Quantitative Accuracy and Lesion Detectability of Low-Dose18F-FDG PET for Lung Cancer Screening.
Lung cancer remains responsible for more deaths worldwide than any other cancer, but recently there has been a significant shift in the clinical paradigm regarding the initial management of subjects at high risk for this disease. Low-dose CT has demonstrated significant improvements over planar x-ray screening for patient prognoses and is now performed in the United States. Specificity of this modality, however, is poor, and the additional information from PET has the potential to improve its accuracy. Routine screening requires consideration of the effective dose delivered to the patient, and this work investigates image quality of PET for low-dose conditions, in the context of lung lesion detectability. Reduced radiotracer doses were simulated by randomly discarding counts from clinical lung cancer scans acquired in list-mode. Bias and reproducibility of lesion activity values were relatively stable even at low total counts of around 5 million trues. Additionally, numeric observer models were developed and trained with the results of 2 physicians and 3 postdoctoral researchers with PET experience in a detection task; detection sensitivity of the observers was well correlated with lesion signal-to-noise ratio. The models were used prospectively to survey detectability of lung cancer lesions, and the findings suggested a lower limit around 10 million true counts for maximizing performance. Under the acquisition parameters used in this study, this translates to an effective patient dose of less than 0.4 mSv, potentially allowing a complete low-dose PET/CT lung screening scan to be obtained under 1 mSv.
A*STAR-NUS, Clinical Imaging Research Centre, Singapore dnrjds@nus.edu.sg.|Department of Diagnostic Radiology, National University Hospital, Singapore.
Joshua D
JD
Schaefferkoetter
Department of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.
Jianhua
J
Yan
A*STAR-NUS, Clinical Imaging Research Centre, Singapore.
Therese
T
Sjöholm
A*STAR-NUS, Clinical Imaging Research Centre, Singapore.|Department of Diagnostic Radiology, National University Hospital, Singapore.
David W
DW
Townsend
Siemens Healthcare Molecular Imaging, Knoxville, Tennessee.
Maurizio
M
Conti
Division of Surgery, National University of Singapore, Singapore.
John Kit Chung
JK
Tam
Department of Haematology-Oncology, National University Cancer Institute, Singapore.|Cancer Science Institute of Singapore, National University of Singapore, Singapore; and.
Ross A
RA
Soo
A*STAR-NUS, Clinical Imaging Research Centre, Singapore.|Department of Radiation Oncology, National University Cancer Institute, Singapore.
Ivan
I
Tham
D000328:Adult; D055088:Early Detection of Cancer / Q000379:methods*; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D049268:Positron-Emission Tomography / Q000379:methods*; D011829:Radiation Dosage; D000069079:Radiation Exposure / Q000032:analysis* / Q000517:prevention & control; D011835:Radiation Protection / Q000379:methods*; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
PET/CT; low dose; lung cancer; screening