Elsevier

Lung Cancer

Volume 23, Issue 2, February 1999, Pages 105-114
Lung Cancer

Multimodality nuclear medicine imaging in three-dimensional radiation treatment planning for lung cancer: challenges and prospects

https://doi.org/10.1016/S0169-5002(99)00005-7Get rights and content

Abstract

The purpose of this study was to determine the utility of quantitative single photon emission computed tomography (SPECT) lung perfusion scans and F-18 fluorodeoxyglucose positron emission computed tomography (PET) during X-ray computed tomography (CT)-based treatment planning for patients with lung cancer. Pre-radiotherapy SPECT (n=104) and PET (n=35) images were available to the clinician to assist in radiation field design for patients with bronchogenic cancer. The SPECT and PET scans were registered with anatomic information derived from CT. The information from SPECT and PET provides the treatment planner with functional data not seen with CT. SPECT yields three-dimensional (3D) lung perfusion maps. PET provides 3D metabolic images that assist in tumor localization. The impact of the nuclear medicine images on the treatment planning process was assessed by determining the frequency, type, and extent of changes to plans. Pre-radiotherapy SPECT scans were used to modify 11 (11%) treatment plans; primarily altering beam angles to avoid highly functioning tissue. Fifty (48%) SPECT datasets were judged to be ‘potentially useful’ due to the detection of hypoperfused regions of the lungs, but were not used during treatment planning. PET data influenced 34% (12 of 35) of the treatment plans examined, and resulted in enlarging portions of the beam aperture (margins) up to 15 mm. Challenges associated with image quality and registration arise when utilizing nuclear medicine data in the treatment planning process. Initial implementation of advanced SPECT image reconstruction techniques that are not typically used in the clinic suggests that the reconstruction method may influence dose response data derived from the SPECT images and improve image registration with CT. The use of nuclear medicine transmission computed tomography (TCT) for both SPECT and PET is presented as a possible tool to reconstruct more accurate emission images and to aid in the registration of emission data with the planning CT. Nuclear medicine imaging techniques appear to be a potentially valuable tool during radiotherapy treatment planning for patients with lung cancer. The utilization of accurate nuclear medicine image reconstruction techniques and TCT may improve the treatment planning process.

Introduction

Traditional radiation treatment planning relies on density imaging such as chest radiographs and X-ray computed tomography (CT) for anatomic information of structures of interest, including target and normal tissues. Recent advances in functional imaging have raised the possibility of redefining the treatment planning process by including or excluding particular areas based on their function. For example, the use of single photon emission computed tomography (SPECT) perfusion imaging has been explored to avoid perfused lung tissue during radiotherapy [1]. Nuclear medicine data has also been used to examine radiation-induced changes in perfusion [2], [3], [4] and to localize monoclonal antibody uptake [5], [6]. Functional magnetic resonance imaging (MRI) and/or positron emission computed tomography (PET) has been used to determine the target volume during treatment planning of patients with brain tumors [7], [8], [9], [10], [11], [12] or lung cancer [13]. Another group has reported on the general use of multiple imaging modalities for 3D treatment planning [14].

We herein update our experience using functional nuclear medicine imaging to assist with radiation therapy treatment planning for patients with lung cancer. Both SPECT lung perfusion imaging (to define regional lung function) and PET (to more accurately defining targets) are addressed. Challenges and proposed solutions to the use of SPECT and PET imaging in treatment planning are discussed. As a result of this investigation, the utility and advantages of using quantitatively accurate nuclear medicine image reconstruction techniques and nuclear medicine transmission computed tomography (TCT) to improved image accuracy and registration were examined.

Section snippets

Methods

A retrospective review was conducted of patients with lung cancer treated at our institution between 1990 and 1997 that also had pre-radiotherapy SPECT (n=104) and PET (n=35) studies. This was a subset of the 603 patients treated with curative intent for lung cancer at our institution during the same time period. The nuclear medicine scans were obtained as part of IRB approved clinical trials and informed consent was obtained. The trials enrolled cases of curative intent, with intact gross

SPECT

One hundred and four patients (59 males and 45 females) with a mean age of 63.3 years were studied with SPECT imaging. This SPECT data is an update on a previous report describing the use of SPECT perfusion images to aid in the treatment planning process [1], [15]. In 11 of 104 patients (11%) SPECT perfusion data resulted in a change of beam orientation to reduce incidental irradiation of well-perfused regions of the lung, while maintaining tumor coverage. Fig. 1 illustrates a case in which

Discussion

Integration of SPECT and PET imaging into traditional CT treatment planning for lung cancer has the potential to more accurately delineate normal lung tissue and target volumes. Eleven of 104 patients had their plans changed due to the functional information provided by SPECT. In general, these 11 patients had extremely poor pre-radiotherapy pulmonary function as the motivation to address the treatment plan based on the SPECT data. Given the clinical uncertainty as to the application of the

Conclusions

This study investigated the integration of CT, SPECT and PET image data during 3D treatment planning for patients with lung cancer. The functional nuclear medicine studies appear to complement CT information and hopefully will result in improved treatment plans with decreases in morbidity. The use of advanced SPECT image reconstruction techniques was explored in hopes of enhancing their utility in clinical radiotherapy. More accurate images may result in better dose response models. Nuclear

Acknowledgements

The authors thank Kim Greer, CNMT, for SPECT data acquisition and processing, Phil Antoine for his help with image processing, and Robert Clough for his assistance with data management. This work was supported, in part, by Public Health Service grants RO1-CA33541 and R29-CA69579, awarded by the National Cancer Institute, and Department of Energy grant DE-FG02-96ER62150. The image processing software SPECTER was used as a tool for the SPECT image analysis.

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