Inferring Positions of Tumor and Nodes in Stage III Lung Cancer From Multiple Anatomical Surrogates Using Four-Dimensional Computed Tomography

Journal Article · Sun Aug 01 00:00:00 EDT 2010 · International Journal of Radiation Oncology, Biology and Physics

DOI:https://doi.org/10.1016/j.ijrobp.2009.12.064· OSTI ID:21436129

Malinowski, Kathleen T ^[1]; Pantarotto, Jason R ^[2]; Senan, Suresh ^[2]

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1. Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD (United States)
2. Department of Radiation Oncology, VU University Medical Center, Amsterdam (Netherlands)

Purpose: To investigate the feasibility of modeling Stage III lung cancer tumor and node positions from anatomical surrogates. Methods and Materials: To localize their centroids, the primary tumor and lymph nodes from 16 Stage III lung cancer patients were contoured in 10 equal-phase planning four-dimensional (4D) computed tomography (CT) image sets. The centroids of anatomical respiratory surrogates (carina, xyphoid, nipples, mid-sternum) in each image set were also localized. The correlations between target and surrogate positions were determined, and ordinary least-squares (OLS) and partial least-squares (PLS) regression models based on a subset of respiratory phases (three to eight randomly selected) were created to predict the target positions in the remaining images. The three-phase image sets that provided the best predictive information were used to create models based on either the carina alone or all surrogates. Results: The surrogate most correlated with target motion varied widely. Depending on the number of phases used to build the models, mean OLS and PLS errors were 1.0 to 1.4 mm and 0.8 to 1.0 mm, respectively. Models trained on the 0%, 40%, and 80% respiration phases had mean ({+-} standard deviation) PLS errors of 0.8 {+-} 0.5 mm and 1.1 {+-} 1.1 mm for models based on all surrogates and carina alone, respectively. For target coordinates with motion >5 mm, the mean three-phase PLS error based on all surrogates was 1.1 mm. Conclusions: Our results establish the feasibility of inferring primary tumor and nodal motion from anatomical surrogates in 4D CT scans of Stage III lung cancer. Using inferential modeling to decrease the processing time of 4D CT scans may facilitate incorporation of patient-specific treatment margins.

• OSTI ID: 21436129
• Journal Information: International Journal of Radiation Oncology, Biology and Physics, Vol. 77, Issue 5; Other Information: DOI: 10.1016/j.ijrobp.2009.12.064; PII: S0360-3016(10)00014-3; Copyright (c) 2010 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; ISSN 0360-3016
• Country of Publication: United States
• Language: English

Related Subjects

62 RADIOLOGY AND NUCLEAR MEDICINE
CAT SCANNING
FOUR-DIMENSIONAL CALCULATIONS
LEAST SQUARE FIT
LUNGS
LYMPH NODES
NEOPLASMS
RESPIRATION
SIMULATION
BODY
COMPUTERIZED TOMOGRAPHY
DIAGNOSTIC TECHNIQUES
DISEASES
LYMPHATIC SYSTEM
MATHEMATICAL SOLUTIONS
MAXIMUM-LIKELIHOOD FIT
NUMERICAL SOLUTION
ORGANS
RESPIRATORY SYSTEM
TOMOGRAPHY