Kai Chen1,2, Lijing Deng1, Qing Li3, Liangping Luo1. 1. Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China. 2. Department of Imaging Center, Shenzhen Samii Medical Center, Shenzhen, China. 3. Department of Radiology, Affiliated Hospital of Xiangnan University, Chenzhou, China.
Abstract
OBJECTIVES: To identify reproducible hematoma radiomics features (RFs) for use in predicting hematoma expansion (HE) in patients with acute intracerebral hemorrhage (ICH). METHODS: For test-retest analysis, three syringes with different volumes of blood collected at the same time (to mimic homogeneous hematoma) and a phantom (FT/HK 2000; Huake, Szechwan, China) containing three cylindrical inserts were scanned seven times within 6 h on the same CT scanner. Three additional syringes with mixed blood collected at different time points (to mimic heterogeneous hematoma) were tied together with the first three syringes as well as the phantom were scanned using modified CT acquisition parameters for intra CT analysis. A coefficient of variation below 10% served as the cutoff value for reproducibility. Finally, reproducible and potentially useful RFs were used to predict HE in 144 acute ICH patients, with the area under the receiver operating characteristic curves (AUC) used to evaluate their diagnostic performance. RESULTS: A total of 630 RFs including 18 first-order, 24 gray-level co-occurrence matrix (GLCM), 16 gray-level run length matrix (GLRLM), five neighborhood gray-tone difference matrix (NGTDM), 63 Laplacian of Gaussian (LoG), and 504 Wavelet features were evaluated. In the test-retest analysis, the percentages of reproducible RFs ranged from 42.54% (268/630) to 45.4% (286/630) for the three homogeneous hematoma samples and 79.05% (498/630) to 81.43% (513/630) for the phantom. In the intra-CT analysis, the percentages varied from 31.43% (198/630) to 42.38% (267/630) for the six hematoma samples and 48.89% (308/630) to 53.97% (340/630) for the phantom. In the in vitro experiment, 148 RFs were reproducible for all hematoma samples in both the test-retest and intra-CT analyses; however, only 80 were statistically different between homogeneous and heterogeneous hematoma samples. Finally, HE occurred in 25% (growth >6 ml, 36/144) to 31.94% (growth >3 ml or 33%, 46/144) of the patients. The AUCs in predicting HE ranged from 0.625 to 0.703. CONCLUSIONS: Only a few CT-based RFs from the in vitro hematoma were reproducible and can distinguish between homogeneous and heterogeneous hematomas. The use of RFs alone to predict HE in acute ICH showed only a moderate performance. ADVANCES IN KNOWLEDGE: Using an in vitro experiment and clinical validation, this study demonstrated for the first time that CT-based hematoma RFs can be used to predict HE in acute ICH; nonetheless, only a few RFs are reproducible and can be used for prediction.
OBJECTIVES: To identify reproducible hematoma radiomics features (RFs) for use in predicting hematoma expansion (HE) in patients with acute intracerebral hemorrhage (ICH). METHODS: For test-retest analysis, three syringes with different volumes of blood collected at the same time (to mimic homogeneous hematoma) and a phantom (FT/HK 2000; Huake, Szechwan, China) containing three cylindrical inserts were scanned seven times within 6 h on the same CT scanner. Three additional syringes with mixed blood collected at different time points (to mimic heterogeneous hematoma) were tied together with the first three syringes as well as the phantom were scanned using modified CT acquisition parameters for intra CT analysis. A coefficient of variation below 10% served as the cutoff value for reproducibility. Finally, reproducible and potentially useful RFs were used to predict HE in 144 acute ICH patients, with the area under the receiver operating characteristic curves (AUC) used to evaluate their diagnostic performance. RESULTS: A total of 630 RFs including 18 first-order, 24 gray-level co-occurrence matrix (GLCM), 16 gray-level run length matrix (GLRLM), five neighborhood gray-tone difference matrix (NGTDM), 63 Laplacian of Gaussian (LoG), and 504 Wavelet features were evaluated. In the test-retest analysis, the percentages of reproducible RFs ranged from 42.54% (268/630) to 45.4% (286/630) for the three homogeneous hematoma samples and 79.05% (498/630) to 81.43% (513/630) for the phantom. In the intra-CT analysis, the percentages varied from 31.43% (198/630) to 42.38% (267/630) for the six hematoma samples and 48.89% (308/630) to 53.97% (340/630) for the phantom. In the in vitro experiment, 148 RFs were reproducible for all hematoma samples in both the test-retest and intra-CT analyses; however, only 80 were statistically different between homogeneous and heterogeneous hematoma samples. Finally, HE occurred in 25% (growth >6 ml, 36/144) to 31.94% (growth >3 ml or 33%, 46/144) of the patients. The AUCs in predicting HE ranged from 0.625 to 0.703. CONCLUSIONS: Only a few CT-based RFs from the in vitro hematoma were reproducible and can distinguish between homogeneous and heterogeneous hematomas. The use of RFs alone to predict HE in acute ICH showed only a moderate performance. ADVANCES IN KNOWLEDGE: Using an in vitro experiment and clinical validation, this study demonstrated for the first time that CT-based hematoma RFs can be used to predict HE in acute ICH; nonetheless, only a few RFs are reproducible and can be used for prediction.
