scholarly journals Impact of Interobserver Variability in Manual Segmentation of Non-Small Cell Lung Cancer (NSCLC) Applying Low-Rank Radiomic Representation on Computed Tomography

Cancers ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 5985
Author(s):  
Michelle Hershman ◽  
Bardia Yousefi ◽  
Lacey Serletti ◽  
Maya Galperin-Aizenberg ◽  
Leonid Roshkovan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Interobserver Variability ◽  
Pearson Correlation ◽  
Small Cell ◽  
Low Rank ◽  
Imaging Biomarkers ◽  
Manual Segmentation ◽  
Small Cell Lung

This study tackles interobserver variability with respect to specialty training in manual segmentation of non-small cell lung cancer (NSCLC). Four readers included for segmentation are: a data scientist (BY), a medical student (LS), a radiology trainee (MH), and a specialty-trained radiologist (SK) for a total of 295 patients from two publicly available databases. Sørensen–Dice (SD) coefficients and low rank Pearson correlation coefficients (CC) of 429 radiomics were calculated to assess interobserver variability. Cox proportional hazard (CPH) models and Kaplan-Meier (KM) curves of overall survival (OS) prediction for each dataset were also generated. SD and CC for segmentations demonstrated high similarities, yielding, SD: 0.79 and CC: 0.92 (BY-SK), SD: 0.81 and CC: 0.83 (LS-SK), and SD: 0.84 and CC: 0.91 (MH-SK) in average for both databases, respectively. OS through the maximal CPH model for the two datasets yielded c-statistics of 0.7 (95% CI) and 0.69 (95% CI), while adding radiomic and clinical variables (sex, stage/morphological status, and histology) together. KM curves also showed significant discrimination between high- and low-risk patients (p-value < 0.005). This supports that readers’ level of training and clinical experience may not significantly influence the ability to extract accurate radiomic features for NSCLC on CT. This potentially allows flexibility in the training required to produce robust prognostic imaging biomarkers for potential clinical translation.

Exploration of Imaging Biomarkers for Predicting Survival of Patients With Advanced Non–Small Cell Lung Cancer Treated With Antiangiogenic Chemotherapy

2016 ◽  
Vol 206 (5) ◽  
pp. 987-993 ◽  
Author(s):  
Koichi Hayano ◽  
Naveen M. Kulkarni ◽  
Dan G. Duda ◽  
Rebecca Suk Heist ◽  
Dushyant V. Sahani
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Imaging Biomarkers ◽  
Small Cell Lung

First-pass perfusion of non-small-cell lung cancer (NSCLC) with 64-detector-row CT: a study of technique repeatability and intra- and interobserver variability

2013 ◽  
Vol 119 (1) ◽  
pp. 4-12 ◽  
Author(s):  
Anna Rita Larici ◽  
Lucio Calandriello ◽  
Michele Amato ◽  
Roberta Silvestri ◽  
Annemilia del Ciello ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Interobserver Variability ◽  
Small Cell ◽  
Small Cell Lung ◽  
Pass Perfusion ◽  
First Pass ◽  
First Pass Perfusion

scholarly journals Comparison of immunohistochemical tests in the CLOVER study by Russian society of clinical oncology

2020 ◽  
Vol 9 (4) ◽  
pp. 25-31
Author(s):  
L. E. Zavalishina ◽  
P. E. Povilaitite ◽  
N. A. Savelov ◽  
Yu. Yu. Andreeva ◽  
A. V. Petrov ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Clinical Oncology ◽  
Cell Lung Cancer ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Pairwise Comparison ◽  
Small Cell ◽  
Russian Society ◽  
Small Cell Lung

