasion

A Lesion-Based Convolutional Neural Network Improves Endoscopic Detection and Depth Prediction of Early Gastric Cancer

Clinical significance of endoscopic ultrasonography in diagnosing invasion depth of early gastric cancer prior to endoscopic submucosal dissection

Contact Info

Product

Resources

About