Fast online Monte Carlo-based IMRT planning for the MRI linear accelerator

Bol, Gijsbert H.; Hissoiny, Sami; Lagendijk, J J W; Raaymakers, B W

doi:10.1088/0031-9155/57/5/1375

Cited by 53 publications

(52 citation statements)

References 20 publications

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“…Although there exists an evaluation study of a standalone version of the GPUMCD algorithm for IMRT optimization, (17) no work has been done, to our knowledge, on the experimental evaluation of the GPUMCD algorithm implemented in the Monaco TPS.…”

Section: Introductionmentioning

confidence: 99%

Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system

Paudel

Kim

Sarfehnia

et al. 2016

J Applied Clin Med Phys

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A new GPU‐based Monte Carlo dose calculation algorithm (GPUMCD), developed by the vendor Elekta for the Monaco treatment planning system (TPS), is capable of modeling dose for both a standard linear accelerator and an Elekta MRI linear accelerator. We have experimentally evaluated this algorithm for a standard Elekta Agility linear accelerator. A beam model was developed in the Monaco TPS (research version 5.09.06) using the commissioned beam data for a 6 MV Agility linac. A heterogeneous phantom representing several scenarios — tumor‐in‐lung, lung, and bone‐in‐tissue — was designed and built. Dose calculations in Monaco were done using both the current clinical Monte Carlo algorithm, XVMC, and the new GPUMCD algorithm. Dose calculations in a Pinnacle TPS were also produced using the collapsed cone convolution (CCC) algorithm with heterogeneity correction. Calculations were compared with the measured doses using an ionization chamber (A1SL) and Gafchromic EBT3 films for 2×2 cm2,5×5 cm2, and 10×2 cm2 field sizes. The percentage depth doses (PDDs) calculated by XVMC and GPUMCD in a homogeneous solid water phantom were within 2%/2 mm of film measurements and within 1% of ion chamber measurements. For the tumor‐in‐lung phantom, the calculated doses were within 2.5%/2.5 mm of film measurements for GPUMCD. For the lung phantom, doses calculated by all of the algorithms were within 3%/3 mm of film measurements, except for the 2×2 cm2 field size where the CCC algorithm underestimated the depth dose by ∼5% in a larger extent of the lung region. For the bone phantom, all of the algorithms were equivalent and calculated dose to within 2%/2 mm of film measurements, except at the interfaces. Both GPUMCD and XVMC showed interface effects, which were more pronounced for GPUMCD and were comparable to film measurements, whereas the CCC algorithm showed these effects poorly.PACS number(s): 87.53.Bn, 87.55.dh, 87.55.km

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Section: Introductionmentioning

confidence: 99%

Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system

Paudel

Kim

Sarfehnia

et al. 2016

J Applied Clin Med Phys

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“…This hybrid approach is especially valuable for MRI-IMRT where the Monte Carlo method may be the only method that is capable of dealing with complex dose deposition in a heterogeneous medium subject to a magnetic field. 18,41 The Monte Carlo methods like , on the other hand, may require many approximations in order to be practical in the clinic, and these approximations may not be thoroughly communicated to an end-user for proprietary reasons. We therefore developed a fast, GPUaccelerated Monte Carlo dose calculation system based on .…”

Section: Discussionmentioning

confidence: 99%

“…Most recent developments include online IMRT planning using  for the MRI-linear accelerator 18 and the clinical use of  on the MRIdian system (ViewRay, Inc., Cleveland, OH). The MRIdian system integrates a 0.35 T whole-body MR imaging system into an RT delivery system consisting of a rotating gantry with three 60 Co heads spaced 120…”

Section: Introductionmentioning

confidence: 99%

A GPU‐accelerated Monte Carlo dose calculation platform and its application toward validating an MRI‐guided radiation therapy beam model

et al. 2016

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Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on  and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods:  was first translated from  to ++ and the result was confirmed to produce equivalent results to the original code. The ++ code was then adapted to  in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make g highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply g as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and g. Ultimately, g was applied toward independent validation of patient doses calculated by MRIdian's . Results: An acceleration factor of 152 was achieved in comparison to the original single-thread  implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with g with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: A Monte Carlo simulation platform was developed based on a GPU-accelerated version of . This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems. C

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“…Genomic DNA was extracted and fingerprinted with the probe IS6110 as described previously (13,14). Genomic DNA was sequenced using an Illumina Genome Analyzer IIx (Illumina Inc., CA) (12,15) and analyzed using Maq (http://maq.sourceforge.net).…”

Section: Ethicsmentioning

confidence: 99%

A Mutation in the 16S rRNA Decoding Region Attenuates the Virulence of Mycobacterium tuberculosis

et al. 2016

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g Mycobacterium tuberculosis contains a single rRNA operon that encodes targets for antituberculosis agents, including kanamycin. To date, only four mutations in the kanamycin binding sites of 16S rRNA have been reported in kanamycin-resistant clinical isolates. We hypothesized that another mutation(s) in the region may dramatically decrease M. tuberculosis viability and virulence. Here, we describe an rRNA mutation, U1406A, which was generated in vitro and confers resistance to kanamycin while highly attenuating M. tuberculosis virulence. The mutant showed decreased expression of 20% (n ‫؍‬ 361) of mycobacterial proteins, including central metabolic enzymes, mycolic acid biosynthesis enzymes, and virulence factors such as antigen 85 complexes and ESAT-6. The mutation also induced three proteins, including KsgA (Rv1010; 16S rRNA adenine dimethyltransferase), which closely bind to the U1406A mutation site on the ribosome; these proteins were associated with ribosome maturation and translation initiation processes. The mutant showed an increase in 17S rRNA (precursor 16S rRNA) and a decrease in the ratio of 30S subunits to the 70S ribosomes, suggesting that the U1406A mutation in 16S rRNA attenuated M. tuberculosis virulence by affecting these processes.

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Fast online Monte Carlo-based IMRT planning for the MRI linear accelerator

Cited by 53 publications

References 20 publications

Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system

Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system

A GPU‐accelerated Monte Carlo dose calculation platform and its application toward validating an MRI‐guided radiation therapy beam model

A Mutation in the 16S rRNA Decoding Region Attenuates the Virulence of Mycobacterium tuberculosis

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