Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?

Abstract Background To assess if radiomics can differentiate benign and malignant subsolid lung nodules (SSNs) on baseline or follow up chest CT examinations. If radiomics can differentiate between benign and malignant subsolid lung nodules, the clinical implications are shorter follow up CT imaging...

Full description

Bibliographic Details
Main Authors: Subba R. Digumarthy, Atul M. Padole, Shivam Rastogi, Melissa Price, Meghan J. Mooradian, Lecia V. Sequist, Mannudeep K. Kalra
Format: Article
Language:English
Published: BMC 2019-06-01
Series:Cancer Imaging
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40644-019-0223-7
id doaj-f3ab845e3ddf4f8bb8ffb3b36c6f3a75
record_format Article
spelling doaj-f3ab845e3ddf4f8bb8ffb3b36c6f3a752021-04-02T14:02:03ZengBMCCancer Imaging1470-73302019-06-011911810.1186/s40644-019-0223-7Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?Subba R. Digumarthy0Atul M. Padole1Shivam Rastogi2Melissa Price3Meghan J. Mooradian4Lecia V. Sequist5Mannudeep K. Kalra6Department of Radiology, Massachusetts General HospitalDepartment of Radiology, Massachusetts General HospitalDepartment of Radiology, Massachusetts General HospitalDepartment of Radiology, Massachusetts General HospitalDepartment of Medicine, Massachusetts General HospitalDepartment of Medicine, Massachusetts General HospitalDepartment of Radiology, Massachusetts General HospitalAbstract Background To assess if radiomics can differentiate benign and malignant subsolid lung nodules (SSNs) on baseline or follow up chest CT examinations. If radiomics can differentiate between benign and malignant subsolid lung nodules, the clinical implications are shorter follow up CT imaging and early recognition of lung adenocarcinoma on imaging. Materials and methods The IRB approved retrospective study included 36 patients (mean age 69 ± 8 years; 5 males, 31 females) with 108 SSNs (31benign, 77 malignant) who underwent follow up chest CT for evaluation of indeterminate SSN. All SSNs were identified on both baseline and follow up chest CT. DICOM CT images were deidentified and exported into the open access 3D Slicer software (version 4.7) to obtain radiomic features. Logistic regression analyses and receiver operating characteristic (ROC) curves for various quantitative parameters were generated with SPSS statistical software. Results Only 2/92 radiomic features (cluster shade and surface volume ratio) enabled differentiation between malignant and benign SSN on baseline chest CT (P = 0.01 and 0.03) with moderate accuracy [AUC 0.624 (0.505–0.743)]. On follow-up CT, 52/92 radiomic features were significantly different between benign and malignant SSN (P: 0.04 - < 0.0001) with improved accuracy [AUC: 0.708 (0.605–0.811), P = 0.04 - < 0.0001]. Radiomics of benign SSN were stable over time, whereas 63/92 radiomic features of malignant SSNs changed significantly between the baseline and follow up chest CT (P: 0.04 - < 0.0001). Conclusions Temporal changes in radiomic features of subsolid lung nodules favor malignant etiology over benign. The change in radiomics features of subsolid lung nodules can allow shorter follow up CT imaging and early recognition of lung adenocarcinoma on imaging. Radiomic features have limited application in differentiating benign and early malignant SSN on baseline chest CT.http://link.springer.com/article/10.1186/s40644-019-0223-7RadiomicsLung cancerSubsolid nodulesBenign and malignant lung nodulesChest CTFollow up CT
collection DOAJ
language English
format Article
sources DOAJ
author Subba R. Digumarthy
Atul M. Padole
Shivam Rastogi
Melissa Price
Meghan J. Mooradian
Lecia V. Sequist
Mannudeep K. Kalra
spellingShingle Subba R. Digumarthy
Atul M. Padole
Shivam Rastogi
Melissa Price
Meghan J. Mooradian
Lecia V. Sequist
Mannudeep K. Kalra
Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?
Cancer Imaging
Radiomics
Lung cancer
Subsolid nodules
Benign and malignant lung nodules
Chest CT
Follow up CT
author_facet Subba R. Digumarthy
Atul M. Padole
Shivam Rastogi
Melissa Price
Meghan J. Mooradian
Lecia V. Sequist
Mannudeep K. Kalra
author_sort Subba R. Digumarthy
title Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?
title_short Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?
title_full Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?
title_fullStr Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?
title_full_unstemmed Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?
title_sort predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up ct?
publisher BMC
series Cancer Imaging
issn 1470-7330
publishDate 2019-06-01
description Abstract Background To assess if radiomics can differentiate benign and malignant subsolid lung nodules (SSNs) on baseline or follow up chest CT examinations. If radiomics can differentiate between benign and malignant subsolid lung nodules, the clinical implications are shorter follow up CT imaging and early recognition of lung adenocarcinoma on imaging. Materials and methods The IRB approved retrospective study included 36 patients (mean age 69 ± 8 years; 5 males, 31 females) with 108 SSNs (31benign, 77 malignant) who underwent follow up chest CT for evaluation of indeterminate SSN. All SSNs were identified on both baseline and follow up chest CT. DICOM CT images were deidentified and exported into the open access 3D Slicer software (version 4.7) to obtain radiomic features. Logistic regression analyses and receiver operating characteristic (ROC) curves for various quantitative parameters were generated with SPSS statistical software. Results Only 2/92 radiomic features (cluster shade and surface volume ratio) enabled differentiation between malignant and benign SSN on baseline chest CT (P = 0.01 and 0.03) with moderate accuracy [AUC 0.624 (0.505–0.743)]. On follow-up CT, 52/92 radiomic features were significantly different between benign and malignant SSN (P: 0.04 - < 0.0001) with improved accuracy [AUC: 0.708 (0.605–0.811), P = 0.04 - < 0.0001]. Radiomics of benign SSN were stable over time, whereas 63/92 radiomic features of malignant SSNs changed significantly between the baseline and follow up chest CT (P: 0.04 - < 0.0001). Conclusions Temporal changes in radiomic features of subsolid lung nodules favor malignant etiology over benign. The change in radiomics features of subsolid lung nodules can allow shorter follow up CT imaging and early recognition of lung adenocarcinoma on imaging. Radiomic features have limited application in differentiating benign and early malignant SSN on baseline chest CT.
topic Radiomics
Lung cancer
Subsolid nodules
Benign and malignant lung nodules
Chest CT
Follow up CT
url http://link.springer.com/article/10.1186/s40644-019-0223-7
work_keys_str_mv AT subbardigumarthy predictingmalignantpotentialofsubsolidnodulescanradiomicspreemptlongitudinalfollowupct
AT atulmpadole predictingmalignantpotentialofsubsolidnodulescanradiomicspreemptlongitudinalfollowupct
AT shivamrastogi predictingmalignantpotentialofsubsolidnodulescanradiomicspreemptlongitudinalfollowupct
AT melissaprice predictingmalignantpotentialofsubsolidnodulescanradiomicspreemptlongitudinalfollowupct
AT meghanjmooradian predictingmalignantpotentialofsubsolidnodulescanradiomicspreemptlongitudinalfollowupct
AT leciavsequist predictingmalignantpotentialofsubsolidnodulescanradiomicspreemptlongitudinalfollowupct
AT mannudeepkkalra predictingmalignantpotentialofsubsolidnodulescanradiomicspreemptlongitudinalfollowupct
_version_ 1721563336162672640