Unique ID issued by UMIN | UMIN000039293 |
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Receipt number | R000044817 |
Scientific Title | Prognostic value of FDG-PET radiomics with machine learning in pancreatic cancer |
Date of disclosure of the study information | 2020/01/29 |
Last modified on | 2020/01/28 20:07:24 |
Prognostic value of FDG-PET radiomics with machine learning in pancreatic cancer
Prognostic value of FDG-PET radiomics with machine learning in pancreatic cancer
Prognostic value of FDG-PET radiomics with machine learning in pancreatic cancer
Prognostic value of FDG-PET radiomics with machine learning in pancreatic cancer
Japan |
Pancreatic cancer
Hepato-biliary-pancreatic medicine | Hepato-biliary-pancreatic surgery | Radiology |
Malignancy
NO
To investigate the utility of radiomics with machine learning using 18F-fluorodeoxyglucose (FDG)-PET in patients with pancreatic cancer.
Efficacy
Not applicable
The study endpoint was overall survival (OS), defined as the time from pretreatment FDG-PET/CT scan to cancer-related death. Outcome data were collected from the medical records of each patient. Surviving patients were censored at the time of last clinical follow-up.
Observational
20 | years-old | <= |
Not applicable |
Male and Female
We enrolled 314 consecutive patients with biopsy-confirmed pancreatic invasive ductal carcinoma who underwent FDG-PET/CT before treatment between April 2010 and March 2018.
20 years old or older
The exclusion criteria were as follows: 1) no significant solid mass on CT/MRI; 2) no significant FDG-uptake; 3) uncontrolled diabetes (<150 mg/dl); 4) multiple cancer; 5) unknown clinical course; 6) under best supportive care; 7) sudden death; 8) early death after surgery.
1000
1st name | Yoshitaka |
Middle name | |
Last name | Toyama |
Tohoku University Hospital
Department of Diagnostic Radiology
9808574
1-1 Seiryo-Machi, Aoba-Ku, Sendai
+81-22-717-7312
ytoyama0818@gmail.com
1st name | Yoshitaka |
Middle name | |
Last name | Toyama |
Tohoku University Hospital
Department of Diagnostic Radiology
9808574
1-1 Seiryo-Machi, Aoba-Ku, Sendai
+81-22-717-7312
ytoyama0818@gmail.com
Tohoku University
N/A
Self funding
Tohoku University Hospital IRB
1-1 Seiryo-Machi, Aoba-Ku, Sendai
022-728-4105
ytoyama0818@gmail.com
NO
2020 | Year | 01 | Month | 29 | Day |
Unpublished
161
Completed
2019 | Year | 07 | Month | 11 | Day |
2019 | Year | 07 | Month | 26 | Day |
2019 | Year | 07 | Month | 11 | Day |
2019 | Year | 07 | Month | 11 | Day |
To obtain the volume of interest (VOI) of the primary tumor, a sphere was set to encompass the lesion and then contoured using a threshold of 40% of the SUVmax. A total of 42 PET parameters including conventional features (e.g., SUVmax, MTV, TLG) and global, local, and regional texture features were measured using the LIFEx package. Texture features were calculated only for VOIs of 64 voxels because textural features cannot be accurately quantified for small regions. All PET/CT images were assessed by two nuclear medicine physicians, with decisions made in consensus.
2020 | Year | 01 | Month | 28 | Day |
2020 | Year | 01 | Month | 28 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000044817
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