RaySearch Americas Inc. (NY) has introduced a commercial Monte Carlo dose algorithm (RS-MC) for routine clinical use in proton spot scanning. In this report, we provide a validation of this algorithm against phantom measurements and simulations in the GATE software package. We also compared the performance of the RayStation analytical algorithm (RS-PBA) against the RS-MC algorithm. A beam model (G-MC) for a spot scanning gantry at our proton center was implemented in the GATE software package. The model was validated against measurements in a water phantom and was used for benchmarking the RS-MC. Validation of the RS-MC was performed in a water phantom by measuring depth doses and profiles for three spread-out Bragg peak (SOBP) beams with normal incidence, an SOBP with oblique incidence, and an SOBP with a range shifter and large air gap. The RS-MC was also validated against measurements and simulations in heterogeneous phantoms created by placing lung or bone slabs in a water phantom. Lateral dose profiles near the distal end of the beam were measured with a microDiamond detector and compared to the G-MC simulations, RS-MC and RS-PBA. Finally, the RS-MC and RS-PBA were validated against measured dose distributions in an Alderson-Rando (AR) phantom. Measurements were made using Gafchromic film in the AR phantom and compared to doses using the RS-PBA and RS-MC algorithms. For SOBP depth doses in a water phantom, all three algorithms matched the measurements to within  ±3% at all points and a range within 1 mm. The RS-PBA algorithm showed up to a 10% difference in dose at the entrance for the beam with a range shifter and >30 cm air gap, while the RS-MC and G-MC were always within 3% of the measurement. For an oblique beam incident at 45°, the RS-PBA algorithm showed up to 6% local dose differences and broadening of distal fall-off by 5 mm. Both the RS-MC and G-MC accurately predicted the depth dose to within  ±3% and distal fall-off to within 2 mm. In an anthropomorphic phantom, the gamma index (dose tolerance  =  3%, distance-to-agreement  =  3 mm) was greater than 90% for six out of seven planes using the RS-MC, and three out seven for the RS-PBA. The RS-MC algorithm demonstrated improved dosimetric accuracy over the RS-PBA in the presence of homogenous, heterogeneous and anthropomorphic phantoms. The computation performance of the RS-MC was similar to the RS-PBA algorithm. For complex disease sites like breast, head and neck, and lung cancer, the RS-MC algorithm will provide significantly more accurate treatment planning.

A substantial barrier to the single- and multi-institutional aggregation of data to supporting clinical trials, practice quality improvement efforts, and development of big data analytics resource systems is the lack of standardized nomenclatures for expressing dosimetric data. To address this issue, the American Association of Physicists in Medicine (AAPM) Task Group 263 was charged with providing nomenclature guidelines and values in radiation oncology for use in clinical trials, data-pooling initiatives, population-based studies, and routine clinical care by standardizing: (1) structure names across image processing and treatment planning system platforms; (2) nomenclature for dosimetric data (eg, dose-volume histogram [DVH]-based metrics); (3) templates for clinical trial groups and users of an initial subset of software platforms to facilitate adoption of the standards; (4) formalism for nomenclature schema, which can accommodate the addition of other structures defined in the future. A multisociety, multidisciplinary, multinational group of 57 members representing stake holders ranging from large academic centers to community clinics and vendors was assembled, including physicists, physicians, dosimetrists, and vendors. The stakeholder groups represented in the membership included the AAPM, American Society for Radiation Oncology (ASTRO), NRG Oncology, European Society for Radiation Oncology (ESTRO), Radiation Therapy Oncology Group (RTOG), Children's Oncology Group (COG), Integrating Healthcare Enterprise in Radiation Oncology (IHE-RO), and Digital Imaging and Communications in Medicine working group (DICOM WG); A nomenclature system for target and organ at risk volumes and DVH nomenclature was developed and piloted to demonstrate viability across a range of clinics and within the framework of clinical trials. The final report was approved by AAPM in October 2017. The approval process included review by 8 AAPM committees, with additional review by ASTRO, European Society for Radiation Oncology (ESTRO), and American Association of Medical Dosimetrists (AAMD). This Executive Summary of the report highlights the key recommendations for clinical practice, research, and trials.

