A pilot study of volume measurement as a method of tumor response evaluation to aid biomarker development.
OBJECTIVE
Tissue biomarker discovery is potentially limited by conventional tumor measurement techniques, which have an uncertain ability to accurately distinguish sensitive and resistant tumors. Semiautomated volumetric measurement of computed tomography imaging has the potential to more accurately capture tumor growth dynamics, allowing for more exact separation of sensitive and resistant tumors and a more accurate comparison of tissue characteristics.


METHODS
Forty-eight patients with early stage non-small cell lung cancer and clinical characteristics of sensitivity to gefitinib were studied. High-resolution computed tomography was done at baseline and after 3 weeks of gefitinib. Tumors were then resected and molecularly profiled. Unidimensional and volumetric measurements were done using a semiautomated algorithm. Measurement changes were evaluated for their ability to differentiate tumors with and without sensitizing mutations.


RESULTS
Forty-four percent of tumors had epidermal growth factor receptor-sensitizing mutations. Receiver operating characteristic curve analysis showed that volumetric measurement had a higher area under the curve than unidimensional measurement for identifying tumors harboring sensitizing mutations (P = 0.009). Tumor volume decrease of >24.9% was the imaging criteria best able to classify tumors with and without sensitizing mutations (sensitivity, 90%; specificity, 89%).


CONCLUSIONS
Volumetric tumor measurement was better than unidimensional tumor measurement at distinguishing tumors based on presence or absence of a sensitizing mutation. Use of volume-based response assessment for the development of tissue biomarkers could reduce contamination between sensitive and resistant tumor populations, improving our ability to identify meaningful predictors of sensitivity.
Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. bz2166@columbia.edu
Binsheng
B
Zhao
Geoffrey R
GR
Oxnard
Chaya S
CS
Moskowitz
Mark G
MG
Kris
William
W
Pao
Pingzhen
P
Guo
Valerie M
VM
Rusch
Marc
M
Ladanyi
Naiyer A
NA
Rizvi
Lawrence H
LH
Schwartz
D000970:Antineoplastic Agents / Q000627:therapeutic use; D054316:Biomarkers, Pharmacological / Q000032:analysis*; D014408:Biomarkers, Tumor / Q000032:analysis / Q000302:isolation & purification*; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging* / Q000188:drug therapy / Q000473:pathology*; D018450:Disease Progression; D019008:Drug Resistance, Neoplasm; D000077156:Gefitinib; D006801:Humans; D021621:Imaging, Three-Dimensional; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000188:drug therapy / Q000473:pathology*; D010865:Pilot Projects; D011379:Prognosis; D011799:Quinazolines / Q000627:therapeutic use; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods; D047368:Tumor Burden
D000970:Antineoplastic Agents; D054316:Biomarkers, Pharmacological; D014408:Biomarkers, Tumor; D011799:Quinazolines; D000077156:Gefitinib