Estimating size specific dose estimate from computed tomography radiograph localizer with radiation risk assessment.

BACKGROUND: Quantifying radiation burden is necessary for optimizing imaging protocols. The normalized dose coefficient (NDC) is determined from the water-equivalent diameter (WED) and is used to scale the CTDIvol based on body habitus to determine the size specific dose estimate (SSDE). In this study we determine the SSDE prior to the CT scan and how sensitive the SSDE from WED is to the lifetime attributable risk (LAR) from BEIR VII. METHOD: For calibration, phantom images are used to relate the mean pixel values along a profile ( PPV ¯ $\overline {{\rm{PPV}}} $ ) of the CT localizer to the water-equivalent area (AW ) of the CT axial scan at the same z-location. Images of the CTDIvol phantoms (32 cm, 16 cm, and ∼1 cm) and ACR phantom (Gammex 464) were acquired on four scanners. The relationship between the AW and PPV ¯ $\overline {{\rm{PPV}}} $ was used to calculate the WED from the CT localizer for patient scans. A total of 790 CT examinations of the chest and abdominopelvic regions were used in this study. The effective diameter (ED) was calculated from the CT localizer. The LAR was calculated based on the patient chest and abdomen using the National Cancer Institute Dosimetry System for Computed Tomography (NCICT). The radiation sensitivity index (RSI) and risk differentiability index (RDI) were calculated for SSDE and CTDIvol. RESULTS: The WED from CT localizers and CT axials scans show good correlation (R2  = 0.96) with the maximum percentage difference being 13.45%. The NDC from WED correlates poorly with LAR for lungs (R2  = 0.18) and stomach (R2  = 0.19), however that is the best correlation. CONCLUSION: The SSDE can be determined within 20% as recommended by the report of AAPM TG 220. The CTDIvol and SSDE are not good surrogates for radiation risk, however the sensitivity for SSDE improves when using WED instead of ED.

The radiobiological impact of motion tracking of liver, pancreas and kidney SBRT tumors in a MR-linac.

The purpose of this work is to evaluate and quantify the potential radiobiological advantages of tumor tracking using the MR-linac for three disease sites: liver, pancreas and kidney. From each disease site, three patients were selected and 4DCT data sets were used. We applied two planning methods using the Monaco treatment planning system (Elekta AB,Stockholm,Sweden): (1) the conventional ITV method using a 6MV Agility beam and (2) a simulated tracking method using MLC GTV tracking with a 7MV MR-linac beam model incorporating a 1.5 T transverse magnetic field. A 5 mm isotropic PTV margin was added to the ITV or the GTV, and 95% of the PTV volume received 100% of the prescription dose. To evaluate the potential radiobiological advantages of tumor tracking, the normal tissue complication probabilities (NTCPs) were calculated for each organ at risk (OAR) using the Layman Kutcher Burman (LKB) model. The average reduction in the target volume, due to tracking, was 31.1%, 26.3% and 26.9% for liver, pancreas and kidney patients, respectively. For each OAR, the % differences in NTCP between the two methods were calculated. The mean 2 Gy equivalent OAR dose for all patients was less than 29.1 Gy, below which the NTCP for most OARs was not sensitive to equivalent uniform dose (EUD). As a result, a NTCP benefit, due to tracking, was observed in 26% of the data. For all three disease sites, the maximum NTCP improvements were for the normal kidney, the bowels, and the duodenum, with reductions in associated toxicities of 79% (radiation nephropathy), 69% (stricture/fistula) and 25% (ulceration), respectively. This study demonstrates the potential benefit of using a MR-linac tracking system to reduce NTCPs. The normal kidney, the bowels and the duodenum showed the largest NTCP improvements. This, in part, is due to the rapid changes in NTCP for small EUD changes.

The development of a 4D treatment planning methodology to simulate the tracking of central lung tumors in an MRI-linac.

PURPOSE: Targeting and tracking of central lung tumors may be feasible on the Elekta MRI-linac (MRL) due to the soft-tissue visualization capabilities of MRI. The purpose of this work is to develop a novel treatment planning methodology to simulate tracking of central lung tumors with the MRL and to quantify the benefits in OAR sparing compared with the ITV approach. METHODS: Full 4D-CT datasets for five central lung cancer patients were selected to simulate the condition of having 4D-pseudo-CTs derived from 4D-MRI data available on the MRL with real-time tracking capabilities. We used the MRL treatment planning system to generate two plans: (a) with a set of MLC-defined apertures around the target at each phase of the breathing ("4D-MRL" method); (b) with a fixed set of fields encompassing the maximum inhale and exhale of the breathing cycle ("ITV" method). For both plans, dose accumulation was performed onto a reference phase. To further study the potential benefits of a 4D-MRL method, the results were stratified by tumor motion amplitude, OAR-to-tumor proximity, and the relative OAR motion (ROM). RESULTS: With the 4D-MRL method, the reduction in mean doses was up to 3.0 Gy and 1.9 Gy for the heart and the lung. Moreover, the lung's V12.5 Gy was spared by a maximum of 300 cc. Maximum doses to serial organs were reduced by up to 6.1 Gy, 1.5 Gy, and 9.0 Gy for the esophagus, spinal cord, and the trachea, respectively. OAR dose reduction with our method depended on the tumor motion amplitude and the ROM. Some OARs with large ROMs and in close proximity to the tumor benefited from tracking despite small tumor amplitudes. CONCLUSIONS: We developed a novel 4D tracking methodology for the MRL for central lung tumors and quantified the potential dosimetric benefits compared with our current ITV approach.

Online Adaptive Radiation Therapy.

The current paradigm of radiation therapy has the treatment planned on a snapshot dataset of the patient's anatomy taken at the time of simulation. Throughout the course of treatment, this snapshot may vary from initial simulation. Although there is the ability to image patients within the treatment room with technologies such as cone beam computed tomography, the current state of the art is largely limited to rigid-body matching and not accounting for any geometric deformations in the patient's anatomy. A plan that was once attuned to the initial simulation can become suboptimal as the treatment progresses unless improved technologies are brought to bear. Adaptive radiation therapy (ART) is an evolving paradigm that seeks to address this deficiency by accounting for ongoing changes in the patient's anatomy and/or physiology during the course of treatment, affording an increasingly more accurate targeting of disease. ART relies on several components working in concert, namely in-room treatment image guidance, deformable image registration, automatic recontouring, plan evaluation and reoptimization, dose calculation, and quality assurance. Various studies have explored how a putative ART solution would improve the current state of the art of radiation therapy-some centers have even clinically implemented online adaptation. These explorations are reviewed here for a variety of sites.