Marc Mackenzie, PhD, FCCPM

Marc MacKenzie

Assistant Professor, Division of Medical Physics, Department of Oncology, University of Alberta

Director of Medical Physics, Community Oncology

BSc Physics: U of New Brunswick - 1993
MSc Physics: U of Alberta -1996
PhD Physics: U of Alberta -2000

Member: Canadian College of Physicists in Medicine
Fellow: Canadian College of Physicists in Medicine

Research Interests

My research interests of late have been in the areas of radiation dosimetry, Monte Carlo methods as applied to radiation therapy, and the optimizing of intensity modulated radiation therapy, especially as it pertains to helical tomotherapy.

Radiation Dosimetry

Accurate assessment of the quantity of radiation energy, also denoted as 'radiation dose' or simply 'dose', that is imparted to the patient is key in radiation therapy. Clinical experience dictates that certain levels of radiation dose will achieve the desired tumour control, and that certain levels of radiation to nearby healthy tissues can be tolerated without undue complications. Knowing how much dose both healthy and diseased tissues receive is therefor needed to achieve the desired clinical outcome. As well, quantifying patient response as a function of dose delivered may feed directly into radiobiological modeling, and to ensure that the data collected is of optimal quality requires accurate assessment of dose delivered. Methods which have been developed or refined at our centre involve the use both novel and conventional detectors.

Monte Carlo Methods

The most sophisticated and accurate means of calculating radiation dose and radiation interactions is by direct simulation of individual photons using known interaction probabilities. This technique is known as a Monte Carlo method, and for the accuracy required for most medical physics applications this may involve the simulation of billions of photons. These methods may be used to determine the quantities used in converting measured charge values from ionization chambers to dose, or in determining the response of other novel detectors to therapy beams (e.g. CR plates). Both of these remain active areas of research in medical physics.

Typically, dedicated computers known as treatment planning systems are used to calculate the 3D radiation distribution that will result when a patient radiation treatment plan is implemented. The algorithms used are generally based on radiation dose interactions in water, with correction factors to infer the dose in a patient, and the data is optimized for large radiation field sizes. The calculations that are in wide spread use may break down in certain situations (e.g. small fields, large deviations from water electron density). One may use Monte Carlo methods to simulate the 3D dose imparted to patient from a given treatment plan with greater accuracy than may be achieved by any other means.

Intensity Modulated Radiation Therapy and Inverse Planning

The machines generally used to treat patients with radiation beams have been designed to output broad beams of radiation with 'flat' energy distributions orthogonal to the beam direction. By varying the intensities across the field and by using multiple converging beams with specific non uniform intensity profiles, however, one may achieve superior dose homogeneity to the target structure and improved sparing of nearby structures. This method of delivery is known as Intensity Modulated Radiation Therapy (IMRT), and requires the use of computers and novel algorithms to determine the required profiles to achieve some desired distribution. Inverse planning is the use of these computers in conjunction with optimizations algorithms to iteratively arrive close to the desired dose distribution.

Selected Publications

N. Pervez, C. Small, M. MacKenzie, D. Yee, M. Parliament, S. Ghosh, A. Mihai, J. Amanie, C. Field, D. Murray, G. Fallone, R. Pearcey,
"Acute toxicity in high risk prostate cancer patients treated with androgen suppression and hypofractionated intensity modulated (IMRT),"
Int. Journal of Rad Oncol Biol Phys,76(1), pp. 57-64 (2010).

A. Syme. C. Kirkby, R. Mirzayans, M. Mackenzie, C. Field, B.G. Fallone,
"Relative biological damage and electron fluence in and out of a 6 MV photon field,"
Phys. Med. Biol. 54(12), pp. 6623-6633 (2009).

M.A. Mackenzie, Y. Zhao, C. Kirkby, B.G. Fallone,
"Monte Carlo evaluation of the convolution/superposition algorithm of Hi-Art tomotherapy in heterogeneous phantoms and clinical cases,"
Med. Phys. 36 (8), pp. 3856-3857 (2009).

Y.Zhao, M. Mackenzie, C. Kirkby, B.G. Fallone,
"Monte Carlo evaluation of a treatment planning system for helical tomotherapy in an anthropomorphic heterogeneous phantom and for clinical treatment plans,"
Med Phys, 35(12), pp. 5366-5374 (2008).

D .Yee, R. Pearcey, G. Dundas, J. Hanson, M. Mackenzie, D. Robinson, C. Field, L.Underwood, R. Urtasun, N. Pervez, B.G. Fallone,
"Dosimetric comparison of tomotehrapy versus 4-4 field pelvic box altered fractionation radiotherapy treatment plans for invasive squamous cell carcinoma,"
Cancer Therapy, 6, pp. 553-562 (2008).

Y. Zhao, C. Kirkby, M. Mackenzie, B.G. Fallone,
"Monte Carlo calculation of helical tomotherapy dose delivery,"
Med Phys, 35(8), pp. 3491-3500 (2008).

E.P. Saibishkumar, M. Mackenzie, D. Severin, A. Mihai, J. Hanson, H. Daly, B.G. Fallone, M. Parliament, B. Abdulkarim,
"Skin-Sparing Radiation using Intensity-Modulated Radiotherapy After Conservative Surgery in Early-Stage Breast Cancer: A Planning Study,"
Int J Radiat Oncol Biol Phys, 70(2), pp.485-91 (2008).

E.P. Saibishkumar, M. Parliament, N. Jha, M. Mackenzie, R. Scrimger, C. Field, B.G. Fallone,
"Sparing the parotid glands and surgically transferred submandibular gland with helical tomotherapy in post-operative radiation of head and neck cancer: A planning study,"
Radiotherapy and Oncology, 85, pp. 98-104 (2007).

K. Breitman, S. Rathee, C. Newcomb, B. Murray, D. Robinson, C. Field, H. Warkentin, S. Connors, M. MacKenzie, P. Dunscombe and B.G. Fallone,
"Experimental Validation of the Eclipse AAA Algorithm."
J. App. Clin. Med. Phys, 8(2), pp.76-92, Spring (2007).

D M Drabik, M Mackenzie, and B G Fallone,
"Quantifying appropriate PTV setup margins: analysis of patient setup fidelity and intrafraction motion using post treatment MVCT scans (TomoTherapy)."
Int J Radiat Oncol Bio Phys, 68(4), pp. 1222-1228 (2007).

C Kirkby, C Field, M MacKenzie, A Syme and B G Fallone,
"A Monte Carlo study of the variation of electron fluence in water from a 6 MV photon beam outside of the field."
Phys. Med. Biol. 52, pp. 3563-3578 (2007).

S Kumar, M Parliament, N Jha, M Mackenzie, R Scrimger, C Field, B G Fallone,
"Sparing the parotid glands and surgically transferred submandibular gland with helical tomotherapy in post-operative radiation of head and neck cancer: A planning study."
Radiotherapy and Oncology, 2007 Oct;85(1):98-104.

S D Thomas, M A Mackenzie, D W O Rogers and B G Fallone
"A Monte Carlo Derived TG-51 Equivalent Calibration for Helical Tomotherapy."
Med. Phys., 32 (5), pp. 1346-1353, 2005.

M van Vulpen, C Field, C Raaijmakers, M Parliament, C Terhaard, M A MacKenzie, R Scrimger, J Lagendijk1 and B G Fallone,
"Comparing Step-and-Shoot IMRT with Dynamic Helical Tomotherapy IMRT Plans for Head-and-Neck Cancer."
IJROBP, 62(5), pp. 1535-9, 2005.

S D Thomas, M A Mackenzie, G C Field, A M Syme and B G Fallone,
"Patient Specific Treatment Verifications For Helical Tomotherapy Treatment Plans."
Med. Phys. 32(12), pp. 3793-3800, 2005.

E Barnett, M A MacKenzie, B G Fallone,
"IMRT point dose measurements using a diamond detector."
Radiol. Oncol. 39(1), pp. 71-78, 2005.

M A MacKenzie and D M Robinson,
"Intensity Modulated Arc Deliveries Approximated by a Large Number of Fixed Gantry Position Sliding Window Dynamic Multileaf Collimator Fields."
Medical Physics 29(10), pp. 2359-2365, 2002.

M A Mackenzie, M Lachaine, B Murray, B G Fallone, D M Robinson and G C Field,
"Dosimetric verification of inverse planned step and shoot multileaf collimator fields from a commercial treatment planning system."
Journal of Applied Clinical Medical Physics 2002, Vol. 3, No. 2; 97-109.