Detectors with depth-encoding allow a PET scanner to simultaneously achieve high sensitivity and high spatial resolution. Methods: A prototype PET scanner, consisting of depth-encoding detectors constructed by dual-ended readout of lutetium oxyorthosilicate (LSO) arrays with 2 position-sensitive avalanche photodiodes (PSAPDs), was developed. The scanner comprised 2 detector plates, each with 4 detector modules, and the LSO arrays consisted of 7 · 7 elements, with a crystal size of 0.9225 · 0.9225 · 20 mm and a pitch of 1.0 mm. The active area of the PSAPDs was 8 · 8 mm. The performance of individual detector modules was characterized. A line-source phantom and a hot-rod phantom were imaged on the prototype scanner in 2 different scanner configurations. The images were reconstructed using 20, 10, 5, 2, and 1 depth-of-interaction (DOI) bins to demonstrate the effects of DOI resolution on reconstructed image resolution and visual image quality. Results: The flood histograms measured from the sum of both PSAPD signals were only weakly depth-dependent, and excellent crystal identification was obtained at all depths. The flood histograms improved as the detector temperature decreased. DOI resolution and energy resolution improved significantly as the temperature decreased from 20°C to 10°C but improved only slightly with a subsequent temperature decrease to 0°C. A full width at half maximum (FWHM) DOI resolution of 2 mm and an FWHM energy resolution of 15% were obtained at a temperature of 10°C. Phantom studies showed that DOI measurements significantly improved the reconstructed image resolution. In the first scanner configuration (parallel detector planes), the image resolution at the center of the field of view was 0.9-mm FWHM with 20 DOI bins and 1.6-mm FWHM with 1 DOI bin. In the second scanner configuration (detector planes at a 40°angle), the image resolution at the center of the field of view was 1.0-mm FWHM with 20 DOI bins and was not measurable when using only 1 bin. Conclusion: PET scanners based on this detector design offer the prospect of high and uniform spatial resolution (crystal size, ;1 mm; DOI resolution, ;2 mm), high sensitivity (20-mm-thick detectors), and compact size (DOI encoding permits detectors to be tightly packed around the subject and minimizes number of detectors needed). Over the past decade, many small-animal PET scanners have been developed (1-12), and this technology has played a very important role in the rapidly growing field of molecular imaging. High sensitivity is needed to increase signal-to-noise ratio of the images to reliably detect lower levels of radiotracer uptake and to reduce the injected dose (reducing radiation dose to the subject) (13) and scan time (increasing temporal resolution for dynamic studies). High spatial resolution is required to detect small structures and lesions and to improve quantification by reducing the partialvolume effect. A compromise between sensitivity and spatial resolution due to depth-of-interaction (DOI) effects always exists in small-ani...

Small animal PET scanners may be improved by increasing the sensitivity, improving the spatial resolution and improving the uniformity of the spatial resolution across the field of view. This may be achieved by using PET detectors based on crystal elements that are thin in the axial and transaxial directions and long in the radial direction, and by employing depth of interaction (DOI) encoding to minimize the parallax error. With DOI detectors, the diameter of the ring of the PET scanner may also be decreased. This minimizes the number of detectors required to achieve the same solid angle coverage as a scanner with a larger ring diameter and minimizes errors due to non-collinearity of the annihilation photons. In this study, we characterize prototype PET detectors that are finely pixelated with individual LSO crystal element sizes of 0.5 mm × 0.5 mm × 20 mm and 0.7 mm × 0.7 mm × 20 mm, read out at both ends by position sensitive avalanche photodiodes (PSAPDs). Both a specular reflector and a diffuse reflector were evaluated. The detectors were characterized based on the ability to clearly resolve the individual crystal elements, the DOI resolution and the energy resolution. Our results indicate that a scanner based on any of the four detector designs would offer improved spatial resolution and more uniform spatial resolution compared to present day small animal PET scanners. The greatest improvements to spatial resolution will be achieved when the detectors employing the 0.5 mm × 0.5 mm × 20 mm crystals are used. Monte Carlo simulations were performed to demonstrate that 2 mm DOI resolution is adequate to ensure uniform spatial resolution for a small animal PET scanner geometry using these detectors. The sensitivity of such a scanner was also simulated using Monte Carlo simulations and was shown to be greater than 10 % for a four ring scanner with an inner diameter of 6 cm, employing 20 detectors per scanner ring.

