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Diagnostic performance and inter-operator variability of apparent diffusion coefficient analysis for differentiating pleomorphic adenoma and carcinoma ex pleomorphic adenoma: comparing one-point measurement and whole-tumor measurement including radiomics approach

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Japanese Journal of Radiology Aims and scope Submit manuscript

Abstract

Background and purpose

The purpose of this study was to compare the diagnostic performance between apparent diffusion coefficient (ADC) analysis of one-point measurement and whole-tumor measurement, including radiomics for differentiating pleomorphic adenoma (PA) from carcinoma ex pleomorphic adenoma (CXPA), and to evaluate the impact of inter-operator segmentation variability.

Materials and methods

One hundred and fifteen patients with PA and 22 with CXPA were included. Four radiologists with different experience independently placed one-point and whole-tumor ROIs and a radiomics-predictive model was constructed from the extracted imaging features. We calculated the area under the receiver-operator characteristic curve (AUC) for the diagnostic performance of imaging features and the radiomics-predictive model.

Results

AUCs of the imaging features from whole-tumor varied between readers (0.50–0.89). The most experienced radiologist (Reader 1) produced significantly high AUCs than less experienced radiologists (Reader 3 and 4; P = 0.01 and 0.009). AUCs were higher for the radiomics-predictive model (0.82–0.87) than for one-point (0.66–0.79) in all readers.

Conclusion

Some imaging features of whole-tumor and radiomics-predictive model had higher diagnostic performance than one-point. The diagnostic performance of imaging features from whole-tumor alone varied depending on operator experience. Operator experience appears less likely to affect diagnostic performance in the radiomics-predictive model.

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Abbreviations

ADC:

Apparent diffusion coefficient

PA:

Pleomorphic adenoma

CXPA:

Carcinoma ex pleomorphic adenoma

ROI:

Region of interest

ICC:

Intraclass correlation coefficient

AUC:

Area under the receiver operating characteristic curve

RF:

Random forest algorithm

EN:

Elastic net algorithm

CV:

Cross-validation

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Authors and Affiliations

  1. Department of Radiology, Chiba University Hospital, 1-8-1, Inohana Chuo-ku, Chiba, 260-8677, Japan

    Takeshi Wada, Takuro Horikoshi, Shinya Hattori & Jun Hashiba

  2. Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, 1-8-1, Inohana Chuo-ku, Chiba, 260-8670, Japan

    Hajime Yokota & Takashi Uno

  3. Department of Radiology, Oregon Health and Science University, 3181 S.W. Sam Jackson Park Rd., Portland, OR, 97239, USA

    Jay Starkey

Authors
  1. Takeshi Wada
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  2. Hajime Yokota
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  3. Takuro Horikoshi
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  4. Jay Starkey
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  5. Shinya Hattori
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  6. Jun Hashiba
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  7. Takashi Uno
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Correspondence to Hajime Yokota.

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Ethical statement

This study was approved by the local ethics review board and informed consent was waived due to the retrospective nature of this study.

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Wada, T., Yokota, H., Horikoshi, T. et al. Diagnostic performance and inter-operator variability of apparent diffusion coefficient analysis for differentiating pleomorphic adenoma and carcinoma ex pleomorphic adenoma: comparing one-point measurement and whole-tumor measurement including radiomics approach. Jpn J Radiol 38, 207–214 (2020). https://doi.org/10.1007/s11604-019-00908-1

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  • DOI: https://doi.org/10.1007/s11604-019-00908-1

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