Bang-Bin Chen1, Yu-Wen Tien2, Ming-Chu Chang3, Mei-Fang Cheng4, Yu-Ting Chang3, Chih-Horng Wu1, Xin-Jia Chen1, Ting-Chun Kuo2, Shih-Hung Yang5, I-Lun Shih1, Hong-Shiee Lai2, Tiffany Ting-Fang Shih6,7. 1. Department of Medical Imaging and Radiology, National Taiwan University College of Medicine and Hospital, No 7, Chung-Shan South Rd, Taipei, 10016, Taiwan. 2. Department of Surgery, National Taiwan University College of Medicine and Hospital, Taipei, Taiwan. 3. Department of Internal Medicine, National Taiwan University College of Medicine and Hospital, Taipei, Taiwan. 4. Department of Nuclear Medicine and Radiology, National Taiwan University College of Medicine and Hospital, Taipei, Taiwan. 5. Department of Oncology, National Taiwan University College of Medicine and Hospital, Taipei, Taiwan. 6. Department of Medical Imaging and Radiology, National Taiwan University College of Medicine and Hospital, No 7, Chung-Shan South Rd, Taipei, 10016, Taiwan. ttfshih@ntu.edu.tw. 7. Department of Medical Imaging, Taipei City Hospital, Taipei, Taiwan. ttfshih@ntu.edu.tw.
Abstract
PURPOSE: To correlate the clinical stage and prognosis of pancreatic or periampullary cancer with the imaging biomarkers on diffusion-weighted imaging, magnetic resonance spectroscopy and glucose metabolic activity derived from integrated PET/MRI. METHODS: This prospective study was approved by the institutional review board and informed consent was obtained. The study group comprised 60 consecutive patients with pancreatic or periampullary cancer who underwent PET/MRI before treatment. The imaging biomarkers were the minimal apparent diffusion coefficient (ADCmin), choline levels, standardized uptake values, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) of the tumours. The relationships between these biomarkers and clinical TNM stage were evaluated using the Pearson test and the Mann-Whitney U test. The area under the receiver operating characteristic curve (AUROC) was used to evaluate accuracy. The correlation between the imaging biomarker and progression-free survival (PFS) was investigated using the Cox proportional hazards model. RESULTS: ADCmin was significantly lower in N1 and TNM stage 3+ tumours. Choline levels significantly higher in T4 tumours. TLG was significantly higher in T4, N1 and TNM stage 3+ tumours. MTV was significantly higher in T4, N1, M1, and TNM stage 3+ tumours (all P < 0.05). The MTV/ADCmin ratio exhibited the highest AUROC for predicting T4, N1, M1, and advanced TNM stages tumours, and was an independent predictor of PFS (P = 0.018) after adjustment for age, sex, tumour size and stage. CONCLUSION: The imaging biomarkers from integrated PET/MRI may predict clinical stage and PFS in patients with pancreatic or periampullary cancer.
PURPOSE: To correlate the clinical stage and prognosis of pancreatic or periampullary cancer with the imaging biomarkers on diffusion-weighted imaging, magnetic resonance spectroscopy and glucose metabolic activity derived from integrated PET/MRI. METHODS: This prospective study was approved by the institutional review board and informed consent was obtained. The study group comprised 60 consecutive patients with pancreatic or periampullary cancer who underwent PET/MRI before treatment. The imaging biomarkers were the minimal apparent diffusion coefficient (ADCmin), choline levels, standardized uptake values, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) of the tumours. The relationships between these biomarkers and clinical TNM stage were evaluated using the Pearson test and the Mann-Whitney U test. The area under the receiver operating characteristic curve (AUROC) was used to evaluate accuracy. The correlation between the imaging biomarker and progression-free survival (PFS) was investigated using the Cox proportional hazards model. RESULTS: ADCmin was significantly lower in N1 and TNM stage 3+ tumours. Choline levels significantly higher in T4 tumours. TLG was significantly higher in T4, N1 and TNM stage 3+ tumours. MTV was significantly higher in T4, N1, M1, and TNM stage 3+ tumours (all P < 0.05). The MTV/ADCmin ratio exhibited the highest AUROC for predicting T4, N1, M1, and advanced TNM stages tumours, and was an independent predictor of PFS (P = 0.018) after adjustment for age, sex, tumour size and stage. CONCLUSION: The imaging biomarkers from integrated PET/MRI may predict clinical stage and PFS in patients with pancreatic or periampullary cancer.
Authors: Yi Wang; Zongming E Chen; Paul Nikolaidis; Robert J McCarthy; Laura Merrick; Laura A Sternick; Jeanne M Horowitz; Vahid Yaghmai; Frank H Miller Journal: J Magn Reson Imaging Date: 2011-01 Impact factor: 4.813
Authors: Steven M. Larson; Yusuf Erdi; Timothy Akhurst; Madhu Mazumdar; Homer A. Macapinlac; Ronald D. Finn; Cecille Casilla; Melissa Fazzari; Neil Srivastava; Henry W.D. Yeung; John L. Humm; Jose Guillem; Robert Downey; Martin Karpeh; Alfred E. Cohen; Robert Ginsberg Journal: Clin Positron Imaging Date: 1999-05
Authors: Johannes Grueneisen; Karsten Beiderwellen; Philipp Heusch; Paul Buderath; Bahriye Aktas; Marcel Gratz; Michael Forsting; Thomas Lauenstein; Verena Ruhlmann; Lale Umutlu Journal: PLoS One Date: 2014-05-07 Impact factor: 3.240
Authors: Naveen M Kulkarni; Lorenzo Mannelli; Marc Zins; Priya R Bhosale; Hina Arif-Tiwari; Olga R Brook; Elizabeth M Hecht; Fay Kastrinos; Zhen Jane Wang; Erik V Soloff; Parag P Tolat; Guillermo Sangster; Jason Fleming; Eric P Tamm; Avinash R Kambadakone Journal: Abdom Radiol (NY) Date: 2020-03
Authors: Thomas A Hope; Zahi A Fayad; Kathryn J Fowler; Dawn Holley; Andrei Iagaru; Alan B McMillan; Patrick Veit-Haiback; Robert J Witte; Greg Zaharchuk; Ciprian Catana Journal: J Nucl Med Date: 2019-05-23 Impact factor: 10.057
Authors: Krista Elise Suarez-Weiss; Alexander Herold; Debra Gervais; Edwin Palmer; Bárbara Amorim; Joseph D King; Li Weier; Tajmir Shahein; Hanna Bernstine; Liran Domachevsk; Lina Garcia Cañamaque; Lale Umutlu; Ken Herrmann; David Groshar; Onofrio A Catalano Journal: Radiologe Date: 2020-05 Impact factor: 0.635
Authors: D L Bailey; B J Pichler; B Gückel; G Antoch; H Barthel; Z M Bhujwalla; S Biskup; S Biswal; M Bitzer; R Boellaard; R F Braren; C Brendle; K Brindle; A Chiti; C la Fougère; R Gillies; V Goh; M Goyen; M Hacker; L Heukamp; G M Knudsen; A M Krackhardt; I Law; J C Morris; K Nikolaou; J Nuyts; A A Ordonez; K Pantel; H H Quick; K Riklund; O Sabri; B Sattler; E G C Troost; M Zaiss; L Zender; Thomas Beyer Journal: Mol Imaging Biol Date: 2018-02 Impact factor: 3.488