Many laboratories are developing depth-encoding detectors to improve the trade-off between spatial resolution and sensitivity in positron emission tomography (PET) scanners. One challenge in implementing these detectors is the need to calibrate the depth of interaction (DOI) response for the large numbers of detector elements in a scanner. In this work, we evaluate two different methods, a linear detector calibration and a linear crystal calibration, for determining DOI calibration parameters. Both methods can use measurements from any source distribution and location, or even the intrinsic LSO background activity, and are therefore well-suited for use in a depth-encoding PET scanner. The methods were evaluated by measuring detector and crystal DOI responses for all eight detectors in a prototype depth-encoding PET scanner. The detectors utilize dual-ended read out of lutetium oxyorthosilicate (LSO) scintillator arrays with position-sensitive avalanche photodiodes (PSAPDs). The LSO arrays have 7×7 elements, with a crystal size of 0.92×0.92×20 mm 3 and pitch of 1.0 mm. The arrays are read out by two 8×8 mm 2 area PSAPDs placed at opposite ends of the arrays. DOI is measured by the ratio of the amplitude of the total energy signals measured by the two PSAPDs. Small variations were observed in the DOI responses of different crystals within an array as well as DOI responses for different arrays. A slightly nonlinear dependence of the DOI ratio on depth was observed and the nonlinearity was larger for the corner and edge crystals. The DOI calibration parameters were obtained from the DOI responses measured in singles mode. The average error between the calibrated DOI and the known DOI was 0.8 mm if a linear detector DOI calibration was used, and 0.5 mm if a linear crystal DOI calibration was used. A line source phantom and a hot rod phantom were scanned on the prototype PET scanner. DOI measurement significantly improved the image spatial resolution no matter which DOI calibration method was used. A linear crystal DOI calibration provided slightly better image spatial resolution compared with a linear detector DOI calibration.

By using detectors with good depth encoding accuracy (~ 2 mm), an animal PET scanner can be built with a small ring diameter and thick crystals to simultaneously obtain high spatial resolution and high sensitivity. However, there will be large wedge-shaped gaps between detector modules in such a scanner if traditional cuboid crystal arrays are used in a polygonal arrangement. The gaps can be minimized by using tapered scintillator arrays enabling the sensitivity of the scanner to be further improved. In this work, tapered lutetium oxyorthosilicate (LSO) arrays with different crystal dimensions and different combinations of inter-crystal reflector and crystal surface treatments were manufactured and their performance was evaluated. Arrays were read out from both ends by position-sensitive avalanche photodiodes (PSAPDs). In the optimal configuration, arrays consisting of 0.5 mm LSO elements could be clearly resolved and a depth of interaction resolution of 2.6 mm was obtained for a 20-mm thick array. For this tapered array, the intrinsic spatial is degraded from 0.67 mm to 0.75 mm compared to a standard cuboidal array with similar dimensions, while the increase in efficiency is 41%. Tapered scintillator arrays offer the prospect of improvements in sensitivity and sampling for small-bore scanners, without large increases in manufacturing complexity.

Accurate understanding and modeling of respiration-induced uncertainties is essential in image-guided radiotherapy. Explicit modeling of overall lung motion and interaction among different organs promises to be a useful approach. Recently, preliminary studies on 3D fluoroscopic treatment imaging and tumor localization based on Principal Component Analysis (PCA) motion models and cost function optimization have shown encouraging results. However, the performance of this technique for varying breathing parameters and under realistic conditions remains unclear and thus warrants further investigation. In this work, we present a systematic evaluation of a 3D fluoroscopic image generation algorithm via two different approaches. In the first approach the model’s accuracy is tested for changing parameters for sinusoidal breathing. These parameters included changing respiratory motion amplitude, period, and baseline shift. The effects of setup error, imaging noise and different tumor sizes are also examined. In the second approach, we test the model for anthropomorphic images obtained from a modified XCAT phantom. This set of experiments is important as all the underlying breathing parameters are simultaneously tested, as in realistic clinical conditions. Based on our simulation results for more than 250 seconds of breathing data for 8 different lung patients, the overall tumor localization accuracy of the model in left-right (LR), anterior-posterior (AP) and superior-inferior (SI) directions are 0.1 ± 0.1 mm, 0.5 ± 0.5 mm and 0.8 ± 0.8 mm respectively. 3D tumor centroid localization accuracy is 1.0 ± 0.9 mm.

No abstract