Quantitative image feature variability amongst CT scanners with a controlled scan protocol

Rachel B. Ger, Shouhao Zhou, Pai Chun Melinda Chi, David L. Goff, Lifei Zhang, Hannah J. Lee, Clifton D. Fuller, Rebecca M. Howell, Heng Li, R. Jason Stafford, Laurence E. Court, Dennis S. MacKin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Radiomics studies often analyze patient computed tomography (CT) images acquired from different CT scanners. This may result in differences in imaging parameters, e.g. different manufacturers, different acquisition protocols, etc. However, quantifiable differences in radiomics features can occur based on acquisition parameters. A controlled protocol may allow for minimization of these effects, thus allowing for larger patient cohorts from many different CT scanners. In order to test radiomics feature variability across different CT scanners a radiomics phantom was developed with six different cartridges encased in high density polystyrene. A harmonized protocol was developed to control for tube voltage, tube current, scan type, pitch, CTDIvol, convolution kernel, display field of view, and slice thickness across different manufacturers. The radiomics phantom was imaged on 18 scanners using the control protocol. A linear mixed effects model was created to assess the impact of inter-scanner variability with decomposition of feature variation between scanners and cartridge materials. The inter-scanner variability was compared to the residual variability (the unexplained variability) and to the inter-patient variability using two different patient cohorts. The patient cohorts consisted of 20 non-small cell lung cancer (NSCLC) and 30 head and neck squamous cell carcinoma (HNSCC) patients. The inter-scanner standard deviation was at least half of the residual standard deviation for 36 of 49 quantitative image features. The ratio of inter-scanner to patient coefficient of variation was above 0.2 for 22 and 28 of the 49 features for NSCLC and HNSCC patients, respectively. Inter-scanner variability was a significant factor compared to patient variation in this small study for many of the features. Further analysis with a larger cohort will allow more thorough analysis with additional variables in the model to truly isolate the interscanner difference.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2018
Subtitle of host publicationComputer-Aided Diagnosis
EditorsKensaku Mori, Nicholas Petrick
PublisherSPIE
ISBN (Electronic)9781510616394
DOIs
StatePublished - Jan 1 2018
EventMedical Imaging 2018: Computer-Aided Diagnosis - Houston, United States
Duration: Feb 12 2018Feb 15 2018

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume10575
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2018: Computer-Aided Diagnosis
CountryUnited States
CityHouston
Period2/12/182/15/18

Fingerprint

X-Ray Computed Tomography Scanners
scanners
Tomography
tomography
cancer
Polystyrenes
cartridges
Convolution
Head and Neck Neoplasms
Non-Small Cell Lung Carcinoma
lungs
Display devices
Cells
standard deviation
Decomposition
acquisition
Imaging techniques
tubes
Electric potential
convolution integrals

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

Cite this

Ger, R. B., Zhou, S., Chi, P. C. M., Goff, D. L., Zhang, L., Lee, H. J., ... MacKin, D. S. (2018). Quantitative image feature variability amongst CT scanners with a controlled scan protocol. In K. Mori, & N. Petrick (Eds.), Medical Imaging 2018: Computer-Aided Diagnosis [105751O] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10575). SPIE. https://doi.org/10.1117/12.2293701
Ger, Rachel B. ; Zhou, Shouhao ; Chi, Pai Chun Melinda ; Goff, David L. ; Zhang, Lifei ; Lee, Hannah J. ; Fuller, Clifton D. ; Howell, Rebecca M. ; Li, Heng ; Jason Stafford, R. ; Court, Laurence E. ; MacKin, Dennis S. / Quantitative image feature variability amongst CT scanners with a controlled scan protocol. Medical Imaging 2018: Computer-Aided Diagnosis. editor / Kensaku Mori ; Nicholas Petrick. SPIE, 2018. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE).
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abstract = "Radiomics studies often analyze patient computed tomography (CT) images acquired from different CT scanners. This may result in differences in imaging parameters, e.g. different manufacturers, different acquisition protocols, etc. However, quantifiable differences in radiomics features can occur based on acquisition parameters. A controlled protocol may allow for minimization of these effects, thus allowing for larger patient cohorts from many different CT scanners. In order to test radiomics feature variability across different CT scanners a radiomics phantom was developed with six different cartridges encased in high density polystyrene. A harmonized protocol was developed to control for tube voltage, tube current, scan type, pitch, CTDIvol, convolution kernel, display field of view, and slice thickness across different manufacturers. The radiomics phantom was imaged on 18 scanners using the control protocol. A linear mixed effects model was created to assess the impact of inter-scanner variability with decomposition of feature variation between scanners and cartridge materials. The inter-scanner variability was compared to the residual variability (the unexplained variability) and to the inter-patient variability using two different patient cohorts. The patient cohorts consisted of 20 non-small cell lung cancer (NSCLC) and 30 head and neck squamous cell carcinoma (HNSCC) patients. The inter-scanner standard deviation was at least half of the residual standard deviation for 36 of 49 quantitative image features. The ratio of inter-scanner to patient coefficient of variation was above 0.2 for 22 and 28 of the 49 features for NSCLC and HNSCC patients, respectively. Inter-scanner variability was a significant factor compared to patient variation in this small study for many of the features. Further analysis with a larger cohort will allow more thorough analysis with additional variables in the model to truly isolate the interscanner difference.",
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Ger, RB, Zhou, S, Chi, PCM, Goff, DL, Zhang, L, Lee, HJ, Fuller, CD, Howell, RM, Li, H, Jason Stafford, R, Court, LE & MacKin, DS 2018, Quantitative image feature variability amongst CT scanners with a controlled scan protocol. in K Mori & N Petrick (eds), Medical Imaging 2018: Computer-Aided Diagnosis., 105751O, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10575, SPIE, Medical Imaging 2018: Computer-Aided Diagnosis, Houston, United States, 2/12/18. https://doi.org/10.1117/12.2293701

Quantitative image feature variability amongst CT scanners with a controlled scan protocol. / Ger, Rachel B.; Zhou, Shouhao; Chi, Pai Chun Melinda; Goff, David L.; Zhang, Lifei; Lee, Hannah J.; Fuller, Clifton D.; Howell, Rebecca M.; Li, Heng; Jason Stafford, R.; Court, Laurence E.; MacKin, Dennis S.

Medical Imaging 2018: Computer-Aided Diagnosis. ed. / Kensaku Mori; Nicholas Petrick. SPIE, 2018. 105751O (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10575).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Ger RB, Zhou S, Chi PCM, Goff DL, Zhang L, Lee HJ et al. Quantitative image feature variability amongst CT scanners with a controlled scan protocol. In Mori K, Petrick N, editors, Medical Imaging 2018: Computer-Aided Diagnosis. SPIE. 2018. 105751O. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). https://doi.org/10.1117/12.2293701