Complementary Value of Intra- and Peri-Tumoral PET/CT Radiomics for Outcome Prediction in Head and Neck Cancer

被引:10
|
作者
Lv, Wenbing [1 ,2 ]
Feng, Hui [1 ,3 ]
Du, Dongyang [1 ,2 ]
Ma, Jianhua [1 ,2 ]
Lu, Lijun [1 ,2 ]
机构
[1] Southern Med Univ, Sch Biomed Engn, Guangdong Prov Key Lab Med Image Proc, Guangzhou 510515, Peoples R China
[2] Southern Med Univ, Guangdong Prov Engn Lab Med Imaging & Diagnost Te, Guangzhou 510515, Peoples R China
[3] Yantai Yuhuangding Hosp, Dept Radiotherapy, Yantai 264000, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Feature extraction; Training; Predictive models; Licenses; Radiomics; Data models; Quantization (signal); Peri-tumor; PET; CT; radiomics; head&neck cancer; prognosis; HEPATOCELLULAR-CARCINOMA; LOCAL RECURRENCE; METASTASIS; CT; FEATURES; IMPACT; MARGINS; IMAGES;
D O I
10.1109/ACCESS.2021.3085601
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To investigate the prognostic value of peri-tumoral radiomics features of pre-treatment PET/CT images in patients with head and neck cancer. 166 patients from 4 centers (111 for training and 55 for external independent testing) were retrospectively analyzed. 11 regions were used for feature extraction, (1) Intra-tumoral region (Intra) was first dilated radially along the edge by 3, 6, 9, 12 and 15 mm to obtain (2) 5 solid combined regions (noted as Comb_3, 6, 9, 12, and 15, respectively), and (3) 5 hollow annular regions with equal ring width of 3 mm were then generated as peri-tumoral regions (noted as Peri_3, 6, 9, 12 and 15, respectively). 92 individual/integrated models were constructed by using features from Clinical alone, CT or PET alone, Clinical+PET, Clinical+CT, PET+CT, Clinical+PET+CT, Intra+Peri, Clinical+Intra+Peri and Clinical+PET+CT (Intra+Peri). In individual models, only 4 models showed p<0.05 (PET_Peri_3 and PET_Comb_6 for distant metastasis (DM) prediction, Clinical and PET_Peri_6 for death prediction). In integrated models, Clinical+CT (Intra+Peri_6), PET (Intra+Peri_3) and Clinical+PET_Peri_6 achieved the best performance for the prediction of local recurrence (LR), DM and death with AUC of 0.75, 0.80 and 0.87, C-index of 0.71, 0.80 and 0.83, p-value of 0.003, 0.008 and 0.001, respectively. Peri-tumoral regions that located closer to the intra-tumoral region (Peri_3 and Peri_6) showed better performance compared to those located further. The integration of intra-tumoral and peri-tumoral radiomics features achieved better performance than either of them alone, PET and CT radiomics features also provided complementary information to clinical features.
引用
收藏
页码:81818 / 81827
页数:10
相关论文
共 50 条
  • [31] Multi-Modality (PET/CT) Radiomics Based Recurrence Prediction in Head and Neck Cancers Prior to Radiotherapy
    Schelin, M.
    Sheu, R.
    Bakst, R.
    Junn, J.
    Yuan, Y.
    [J]. MEDICAL PHYSICS, 2021, 48 (06)
  • [32] Prognostic value of combined FDG-PET/CT in Head and Neck Tumors: is there any potential for further improvement of outcome prediction?
    Abramyuk, A.
    Zoephel, K.
    Tokalov, S.
    Shakirin, G.
    Haberland, U.
    Klotz, E.
    Wolf, G.
    Abolmaali, N.
    [J]. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2009, 36 : S327 - S327
  • [33] A radiomics strategy based on CT intra-tumoral and peritumoral regions for preoperative prediction of neoadjuvant chemoradiotherapy for esophageal cancer
    Li, Zhiyang
    Wang, Fuqiang
    Zhang, Hanlu
    Xie, Shenglong
    Peng, Lei
    Xu, Hui
    Wang, Yun
    [J]. EJSO, 2024, 50 (04):
  • [34] Interim 18F-FDG-PET/CT during chemoradiotherapy for early outcome prediction of head and neck cancer
    Garibaldi, C.
    Ronchi, S.
    Cremonesi, M.
    Ferrari, M.
    Gilardi, L.
    Travaini, L.
    Ciardo, D.
    Botta, F.
    Baroni, G.
    Grana, C.
    Jereczek-Fossa, B. A.
    Orecchia, R.
    [J]. RADIOTHERAPY AND ONCOLOGY, 2016, 119 : S520 - S520
  • [35] A radiomics strategy based on CT intra-tumoral and peritumoral regions for preoperative prediction of neoadjuvant chemoradiotherapy for esophageal cancer
    Li, Z.
    Wang, Y.
    [J]. ANNALS OF ONCOLOGY, 2023, 34 : S1553 - S1553
  • [36] Context-Aware Saliency Guided Radiomics: Application to Prediction of Outcome and HPV-Status from Multi-Center PET/CT Images of Head and Neck Cancer
    Lv, Wenbing
    Xu, Hui
    Han, Xu
    Zhang, Hao
    Ma, Jianhua
    Rahmim, Arman
    Lu, Lijun
    [J]. CANCERS, 2022, 14 (07)
  • [37] Negative Predictive Value of Surveillance PET/CT in Head and Neck Squamous Cell Cancer
    McDermott, M.
    Hughes, M.
    Rath, T.
    Johnson, J. T.
    Heron, D. E.
    Kubicek, G. J.
    Kim, S. W.
    Ferris, R. L.
    Duvvuri, U.
    Ohr, J. P.
    Branstetter, B. F.
    [J]. AMERICAN JOURNAL OF NEURORADIOLOGY, 2013, 34 (08) : 1632 - 1636
  • [38] Utility of FDG-PET scans in staging and prediction of outcome in head and neck cancer
    Chaudhry, S.
    Natwa, M.
    Lavarino, J.
    Anne, P.
    Keane, W.
    Intenzo, C.
    Machtay, M.
    [J]. INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2006, 66 (03): : S446 - S446
  • [39] Prognostic value of FDG PET/CT during radiotherapy in head and neck cancer patients
    Kim, Suzy
    Oh, Sowon
    Kim, Jin Soo
    Kim, Yu Kyeong
    Kim, Kwang Hyun
    Oh, Do Hoon
    Lee, Dong-Han
    Jeong, Woo-Jin
    Jung, Young Ho
    [J]. RADIATION ONCOLOGY JOURNAL, 2018, 36 (02): : 95 - 102
  • [40] Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics
    Huynh, Bao Ngoc
    Groendahl, Aurora Rosvoll
    Tomic, Oliver
    Liland, Kristian Hovde
    Knudtsen, Ingerid Skjei
    Hoebers, Frank
    van Elmpt, Wouter
    Malinen, Eirik
    Dale, Einar
    Futsaether, Cecilia Marie
    [J]. FRONTIERS IN MEDICINE, 2023, 10