Introduction. The goal of the CLOVER study performed by the Russian Society of Clinical Oncology, was a pairwise comparison of three validated PD-L1 immunohistochemical (IHC) tests (Ventana SP142, Ventana SP263, Dako 22C3) in the patient population with non-small cell lung cancer (NSCLC). This study is the first large Russian comparative study to evaluate PD-L1 expression levels using immunohistochemistry methods.Materials and methods. The study was conducted on 473 NSCLC samples from Biobank. The IHC tests were carried out with 3 antibody clones. Four trained pathologists independently evaluated the percentage of positively stained tumor cells (TC) and immune cells (IC). To assess the correlation of TC and IC between different runs and the prognostic values of one test for another, a concordant analysis was used.Results. The number of PD-L1‑positive cells (≥1 %) was higher among IC compared with TC in all three IHC tests. Pearson correlation coefficients (PCC) for TCs were 0.71, 0.87, and 0.75 for 22C3 / SP142, 22C3 / SP263 and SP263 / SP142, respectively. PCC values for ICs were 0.45, 0.61, and 0.68 for the same pairs. A high coincidence of positive and negative results (>91 %) was obtained between the staining with antibodies 22C3 and SP263 of immunooncological agents in the 1st line.Conclusions. The highest correlation between IHC tests was obtained by pairwise comparison of 22C3 and SP263. Clone 22C3 can be considered as a substitute for SP263 in the first-line treatment of NSCLC. Clone SP142 showed weaker expression in TC and IC compared to the other two tests in patients with non-small cell lung cancer.

scholarly journals Multicentre study on the consistency of PD-L1 immunohistochemistry as predictive test for immunotherapy in non-small cell lung cancer

2019 ◽  
Vol 73 (7) ◽  
pp. 423-430
Author(s):  
Rogier Butter ◽  
Nils A 't Hart ◽  
Gerrit K J Hooijer ◽  
Kim Monkhorst ◽  
Ernst-Jan Speel ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Interobserver Variability ◽  
Small Cell ◽  
Predictive Test ◽  
Small Cell Lung ◽  
Resected Nsclc ◽  
Interlaboratory Variability ◽  
The Impact

AimsInvestigate the impact of interlaboratory- and interobserver variability of immunohistochemistry on the assessment of programmed death ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC).MethodsTwo tissue microarrays (TMAs) were constructed from 50 (TMA-A) and 51 (TMA-B) resected NSCLC cases, and distributed among eight centres. Immunostaining for PD-L1 was performed using Agilent’s 22C3 pharmDx Assay (pharmDx) and/or a 22C3 laboratory developed test (LDT). The interlaboratory variability of staining- and interobserver variability of scoring for PD-L1 were assessed in selected critical samples (samples at the cut-off of positivity) and non-critical samples. Also, PD-L1 epitope deterioration in time in stored unstained slides was analysed. Krippendorff’s alpha values (0=maximal, 1=no variability) were calculated as measure for variability.ResultsFor interlaboratory variability of immunostaining, the percentage of PD-L1 positive cases among centres ranged 40%–51% (1% cut-off) and 23%–30% (50% cut-off). Alpha values at 1% cut-off were 0.88 (pharmDx) and 0.87 (LDT) and at 50% cut-off 0.82 (pharmDx) and 0.95 (LDT). Interobserver variability of scoring resulted in PD-L1 positive cases ranging 29%–55% (1% cut-off) and 14%–30% (50% cut-off) among pathologists. Alpha values were at 1% cut-off 0.83 (TMA-A) and 0.66 (TMA-B), and at 50% cut-off 0.77 (TMA-A) and 0.78 (TMA-B). Interlaboratory variability of staining was higher (p<0.001) in critical samples than in non-critical samples at 50% cut-off. Furthermore, PD-L1 epitope deterioration in unstained slides was observed after 12 weeks.ConclusionsThe results provide insight in factors contributing to variability of immunohistochemical assessment of PD-L1, and contribute to more reliable predictive testing for PD-L1.

scholarly journals Role of imaging biomarkers in mutation-driven non-small cell lung cancer

2020 ◽  
Vol 11 (7) ◽  
pp. 412-427
Author(s):  
Dexter P Mendoza ◽  
Zofia Piotrowska ◽  
Jochen K Lennerz ◽  
Subba R Digumarthy
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Imaging Biomarkers ◽  
Small Cell Lung
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