Newswise — Orlando, Fla., February 8, 2013 – Monitoring the hepatic function of unresectable liver cancer patients, measured by 99mTc-labeled iminodiacetic acid (HIDA) via single-photon emission computed tomography (SPECT) prior to and during radiation therapy, provides vital information that could guide more customized treatment plans and reduce risks of liver injury, according to research being presented at the 2013 Cancer Imaging and Radiation Therapy Symposium. This Symposium is sponsored by the American Society for Radiation Oncology (ASTRO) and the Radiological Society of North American (RSNA).
This study included 14 patients who had unresectable intrahepatic cancers and were treated with 3-D conformal radiation therapy (3-D CRT), intensity modulated radiation therapy (IMRT) or stereotactic body radiation therapy (SBRT) at a median dose of 52 Gy. Patients underwent HIDA SPECT scanning prior to radiation therapy, after delivery of 50 to 60 percent of the planned doses and one month after completion of radiation therapy. In addition, indocyanine green tests, a measure of overall liver function, were performed +/- one day of each SPECT scan. The 27 dynamic HIDA SPECT volumes were acquired over a 60-minute period after the administration of 10 mCi 99mTc-labeled HIDA on a SPECT/CT scanner.
Measuring the regional liver function prior to radiation therapy allows assessment of the precondition of the patient’s liver function. Evaluating the change of the regional liver function during the mid-course of radiation therapy indicates the response of the individual patient’s liver to radiation doses. Combining the planned radiation doses with the regional liver function assessment and re-assessment, investigators developed a model to predict the regional liver function post-radiation therapy. This information is vital to providing patients with the highest radiation doses for better tumor control, while minimizing the risk for each patient.
“Through this assessment method, patients could potentially receive more treatment doses tailored to meet their needs, based on their liver function,” said Hesheng Wang, PhD, the lead study author and a postdoctoral fellow in radiation oncology at the University of Michigan in Ann Arbor, Mich. “The physiological adaptation of radiation therapy based upon individual response assessment is a valuable new paradigm worth additional testing.”
The abstract, “Hepatic Function Model Based upon HIDA SPECT and Dose for Physiological Adaptive RT,” will be presented in detail during a scientific session at 10:30 a.m. Eastern time on Friday, February 8, 2013. To speak with Hesheng Wang, PhD, call Michelle Kirkwood on February 8-9, 2013, in the Press Office at the Hilton Orlando Lake Buena Vista in the Walt Disney World Resort at 407-560-2314 or email email@example.com.
2013 Cancer Imaging and Radiation Therapy Symposium
Abstracts of Interest News Briefing, Saturday, February 9, 2013, 7:00 a.m. – 7:45 a.m. ET
Oral Presentation: Friday, February 8, 10:30 a.m. Eastern time
4 Hepatic Function Model Based upon HIDA SPECT and Dose for Physiological Adaptive RT
H. Wang, M. Feng, K. Frey, J. Balter, R. Ten Haken, T. Lawrence, Y. Cao, University of Michgian, Ann Arbor, MI
Purpose/Objective(s): High dose radiation therapy (RT) for hepatic cancer treatment is limited by development of radiation-induced liver disease. We hypothesized that hepatic function measured by 99mTc-labeled imindodiacetic acid (HIDA) SPECT prior to and during RT, combined with radiation doses, could predict post-RT hepatic function, and thereby could support physiological adaptive RT.
Materials/Methods: Fourteen patients who had unresectable intrahepatic cancers and were treated with 3D conformal RT, IMRT or SBRT (median dose 52 Gy) underwent dynamic HIDA SPECT scanning prior to RT, after delivery of 50%-60% planned doses, and one month after the completion of RT. Indocyanine green (ICG) tests (a measure of overall liver function) were performed +/-1 day of each SPECT scan. The 27 dynamic HIDA SPECT volumes were acquired over 60-min after the administration of 5-15mCi 99mTc-labled HIDA on a SPECT/CT scanner. The 3D volumetric hepatic extract fraction (HEF) images of the liver were quantified by deconvolution of the liver-voxel radioactivity curves from the vascular input function measured from a volume of interest in the spleen. After co-registration of CT/SPECT with treatment planning CT, planned 2 Gy-equivalent dose distributions were overlaid on the HEF images. The HEF dose-response functions during and post RT were generated for regions corresponding to planned iso-dose intervals of 4 Gy. To validate HEF, the mean HEFs in the whole liver were correlated with the ICG clearance rate. Two predictive models, one priori and another adaptive, based upon the HEF measured prior to or during RT and planned doses, were developed for prediction of hepatic function post RT by multivariate linear regression.
Results: The mean HEFs were significantly correlated with ICG clearance rates (r=0.83, p<0.001), regardless of the time of measurements. Dose-dependent reductions in the regional HEFs one month post RT were observed in 13 patients. In the priori model, the regional HEF post RT was predicted by the planned local total dose and the HEF assessed prior to RT (R2=0.35, p<0.00001); in which, as a group average, every Gy reduced the HEF by approximately 0.24%. In the adaptive model, the regional HEF post RT was predicted by the HEF re-assessed at the mid-course of RT and the planned remaining dose (R2=0.54, p<0.00001), indicating an improvement in the model prediction by the mid-course HEF that measures individual patient and regional sensitivity to radiation.
Conclusions: Predictive models relating planned doses with either hepatic function measured prior to RT, or that assessed at the mid-course of RT, could aid in physiological adaptive RT for intrahepatic cancer treatment and management of risks for liver injury. Supported by RO1CA132834.
Author Disclosure Block:
H. Wang: None. M. Feng: None. K. Frey: None. J. Balter: None. R. Ten Haken: None. T. Lawrence: None. Y. Cao: None.