Effects of alterations in positron emission tomography imaging parameters on radiomics features.
Rachel B GerJoseph G MeierRaymond B PahlkaSkylar S GayRaymond P MummeClifton D FullerHeng LiRebecca M HowellRick R LaymanR Jason StaffordShouhao ZhouOsama MawlawiLaurence E CourtPublished in: PloS one (2019)
Radiomics studies require large patient cohorts, which often include patients imaged using different imaging protocols. We aimed to determine the impact of variability in imaging protocol parameters and interscanner variability using a phantom that produced feature values similar to those of patients. Positron emission tomography (PET) scans of a Hoffman brain phantom were acquired on GE Discovery 710, Siemens mCT, and Philips Vereos scanners. A standard-protocol scan was acquired on each machine, and then each parameter that could be changed was altered individually. The phantom was contoured with 10 regions of interest (ROIs). Values for 45 features with 2 different preprocessing techniques were extracted for each image. To determine the impact of each parameter on the reliability of each radiomics feature, the intraclass correlation coefficient (ICC) was calculated with the ROIs as the subjects and the parameter values as the raters. For interscanner comparisons, we compared the standard deviation of each radiomics feature value from the standard-protocol images to the standard deviation of the same radiomics feature from PET scans of 224 patients with non-small cell lung cancer. When the pixel size was resampled prior to feature extraction, all features had good reliability (ICC > 0.75) for the field of view and matrix size. The time per bed position had excellent reliability (ICC > 0.9) on all features. When the filter cutoff was restricted to values below 6 mm, all features had good reliability. Similarly, when subsets and iterations were restricted to reasonable values used in clinics, almost all features had good reliability. The average ratio of the standard deviation of features on the phantom scans to that of the NSCLC patient scans was 0.73 using fixed-bin-width preprocessing and 0.92 using 64-level preprocessing. Most radiomics feature values had at least good reliability when imaging protocol parameters were within clinically used ranges. However, interscanner variability was about equal to interpatient variability; therefore, caution must be used when combining patients scanned on equipment from different vendors in radiomics data sets.
Keyphrases
- computed tomography
- positron emission tomography
- deep learning
- contrast enhanced
- end stage renal disease
- lymph node metastasis
- machine learning
- ejection fraction
- randomized controlled trial
- newly diagnosed
- high resolution
- chronic kidney disease
- pet ct
- dual energy
- image quality
- pet imaging
- primary care
- prognostic factors
- squamous cell carcinoma
- patient reported outcomes
- magnetic resonance imaging
- magnetic resonance
- electronic health record
- mass spectrometry
- white matter
- artificial intelligence
- fluorescence imaging
- resting state
- tyrosine kinase
- single cell
- case control
- patient reported