Colorectal liver metastasis DWI-DKI RAS (Naples)
Diffusion-Weighted MRI and Diffusion Kurtosis Imaging to Detect RAS Mutation in Colorectal Liver Metastasis
Liver MRI with multi-b-value diffusion of 52 patients with resected colorectal liver metastases, used to predict RAS mutation from diffusion, IVIM and kurtosis parameters. Only per-lesion parameter values are open; the images are not shared.
Overview
A retrospective single-centre cohort from the National Cancer Institute of Naples (IRCCS Fondazione G. Pascale). The study tested whether quantitative diffusion MRI of colorectal cancer metastases in the liver can tell lesions with a RAS mutation from wild-type ones before treatment. Diffusion was modelled three ways (mono-exponential ADC, intravoxel incoherent motion and diffusion kurtosis), and the per-lesion statistics were compared by ROC analysis and simple classifiers. The authors posted a spreadsheet of these per-lesion values on Zenodo under CC BY 4.0. The MR images themselves are not available.
Composition
52 patients (27 men, 25 women, mean age 59 years, range 36 to 80) with 106 liver metastases, all confirmed at pathology after hepatic resection between January 2018 and December 2019. 60 metastases carried a RAS mutation; at patient level 28 were mutated and 24 wild-type. The primary tumour was in the colon in 28 patients and in the rectum in 24. 20 patients had one metastasis and 32 had between 2 and 15. Of 66 eligible patients, 14 were excluded for missing or poor-quality MRI or missing contrast phases.
Acquisition
All scans came from one 1.5 T Siemens Magnetom Symphony. The liver protocol had T2-weighted TrueFISP and HASTE sequences, T1-weighted in- and opposed-phase imaging, fat-suppressed VIBE before and after the hepatobiliary agent Gd-EOB-DTPA (including a 20-minute hepatobiliary phase), and echo-planar DWI with eight b-values from 0 to 2000 s/mm2. Parameter maps were computed with a Siemens prototype diffusion toolbox.
Annotations
Two radiologists with at least 15 years of liver MRI experience drew a volume of interest around every lesion on the highest b-value image, blinded to RAS status. RAS status from histology is the label. The Zenodo spreadsheet gives the mean and standard deviation of seven diffusion parameters per lesion with that label.
Known limitations
- Images and segmentations are not shared; only derived values are open.
- Single centre and single scanner, small sample, no external validation set.
- No inter- or intra-reader variability analysis of the segmentations.
Cohort
Aggregate numbers from the sources below. Bars are relative to the 52 subjects.
Condition
Groups can overlap
- Colorectal cancer 52 100%
Table 1 in Granata et al. 2020, Cancers 12(9), 2420
Age
mean 59, range 36 to 80
No age bins reported.
Section 2.1 in Granata et al. 2020, Cancers 12(9), 2420
Contrast / sequence
Groups can overlap
- Diffusion-weighted 52 100%
Section 2.2 in Granata et al. 2020, Cancers 12(9), 2420
License and access
Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer
The data are not available outside the institution or study that holds them
The Zenodo record holds one spreadsheet of derived values: the mean and standard deviation of ADC, S0, DP, FP, DT, MD and MK inside each segmented lesion, with the RAS status. It is openly downloadable under CC BY 4.0. The paper has no data availability statement and no route to the MR images is published.
Different parts of the data carry different licenses. The summary on the right shows the most restrictive answer per rule.
No published license or data use terms
The data holder has published no license and no data use terms. Any use, sharing or commercial right has to be agreed with the data holder, and nothing can be assumed to be allowed. Default copyright and data protection law still apply.
Neither the Zenodo record nor the paper offers the images or states terms for them.
What you can do
- Commercial use Not stated
- Not stated
- Train ML models Not stated
- Create derived data Not stated
- Publish results Not stated
What you can share
- Share the data Not stated
- Share derived data Not stated
- Share trained models Not stated
What you must do
- Cite or credit Not stated
- Share alike Not stated
- Sign an agreement Not stated
- Ethics approval Not stated
- Manuscript review Not stated
- Release code Not stated
- Return results Not stated
- Delete after use Not stated
Limits
- No re-identification Not stated
- Location limits Not stated
Creative Commons Attribution 4.0 International
Use, share and adapt the data for any purpose, including commercial use, as long as you credit the creators.
What you can do
- Yes
- Yes
- Yes
- Yes
- Yes
What you can share
- Yes
- Yes
- Yes
What you must do
- Yes
- Share alike No
- No
- No
- Manuscript review No
- Release code No
- Return results No
- Delete after use No
Limits
- No
- Location limits No
Citation
Granata V, Fusco R, Risi C, Ottaiano A, Avallone A, De Stefano A, Grimm R, Grassi R, Brunese L, Izzo F, Petrillo A. Diffusion-Weighted MRI and Diffusion Kurtosis Imaging to Detect RAS Mutation in Colorectal Liver Metastasis. Cancers 12(9), 2420 (2020). doi:10.3390/cancers12092420
Sources
Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.