Comparison of CT volumetric measurement with RECIST response in patients with lung cancer

Hayes, Sara A.; Pietanza, M. Catherine; O’Driscoll, Dearbhail; Zheng, Junting; Moskowitz, Chaya S.; Kris, Mark G.; Ginsberg, Michelle S.

doi:10.1016/j.ejrad.2015.12.019

Cited by 58 publications

(46 citation statements)

References 49 publications

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“…Our results demonstrated that the total tumor volume and mean tumor density obtained using volumetric measurements correlated better with PFS than tumor size of RECIST 1.1. Similar results have been reported elsewhere [ 18 , 25 ]. Hayes et al reported superiority of volumetric measurements over use of unidimensional RECIST criteria to predict overall survival [ 25 ].…”

Section: Discussionsupporting

confidence: 93%

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Combined Volumetric and Density Analyses of Contrast-Enhanced CT Imaging to Assess Drug Therapy Response in Gastroenteropancreatic Neuroendocrine Diffuse Liver Metastasis

Wang

Huang

Chen

et al. 2018

Contrast Media & Molecular Imaging

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Objective We propose a computer-aided method to assess response to drug treatment, using CT imaging-based volumetric and density measures in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and diffuse liver metastases. Methods Twenty-five patients with GEP-NETs with diffuse liver metastases were enrolled. Pre- and posttreatment CT examinations were retrospectively analyzed. Total tumor volume (volume) and mean volumetric tumor density (density) were calculated based on tumor segmentation on CT images. The maximum axial diameter (tumor size) for each target tumor was measured on pre- and posttreatment CT images according to Response Evaluation Criteria In Solid Tumors (RECIST). Progression-free survival (PFS) for each patient was measured and recorded. Results Correlation analysis showed inverse correlation between change of volume and density (Δ(V + D)), change of volume (ΔV), and change of tumor size (ΔS) with PFS (r = −0.653, P=0.001; r = −0.617, P=0.003; r = −0.548, P=0.01, respectively). There was no linear correlation between ΔD and PFS (r = −0.226, P=0.325). Conclusion The changes of volume and density derived from CT images of all lesions showed a good correlation with PFS and may help assess treatment response.

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Section: Discussionsupporting

confidence: 93%

“…Similar results have been reported elsewhere [ 18 , 25 ]. Hayes et al reported superiority of volumetric measurements over use of unidimensional RECIST criteria to predict overall survival [ 25 ]. Welsh et al also suggested volumetric analysis as the preferred method to detect tumor progression [ 18 ].…”

Section: Discussionsupporting

confidence: 93%

Combined Volumetric and Density Analyses of Contrast-Enhanced CT Imaging to Assess Drug Therapy Response in Gastroenteropancreatic Neuroendocrine Diffuse Liver Metastasis

Wang

Huang

Chen

et al. 2018

Contrast Media & Molecular Imaging

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“…For example, some studies have shown discordance between response criteria and volume measurements in the classification of tumour response assessment. 27,28 While some have found that 3D or volumetric measures for tumour response appear to be the superior method, 16,[29][30][31][32] other authors have shown no difference in comparison to unidimensional measurements, and thus careful attention to the clinical scenario or application, as well as further validation and correlation with outcomes is needed to establish this resource-intensive measurement technique.…”

Section: Response To Therapymentioning

confidence: 99%

Volumetric analysis at abdominal CT: oncologic and non-oncologic applications

Planz¹,

Lubner²,

Pickhardt

2019

BJR

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Volumetric analysis is an objective three-dimensional assessment of a lesion or organ that may more accurately depict the burden of complex objects compared to traditional linear size measurement. Small changes in linear size are amplified by corresponding changes in volume, which could have significant clinical implications. Though early methods of calculating volumes were time-consuming and laborious, multiple software platforms are now available with varying degrees of user-software interaction ranging from manual to fully automated. For the assessment of primary malignancy and metastatic disease, volumetric measurements have shown utility in the evaluation of disease burden prior to and following therapy in a variety of cancers. Additionally, volume can be useful in treatment planning prior to resection or locoregional therapies, particularly for hepatic tumours. The utility of CT volumetry in a wide spectrum of non-oncologic pathology has also been described. While clear advantages exist in certain applications, some data have shown that volume is not always the superior method of size assessment and the associated labor intensity may not be worthwhile. Further, lack of uniformity among software platforms is a challenge to widespread implementation. This review will discuss CT volumetry and its potential oncologic and non-oncologic applications in abdominal imaging, as well as advantages and limitations to this quantitative technique.

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“…Accurate radiological assessment for predicting therapeutic responses and clinical outcomes of non-small cell lung cancer (NSCLC) is important in clinical practice and drug development trials 1 . Cancers have uneven growth patterns, and even within single tumors specific areas may increase in size while other portions remain stable.…”

Section: Introductionmentioning

confidence: 99%

Prognostic Impact of Longitudinal Monitoring of Radiomic Features in Patients with Advanced Non-Small Cell Lung Cancer

Bak

Park

Sohn

et al. 2019

Sci Rep

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Tumor growth dynamics vary substantially in non-small cell lung cancer (NSCLC). We aimed to develop biomarkers reflecting longitudinal change of radiomic features in NSCLC and evaluate their prognostic power. Fifty-three patients with advanced NSCLC were included. Three primary variables reflecting patterns of longitudinal change were extracted: area under the curve of longitudinal change (AUC1), beta value reflecting slope over time, and AUC2, a value obtained by considering the slope and area over the longitudinal change of features. We constructed models for predicting survival with multivariate cox regression, and identified the performance of these models. AUC2 exhibited an excellent correlation between patterns of longitudinal volume change and a significant difference in overall survival time. Multivariate regression analysis based on cut-off values of radiomic features extracted from baseline CT and AUC2 showed that kurtosis of positive pixel values and surface area from baseline CT, AUC2 of density, skewness of positive pixel values, and entropy at inner portion were associated with overall survival. For the prediction model, the areas under the receiver operating characteristic curve (AUROC) were 0.948 and 0.862 at 1 and 3 years of follow-up, respectively. Longitudinal change of radiomic tumor features may serve as prognostic biomarkers in patients with advanced NSCLC.

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Comparison of CT volumetric measurement with RECIST response in patients with lung cancer

Cited by 58 publications

References 49 publications

Combined Volumetric and Density Analyses of Contrast-Enhanced CT Imaging to Assess Drug Therapy Response in Gastroenteropancreatic Neuroendocrine Diffuse Liver Metastasis

Combined Volumetric and Density Analyses of Contrast-Enhanced CT Imaging to Assess Drug Therapy Response in Gastroenteropancreatic Neuroendocrine Diffuse Liver Metastasis

Volumetric analysis at abdominal CT: oncologic and non-oncologic applications

Prognostic Impact of Longitudinal Monitoring of Radiomic Features in Patients with Advanced Non-Small Cell Lung Cancer

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