Cone-beam computed tomography for lung cancer - validation with CT and monitoring tumour response during chemo-radiation therapy.
BACKGROUND
Cone-beam computed tomography (CBCT) is a valuable image-guidance tool in radiation therapy (RT). This study was initiated to assess the accuracy of CBCT for quantifying non-small cell lung cancer (NSCLC) tumour volumes compared to the anatomical 'gold standard', CT. Tumour regression or progression on CBCT was also analysed.


METHODS
Patients with Stage I-III NSCLC, prescribed 60 Gy in 30 fractions RT with concurrent platinum-based chemotherapy, routine CBCT and enrolled in a prospective study of serial PET/CT (baseline, weeks two and four) were eligible. Time-matched CBCT and CT gross tumour volumes (GTVs) were manually delineated by a single observer on MIM software, and were analysed descriptively and using Pearson's correlation coefficient (r) and linear regression (R2).


RESULTS
Of 94 CT/CBCT pairs, 30 patients were eligible for inclusion. The mean (± SD) CT GTV vs CBCT GTV on the four time-matched pairs were 95 (±182) vs 98.8 (±160.3), 73.6 (±132.4) vs 70.7 (±96.6), 54.7 (±92.9) vs 61.0 (±98.8) and 61.3 (±53.3) vs 62.1 (±47.9) respectively. Pearson's correlation coefficient (r) was 0.98 (95% CI 0.97-0.99, ρ < 0.001). The mean (±SD) CT/CBCT Dice's similarity coefficient was 0.66 (±0.16). Of 289 CBCT scans, tumours in 27 (90%) patients regressed by a mean (±SD) rate of 1.5% (±0.75) per fraction. The mean (±SD) GTV regression was 43.1% (±23.1) from the first to final CBCT.


CONCLUSIONS
Primary lung tumour volumes observed on CBCT and time-matched CT are highly correlated (although not identical), thereby validating observations of GTV regression on CBCT in NSCLC.
Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia.
Alissa
A
Michienzi
Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.|Department of Medical Imaging and Radiation Sciences, Monash University, Clayton, Victoria, Australia.|Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia.
Tomas
T
Kron
Department of Medical Imaging and Radiation Sciences, Monash University, Clayton, Victoria, Australia.|Centre for Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Jason
J
Callahan
Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Nikki
N
Plumridge
Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia.|Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
David
http://orcid.org/0000-0002-0491-6919
D
Ball
Department of Medical Imaging and Radiation Sciences, Monash University, Clayton, Victoria, Australia.|Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia.|Radiation Therapy Services, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Sarah
S
Everitt
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging* / Q000473:pathology / Q000628:therapy*; D059248:Chemoradiotherapy; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D018450:Disease Progression; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology / Q000628:therapy*; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D000072078:Positron Emission Tomography Computed Tomography; D011446:Prospective Studies; D011879:Radiotherapy Dosage; D012984:Software; D014057:Tomography, X-Ray Computed; D016896:Treatment Outcome; D047368:Tumor Burden

CBCT
; 
CT
; lung cancer; radiation therapy; regression