SciMoCa™ is an Independent Secondary Dose Check- and Plan QA-Software based on Monte Carlo

  • as independent as a measurement
  • as reliable as a TPS
  • maximal accuracy guaranteed by Monte Carlo algorithm

A brief introduction into some SciMoCa™ features:

  • Accuracy of Monte Carlo

  • Customized beam models, individually commissioned

  • All types of conventional linacs from Elekta®, Varian® (including Halcyon™ and Ethos™) and Siemens, as well as the Accuray® TomoTherapy®, Radixact® and CyberKnife®-systems (cones, Iris, Incise2), and the ZAP-X®-system

  • NEW: Elekta® Unity MR-Linac

  • All treatment planning systems that provide DICOM® export: Eclipse®, Monaco®, RayStation®, Brainlab®, Pinnacle®, as well as the Accuray® Precision®-TPS and the ZAP-X®-TPS

  • 3D, IMRT, VMAT, SBRT, SRS (MLC-shaped photons), HyperArc

  • SRS-cones (photons)

  • Electrons (applicators and cutouts)

  • Streamlined web-based user interface

  • Extendable, service-oriented architecture

  • Seamless clinical integration

  • Automated workflow

  • Comprehensive analysis and reporting

  • No proprietary hardware needed

The SciMoCa™ dose engine shares its fundamental concepts with the voxel Monte Carlo (VMC) family of codes, e.g. VMC++ or XVMC [4–6], coupled with a powerful and versatile virtual source model (VSM) that is based on published concepts [7–9].

SciMoCa™ Concept for Monte-Carlo Beam Commissioning

Virtual source models can contain very fine detail, but are much more efficient than explicit simulations (e.g. BEAMnrc) or phase space files. A virtual source model has a number of parameters:

  • some can be determined once and for all from high-quality simulations (BEAMnrc)
  • some need to be adjusted to a specific accelerator

Adjustment becomes necessary because the spectrum of primary photons from the electron target depends on:

  • mean energy of electron beam
  • energy spread of electron beam
  • focus size
  • focus form
  • thickness of target and flattening filter (down to fractions of a mm!)
  • exact material composition of target, collimators and filters (often not disclosed to sufficient detail)
  • …

Clinical Examples

SciMoCa™ sets new standards in ACCURACY and SPEED in radiotherapy dose computation [1,2,3]

ACCURACY

Comparison to other industry-leading TPS-dose calculation algorithms shows excellent agreement:

SPEED

Calculation times on 24-core Intel Core i9-14900; stat. MC-uncertainty 1%

Example: Elekta 6MV FF Benchmark

Customer data: Exceptionally good quality of the measurements

 Excellent beam-model fit of depth-dose-curves over the full range of field sizes

  Excellent beam-model fit of output-factors over the full range of field sizes

detector used for measurements: microDiamond

residual errors (<~0.3%) are in the order of noise of the detector and MC-calculations

Some Cool Facts

Numbers Speak For Themselves

Satisfied Clients
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Years of Experience
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Completed Projects
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Worldwide Installations of SciMoCa™

Do you want to know more about SciMoCa™?

Watch a webinar of Prof. Markus Alber, Medical Physicist at University of Heidelberg, Germany, speaking during AAPM 2018. Learn about the Monte Carlo algorithm and benefits of SciMoCa™ for secondary dose check and plan QA.

References

[1] Stanhope CW, Drake DG, Liang J, Alber M, Söhn M, Habib C, Willcut V, Yan D. Evaluation of Machine Log-Files/MC based Treatment Planning and Delivery QA as Compared to ArcCHECK QA. Med Phys. 2018 Jul;45(7):2864-74

[2] Hoffmann L, Alber M, Söhn M, Elstrøm UV. Validation of the Acuros XB dose calculation algorithm versus Monte Carlo for clinical treatment plans. Med Phys. 2018 Aug;45(8):3909-15

[3] Milder MTW, Alber M, Söhn M, Hoogeman MS. Commissioning and clinical implementation of the first commercial independent Monte Carlo 3D dose calculation to replace CyberKnife M6™ patient-specific QA measurements. JACMP 2020 Nov;21(11):304-11

[4] Kawrakow I, Fippel M, Friedrich K. 3D electron dose calculation using a Voxel based Monte Carlo algorithm (VMC). Med Phys. 1996;23:445-57

[5] Kawrakow I. Improved modeling of multiple scattering in the Voxel Monte Carlo model. Med Phys. 1997 Apr;24:505-17

[6] Kawrakow I, Fippel M. Investigation of variance reduction techniques for Monte Carlo photon dose calculation using XVMC. Phys Med Biol. 2000;45:2163-83

[7] Sikora M, Dohm O, Alber M. A virtual photon source model of an Elekta linear accelerator with integrated mini MLC for Monte Carlo based IMRT dose calculation. Phys Med Biol. 2007;52:4449-63

[8] Sikora M, Alber M. A virtual source model of electron contamination of a therapeutic photon beam. Phys Med Biol. 2009;54:7329-44

[9] Sikora M, Virtual Source Modelling of Photon Beams for Monte Carlo Based Radiation Therapy Treatment Planning. PhD thesis