Objective: This article aimed to differentiate noncalcified hamartoma from pulmonary carcinoid preoperatively using computed tomography (CT) radiomics approaches.
Materials And Methods: The unenhanced CT (UECT) and contrast-enhanced CT (CECT) data of noncalcified hamartoma (n = 73) and pulmonary carcinoid (n = 54; typical/atypical carcinoid = 13/41) were retrospectively analyzed. The patients were randomly divided into the training and validation sets. A total of 396 radiomics features were extracted from UECT and CECT, respectively. The features were selected by using the minimum redundancy maximum relevance and the least absolute shrinkage and selection operator to construct a radiomics model. Clinical factors and radiomics features were integrated to build a nomogram model. The performance of clinical factors, radiomics, and nomogram models on the differential diagnosis between noncalcified hamartoma and carcinoid were investigated. Diagnostic performance of radiologists was also explored.
Result: In regard to distinguishing noncalcified hamartoma from carcinoid, the areas under the receiver operating characteristic curves of the clinical, radiomics, and nomogram models were 0.88, 0.94, and 0.96 in the training set UECT, and were 0.85, 0.92, and 0.96 in the training set CECT, respectively. The areas under the curve of the 3 models were 0.89, 0.96, and 0.96 in the validation set UECT, and were 0.79, 0.90, and 0.94 in the validation set CECT, respectively. The nomogram model exhibited good calibration and was clinically useful by decision curve analysis. Nomogram did not show significant improvement compared with radiomics, neither for UECT nor for CECT. Diagnostic performance of radiologists was lower than both radiomics and nomogram model.
Conclusions: Radiomics approaches may be useful in distinguishing peripheral pulmonary noncalcified hamartoma from carcinoid. Radiomics features extracted from CECT provided no significant benefit when compared with UECT.
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http://dx.doi.org/10.1097/RCT.0000000000001414 | DOI Listing |
Int J Surg
August 2024
Department of Thoracic Surgery, First Medical Center, Chinese General Hospital of PLA, Beijing.
Background: Clinical differentiation between pulmonary metastases and noncalcified pulmonary hamartomas (NCPH) often presents challenges, leading to potential misdiagnosis. However, the efficacy of a comprehensive model that integrates clinical features, radiomics, and deep learning (CRDL) for differential diagnosis of these two diseases remains uncertain.
Objective: This study evaluated the diagnostic efficacy of a CRDL model in differentiating pulmonary metastases from NCPH.
J Comput Assist Tomogr
May 2023
From the Departments of Radiology.
Objective: This article aimed to differentiate noncalcified hamartoma from pulmonary carcinoid preoperatively using computed tomography (CT) radiomics approaches.
Materials And Methods: The unenhanced CT (UECT) and contrast-enhanced CT (CECT) data of noncalcified hamartoma (n = 73) and pulmonary carcinoid (n = 54; typical/atypical carcinoid = 13/41) were retrospectively analyzed. The patients were randomly divided into the training and validation sets.
Sci Rep
March 2021
Division of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, 3-1-3 Hongo, Bunkyo-ku, Tokyo, 113-8431, Japan.
Lymphangioleiomyomatosis (LAM) is a rare destructive lung disease characterized by multiple thin-walled pulmonary cysts. The currently proposed diagnostic algorithm emphasizes the characteristic cystic appearance on high-resolution computed tomography (HRCT) so uncommon HRCT appearances present challenges to establishing the proper LAM diagnosis. The objective of this study is to accrue uncommon chest HRCT appearances, determine frequencies in both tuberous sclerosis complex (TSC)-associated LAM (TSC-LAM) and sporadic LAM (S-LAM) patients.
View Article and Find Full Text PDFFront Oncol
October 2020
Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Background: Patients with non-calcified hamartoma were more susceptible to surgery or needle biopsy for the tough discrimination from lung adenocarcinoma. Radiomics have the ability to quantify the lesion features and potentially improve disease diagnosis. Thus, this study aimed to discriminate non-calcified hamartoma from adenocarcinoma by employing imaging quantification and machine learning.
View Article and Find Full Text PDFGraefes Arch Clin Exp Ophthalmol
April 2020
Department of Ophthalmology, Key laboratory of Ocular Fundus Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 1# Shuai Fu Yuan, Dongcheng District, Beijing, 100730, China.
Purpose: To investigate the clinical features and spectral-domain optical coherence tomography (SD-OCT) findings of retinal astrocytic hamartoma (RAH) in Chinese patients with tuberous sclerosis complex (TSC).
Methods: The medical records of 91 consecutive patients with established TSC diagnosis were retrospectively reviewed. Fundus findings regarding RAH documented by fundus photography and SD-OCT at presentation were collected and analyzed.
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