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Radiomics Analysis of PET and CT Components of PET/CT Imaging Integrated with Clinical Parameters: Application to Prognosis for Nasopharyngeal Carcinoma

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Abstract

Purpose

To investigate the prognostic performance of radiomics features, as extracted from positron emission tomography (PET) and X-ray computed tomography (CT) components of baseline 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET/CT images and integrated with clinical parameters, in patients with nasopharyngeal carcinoma (NPC).

Procedures

One hundred twenty-eight NPC patients (85 vs. 43 for training vs. validation), containing a subset of 86 patients with local-regional advanced stage, were enrolled. All patients underwent pretreatment PET/CT scans (mean follow-up time 24 ± 14 months). Three thousand two hundred seventy-six radiomics features extracted from PET or CT components and 13 clinical parameters were used to predict progression-free survival (PFS). Univariate analysis with Benjamini–Hochberg false discovery rate (FDR) correction was first used to screen significant features, and redundant features with Spearman’s correlation > 0.8 were further eliminated. Then, seven multivariate models involving PET features and/or CT features and/or clinical parameters (denoted as clinical, PET, CT, clinical + PET, clinical + CT, PET + CT and clinical + PET + CT) were constructed by forward stepwise multivariate Cox regression. Model performance was evaluated by concordance index (C-index).

Results

Sixty patients encountered events (28 recurrences, 17 metastases, and 15 deaths). Six clinical parameters, 3 PET features, and 14 CT features in training cohort and 4 clinical parameters, 10 PET features, and 4 CT features in subset of local-regional advanced stage were significantly associated with PFS. Combining PET and/or CT features with clinical parameters showed equal or higher prognostic performance than models with PET or CT or clinical parameters alone (C-index 0.71–0.76 vs. 0.67–0.73 and 0.62–0.75 vs. 0.54–0.75 for training and validation cohorts, respectively), while the prognostic performance was significantly improved in local-regional advanced cohort (C-index 0.67–0.84 vs. 0.64–0.77, p value 0.001–0.059).

Conclusion

Radiomics features extracted from the PET and CT components of baseline PET/CT images provide complementary prognostic information and improved outcome prediction for NPC patients compared with use of clinical parameters alone.

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Funding

This work was supported by the National Natural Science Foundation of China under grants 61628105, 81501541, 81871437, U1708261, and 61471188, the National Key Research and Development Program under grant 2016YFC0104003, the Natural Science Foundation of Guangdong Province under grant 2016A030313577, the Program of Pearl River Young Talents of Science and Technology in Guangzhou under grant 201610010011, the Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (Lijun Lu, 2018), and the China Scholarship Council under grant 201808440464.

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Authors and Affiliations

  1. School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Road, Guangzhou, 510515, Guangdong, China

    Wenbing Lv, Jianhua Ma, Qianjin Feng, Wufan Chen & Lijun Lu

  2. Nanfang PET Center, Nanfang Hospital, Southern Medical University, 1023 Shatai Road, Guangzhou, 510515, Guangdong, China

    Qingyu Yuan & Quanshi Wang

  3. Department of Radiology, Johns Hopkins University, 601 N. Caroline St., Baltimore, MD, 21287, USA

    Arman Rahmim

  4. Departments of Radiology and Physics & Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC, V6T 1Z1, Canada

    Arman Rahmim

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  1. Wenbing Lv
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  2. Qingyu Yuan
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  3. Quanshi Wang
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  4. Jianhua Ma
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Lv, W., Yuan, Q., Wang, Q. et al. Radiomics Analysis of PET and CT Components of PET/CT Imaging Integrated with Clinical Parameters: Application to Prognosis for Nasopharyngeal Carcinoma. Mol Imaging Biol 21, 954–964 (2019). https://doi.org/10.1007/s11307-018-01304-3

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