Y Lao¹*, R Tuli¹ , J David¹ , A Mirhadi¹ , N Lepore² , H Sandler¹ , Y Wang³ , W Yang¹ , (1)Cedars Sinai Medical Center, Los Angeles, California, (2) Children's Hospital Los Angeles, Los Angeles, California, (3) Arizona State University, Tempe, Arizona

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  Y Lao

(Sunday, 7/29/2018) 4:00 PM - 4:55 PM

Room: Room 205

Purpose: Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are two major sub-types of non-small cell lung cancer with different treatment options. Definitive pretreatment histopathological diagnosis is needed, while traditional invasive diagnostic techniques have either low specificity or various contraindications. Based on 4D-CT, this study aims to characterize the pattern of morphological changes in lung tumors during respiration, and investigate its potential in non-invasively differentiating lung AC and SCC.

Methods: We applied a 3D surface analysis on 22 tumors (13 AC, 9 SCC) to investigate the tumor regional morphological fluctuations in response to respiration phases. Tumor surface vertices among 10 respiratory phases were matched using surface based registration, and the shape descriptors ( Ï? and detJ) were calculated and tracked across respiration stages in a regionally aligned scenario. Specifically, Ï? described the radius of the corresponding vertex in the normal direction, and detJ represented the extent of local surface warping from the registration. Pair-wise group comparisons were performed between lung AC and SCC subtypes, in terms of ratios of maximal shape changes (M1) as well as correlation coefficients between tumor shape and respiratory stage indicators from the lung (M2).

Results: AC type tumors had averaged larger surface measurements at exhale than at inhale, and these surface measurements were on average negatively correlated with lung volumes across respiratory stages (RÏ?-Vlung=-0.23±0.41, RdetJ-Vlung=-0.06±0.32). In contrast, SCC type tumors had averaged smaller surface measurements at exhale than at inhale, and the correlations with lung volumes were positive (RÏ?-Vlung=0.34±0.19, RdetJ-Vlung=0.43±0.20). The group differences in maximal shape changes as well as correlations were both statistically significant (p < 0.05).

Conclusion: We developed a non-invasive lung tumor subtype detection pipeline based on respiration induced tumor surface deformation. Significant differences in deformation patterns were detected between lung AC and SCC.

Keywords

Not Applicable / None Entered.

Taxonomy

IM- CT: Biomarkers

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