Abstract
ObjectiveTo evaluate the effectiveness of a novel computerized quantitative analysis based on histopathological and computed tomography (CT) images for predicting the postoperative prognosis of esophageal squamous cell carcinoma (ESCC) patients.MethodsWe retrospectively reviewed the medical records of 153 ESCC patients who underwent esophagectomy alone and quantitatively analyzed digital histological specimens and diagnostic CT images. We cut pathological images (6000 × 6000) into 50 × 50 patches; each patient had 14,400 patches. Cluster analysis was used to process these patches. We used the pathological clusters to all patches ratio (PCPR) of each case for pathological features and we obtained 20 PCPR quantitative features. Totally, 125 computerized quantitative (20 PCPR and 105 CT) features were extracted. We used a recursive feature elimination approach to select features. A Cox hazard model with L1 penalization was used for prognostic indexing. We compared the following prognostic models: Model A: clinical features; Model B: quantitative CT and clinical features; Model C: quantitative histopathological and clinical features; and Model D: combined information of clinical, CT, and histopathology. Indices of concordance (C-index) and leave-one-out cross-validation (LOOCV) were used to assess prognostic model accuracy.ResultsFive PCPR and eight CT features were treated as significant indicators in ESCC prognosis. C-indices adjusted for LOOCV were comparable among four models, 0.596 (Model A) vs. 0.658 (Model B) vs. 0.651 (Model C), and improved to 0.711with Model D combining information of clinical, CT, and histopathology (all p<0.05). Using Model D, we stratified patients into low- and high-risk groups. The 3-year overall survival rates of low- and high-risk patients were 38.0% and 25.0%, respectively (p<0.001).ConclusionQuantitative prognostic modeling using a combination of clinical data, histopathological, and CT images can stratify ESCC patients with surgery alone into high-risk and low-risk groups.
Highlights
Esophageal cancer (EC) is the seventh most common cancer and the sixth leading cause of cancer-related mortality globally [1]
Five pathological clusters to all patches ratio (PCPR) and eight computed tomography (CT) features were treated as significant indicators in esophageal squamous cell carcinoma (ESCC) prognosis
C-indices adjusted for leave-one-out cross-validation (LOOCV) were comparable among four models, 0.596 (Model A) vs. 0.658 (Model B) vs. 0.651 (Model C), and improved to 0.711with Model D combining information of clinical, CT, and histopathology
Summary
Esophageal cancer (EC) is the seventh most common cancer and the sixth leading cause of cancer-related mortality globally [1]. The main histological subtypes of EC include esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EA) [1,2,3]. ESCC accounts for approximately 79% of ECs worldwide, and in China, more than 90% of all ECs are ESCCs [4, 5]. Esophagectomy is a routine treatment for ESCC in current clinical practice. The 5-year overall survival rate of ESCC is only 20–40% [6] and the postoperative care of patients with ESCC remains challenging. The current postoperative care protocol for the management of patients with ESCC needs to be optimized to improve their life expectancy
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