Authors: Roberto Berenguer; María Del Rosario Pastor-Juan; Jesús Canales-Vázquez; Miguel Castro-García; María Victoria Villas; Francisco Mansilla Legorburo; Sebastià Sabater Journal: Radiology Date: 2018-04-24 Impact factor: 11.105
Authors: Philipp Kickingereder; Michael Götz; John Muschelli; Antje Wick; Ulf Neuberger; Russell T Shinohara; Martin Sill; Martha Nowosielski; Heinz-Peter Schlemmer; Alexander Radbruch; Wolfgang Wick; Martin Bendszus; Klaus H Maier-Hein; David Bonekamp Journal: Clin Cancer Res Date: 2016-10-10 Impact factor: 12.531
Authors: Meghan G Lubner; Andrew D Smith; Kumar Sandrasegaran; Dushyant V Sahani; Perry J Pickhardt Journal: Radiographics Date: 2017 Sep-Oct Impact factor: 5.333
Authors: Ruben T H M Larue; Gilles Defraene; Dirk De Ruysscher; Philippe Lambin; Wouter van Elmpt Journal: Br J Radiol Date: 2016-12-12 Impact factor: 3.039
Authors: Rustam Al-Shahi Salman; Joseph Frantzias; Robert J Lee; Patrick D Lyden; Thomas W K Battey; Alison M Ayres; Joshua N Goldstein; Stephan A Mayer; Thorsten Steiner; Xia Wang; Hisatomi Arima; Hitoshi Hasegawa; Makoto Oishi; Daniel A Godoy; Luca Masotti; Dar Dowlatshahi; David Rodriguez-Luna; Carlos A Molina; Dong-Kyu Jang; Antonio Davalos; José Castillo; Xiaoying Yao; Jan Claassen; Bastian Volbers; Seiji Kazui; Yasushi Okada; Shigeru Fujimoto; Kazunori Toyoda; Qi Li; Jane Khoury; Pilar Delgado; José Álvarez Sabín; Mar Hernández-Guillamon; Luis Prats-Sánchez; Chunyan Cai; Mahesh P Kate; Rebecca McCourt; Chitra Venkatasubramanian; Michael N Diringer; Yukio Ikeda; Hans Worthmann; Wendy C Ziai; Christopher D d'Esterre; Richard I Aviv; Peter Raab; Yasuo Murai; Allyson R Zazulia; Kenneth S Butcher; Seyed Mohammad Seyedsaadat; James C Grotta; Joan Martí-Fàbregas; Joan Montaner; Joseph Broderick; Haruko Yamamoto; Dimitre Staykov; E Sander Connolly; Magdy Selim; Rogelio Leira; Byung Hoo Moon; Andrew M Demchuk; Mario Di Napoli; Yukihiko Fujii; Craig S Anderson; Jonathan Rosand Journal: Lancet Neurol Date: 2018-08-14 Impact factor: 44.182