AI Article Synopsis
- The Apparent Diffusion Coefficient (ADC) is a key imaging biomarker for assessing tumor cell density and detecting early changes in cancer treatment.
- This study introduces a data-driven model to enhance the reliability of ADC measurements by accounting for measurement errors and quantifying uncertainty in data.
- After testing on 20 patients, the standardisation process significantly reduced the confidence interval for ADC changes, improving the reproducibility of results, especially in the context of small tumors and patient movement during scans.
Article Abstract
Apparent Diffusion Coefficient (ADC) is a potential quantitative imaging biomarker for tumour cell density and is widely used to detect early treatment changes in cancer therapy. We propose a strategy to improve confidence in the interpretation of measured changes in ADC using a data-driven model that describes sources of measurement error. Observed ADC is then standardised against this estimation of uncertainty for any given measurement. 20 patients were recruited prospectively and equitably across 4 sites, and scanned twice (test-retest) within 7 days. Repeatability measurements of defined regions (ROIs) of tumour and normal tissue were quantified as percentage change in mean ADC (test vs. re-test) and then standardised against an estimation of uncertainty. Multi-site reproducibility, (quantified as width of the 95% confidence bound between the lower confidence interval and higher confidence interval for all repeatability measurements), was compared before and after standardisation to the model. The 95% confidence interval width used to determine a statistically significant change reduced from 21.1 to 2.7% after standardisation. Small tumour volumes and respiratory motion were found to be important contributors to poor reproducibility. A look up chart has been provided for investigators who would like to estimate uncertainty from statistical error on individual ADC measurements.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5658431 | PMC |
| http://dx.doi.org/10.1038/s41598-017-14625-0 | DOI Listing |
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