Dataset Information

Synchronous resection of 12 small pulmonary nodules guided by a noninvasive 3D printed emulation model: A case report.

ABSTRACT: Localization of multiple small pulmonary nodules is the major obstacle in surgical resection. Here, we report a novel noninvasive localization technique based on a life-size 3D printed "emulation pulmonary nodule localization model" which is simple and efficient. In the case reported here of a patient with synchronous multiple pulmonary nodules, the nodules were successfully and conveniently localized without any trauma by navigation of the emulation localization model. All 12 nodules were resected precisely and thoroughly, while normal lung tissues were considerably well preserved. Pathological examination confirmed malignancy of the major nodule and some other small nodules.

SUBMITTER: Li K

PROVIDER: S-EPMC9346182 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Synchronous resection of 12 small pulmonary nodules guided by a noninvasive 3D printed emulation model: A case report.

Li Kaidi K Ding Ningying N Xu Yuyang Y Guo Chenglin C Liu Chengwu C Mei Jiandong J Liu Lunxu L

Thoracic cancer 20220621 15

Localization of multiple small pulmonary nodules is the major obstacle in surgical resection. Here, we report a novel noninvasive localization technique based on a life-size 3D printed "emulation pulmonary nodule localization model" which is simple and efficient. In the case reported here of a patient with synchronous multiple pulmonary nodules, the nodules were successfully and conveniently localized without any trauma by navigation of the emulation localization model. All 12 nodules were resec ...[more]

PMID: 35730109

Similar Datasets

Project description:BACKGROUNDCurrent clinical management of patients with pulmonary nodules involves either repeated low-dose CT (LDCT)/CT scans or invasive procedures, yet causes significant patient misclassification. An accurate noninvasive test is needed to identify malignant nodules and reduce unnecessary invasive tests.METHODWe developed a diagnostic model based on targeted DNA methylation sequencing of 389 pulmonary nodule patients' plasma samples and then validation in 140 plasma samples independently. We tested the model in different stages and subtypes of pulmonary nodules.RESULTSA 100-feature model was developed and validated for pulmonary nodule diagnosis; the model achieved a receiver operating characteristic curve-AUC (ROC-AUC) of 0.843 on 140 independent validation samples, with an accuracy of 0.800. The performance was well maintained in (a) a 6 to 20 mm size subgroup (n = 100), with a sensitivity of 1.000 and adjusted negative predictive value (NPV) of 1.000 at 10% prevalence; (b) stage I malignancy (n = 90), with a sensitivity of 0.971; (c) different nodule types: solid nodules (n = 78) with a sensitivity of 1.000 and adjusted NPV of 1.000, part-solid nodules (n = 75) with a sensitivity of 0.947 and adjusted NPV of 0.983, and ground-glass nodules (n = 67) with a sensitivity of 0.964 and adjusted NPV of 0.989 at 10% prevalence. This methylation test, called PulmoSeek, outperformed PET-CT and 2 clinical prediction models (Mayo Clinic and Veterans Affairs) in discriminating malignant pulmonary nodules from benign ones.CONCLUSIONThis study suggests that the blood-based DNA methylation model may provide a better test for classifying pulmonary nodules, which could help facilitate the accurate diagnosis of early stage lung cancer from pulmonary nodule patients and guide clinical decisions.FUNDINGThe National Key Research and Development Program of China; Science and Technology Planning Project of Guangdong Province; The National Natural Science Foundation of China National.

Dataset Information

Synchronous resection of 12 small pulmonary nodules guided by a noninvasive 3D printed emulation model: A case report.

Publications

Synchronous resection of 12 small pulmonary nodules guided by a noninvasive 3D printed emulation model: A case report.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets