Literature DB >> 10217614

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

M T Munley1, L B Marks, C Scarfone, G S Sibley, E F Patz, T G Turkington, R J Jaszczak, D R Gilland, M S Anscher, R E Coleman.   

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.

Entities:  

Mesh:

Year:  1999        PMID: 10217614     DOI: 10.1016/s0169-5002(99)00005-7

Source DB:  PubMed          Journal:  Lung Cancer        ISSN: 0169-5002            Impact factor:   5.705


  21 in total

Review 1.  PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques.

Authors:  Habib Zaidi; Issam El Naqa
Journal:  Eur J Nucl Med Mol Imaging       Date:  2010-03-25       Impact factor: 9.236

2.  [18F]FDG uptake and PCNA, Glut-1, and Hexokinase-II expressions in cancers and inflammatory lesions of the lung.

Authors:  Marcelo Mamede; Tatsuya Higashi; Masanori Kitaichi; Koichi Ishizu; Takayoshi Ishimori; Yuji Nakamoto; Kazuhiro Yanagihara; Mio Li; Fumihiro Tanaka; Hiromi Wada; Toshiaki Manabe; Tsuneo Saga
Journal:  Neoplasia       Date:  2005-04       Impact factor: 5.715

Review 3.  Technological development and advances in single-photon emission computed tomography/computed tomography.

Authors:  Youngho Seo; Carina Mari; Bruce H Hasegawa
Journal:  Semin Nucl Med       Date:  2008-05       Impact factor: 4.446

4.  PET-CT in the staging and treatment of non-small-cell lung cancer.

Authors:  Patricia Ibeas; Blanca Cantos; José Manuel Gasent; Begoña Rodríguez; Mariano Provencio
Journal:  Clin Transl Oncol       Date:  2011-06       Impact factor: 3.405

5.  Computer-aided diagnosis systems for lung cancer: challenges and methodologies.

Authors:  Ayman El-Baz; Garth M Beache; Georgy Gimel'farb; Kenji Suzuki; Kazunori Okada; Ahmed Elnakib; Ahmed Soliman; Behnoush Abdollahi
Journal:  Int J Biomed Imaging       Date:  2013-01-29

6.  A hardware investigation of robotic SPECT for functional and molecular imaging onboard radiation therapy systems.

Authors:  Susu Yan; James Bowsher; MengHeng Tough; Lin Cheng; Fang-Fang Yin
Journal:  Med Phys       Date:  2014-11       Impact factor: 4.071

7.  Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211.

Authors:  Mathieu Hatt; John A Lee; Charles R Schmidtlein; Issam El Naqa; Curtis Caldwell; Elisabetta De Bernardi; Wei Lu; Shiva Das; Xavier Geets; Vincent Gregoire; Robert Jeraj; Michael P MacManus; Osama R Mawlawi; Ursula Nestle; Andrei B Pugachev; Heiko Schöder; Tony Shepherd; Emiliano Spezi; Dimitris Visvikis; Habib Zaidi; Assen S Kirov
Journal:  Med Phys       Date:  2017-05-18       Impact factor: 4.071

8.  Radiotherapy planning: PET/CT scanner performances in the definition of gross tumour volume and clinical target volume.

Authors:  Ernesto Brianzoni; Gloria Rossi; Sergio Ancidei; Alfonso Berbellini; Francesca Capoccetti; Carla Cidda; Paola D'Avenia; Sara Fattori; Gian Carlo Montini; Gianluca Valentini; Alfredo Proietti; Carlo Algranati
Journal:  Eur J Nucl Med Mol Imaging       Date:  2005-08-26       Impact factor: 9.236

9.  High impact of 18F-FDG-PET on management and prognostic stratification of newly diagnosed small cell lung cancer.

Authors:  Arun Azad; Fiona Chionh; Andrew M Scott; Szeting T Lee; Sam U Berlangieri; Shane White; Paul L Mitchell
Journal:  Mol Imaging Biol       Date:  2009-11-17       Impact factor: 3.488

10.  Feasibility of image registration and intensity-modulated radiotherapy planning with hyperpolarized helium-3 magnetic resonance imaging for non-small-cell lung cancer.

Authors:  Rob H Ireland; Chris M Bragg; Mark McJury; Neil Woodhouse; Stan Fichele; Edwin J R van Beek; Jim M Wild; Matthew Q Hatton
Journal:  Int J Radiat Oncol Biol Phys       Date:  2007-05-01       Impact factor: 7.038

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