Report: Lung cancer biomarkers lag technology, collaboration needed
Developing new imaging biomarkers and public data sets for lung cancer is important for independent peer review and verification of results, and new capabilities for the rapid assessment of treatment responses are required in order to allow for more rapid evaluation of the success or failure of drug candidates in clinical trials, according to a report published July in Optics Express.
“Deployment of qualified imaging biomarkers lags apparent technology capabilities,” wrote lead author Andrew Buckler of Buckler Biomedical in Wenham, Mass., and of the Quantitative Imaging Biomarkers Alliance, an initiative of the Radiological Society of North America. “The lack of consensus methods and qualification evidence needed for large-scale multi-center trials, as well as the standardization that allows them, are widely acknowledged to be the limiting factors."
Buckler and colleagues reviewed efforts made to collect and utilize publicly available data sets--which range from scans of mock tumors in artificial torsos to clinical data from lung cancer patients--to improve the practicality of imaging biomarkers by reducing the variability of measurements.
The researchers served as stewards for the NCI-funded library of lung cancer clinical images, the Reference Image Database to Evaluate Response to Therapy (RIDER), and found:
Buckler and colleagues also determined that data sets that have been created from the collaborations of multiple groups, including the research, regulatory and pharmaceutical communities, are enabling developments within lung cancer treatment that were not in existence when individuals maintained their own data sets.
“The drug development industry is faced with increasing costs and decreasing success rates. New ways to understand biology as well as the increasing interest in personalized treatments for smaller patient segments requires new capabilities for the rapid assessment of treatment responses,” the study concluded.
“Deployment of qualified imaging biomarkers lags apparent technology capabilities,” wrote lead author Andrew Buckler of Buckler Biomedical in Wenham, Mass., and of the Quantitative Imaging Biomarkers Alliance, an initiative of the Radiological Society of North America. “The lack of consensus methods and qualification evidence needed for large-scale multi-center trials, as well as the standardization that allows them, are widely acknowledged to be the limiting factors."
Buckler and colleagues reviewed efforts made to collect and utilize publicly available data sets--which range from scans of mock tumors in artificial torsos to clinical data from lung cancer patients--to improve the practicality of imaging biomarkers by reducing the variability of measurements.
The researchers served as stewards for the NCI-funded library of lung cancer clinical images, the Reference Image Database to Evaluate Response to Therapy (RIDER), and found:
- Patient images from one study show patient lesions scanned repeatedly after longer time periods, while another study scanned patients repeatedly within 15 minutes. This allowed the minimum detectable changes in tumor size to be observed.
- Thickness of CT scan slices used to piece together a 3D lesion image can have a large impact on the accuracy of lesion volume calculations.
- After analysis comparing computer algorithms to physicians, the computer algorithms were determined to be able to reach conclusions similar to those of trained radiologists.
Buckler and colleagues also determined that data sets that have been created from the collaborations of multiple groups, including the research, regulatory and pharmaceutical communities, are enabling developments within lung cancer treatment that were not in existence when individuals maintained their own data sets.
“The drug development industry is faced with increasing costs and decreasing success rates. New ways to understand biology as well as the increasing interest in personalized treatments for smaller patient segments requires new capabilities for the rapid assessment of treatment responses,” the study concluded.