Chris Peressotti
Sunnybrook Health Sciences Centre
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Publication
Featured researches published by Chris Peressotti.
Cancer Epidemiology, Biomarkers & Prevention | 2009
Norman F. Boyd; Lisa J. Martin; Anoma Gunasekara; Olga Melnichouk; Gord Maudsley; Chris Peressotti; Martin J. Yaffe; Salomon Minkin
Background: Mammographic density has been found to be strongly associated with risk of breast cancer. We have assessed a novel method of assessing breast tissue that is fully automated, does not require an observer, and measures the volume, rather than the projected area, of the relevant tissues in digitized screen-film mammogram. Methods: Sixteen mammography machines in seven locations in Toronto were calibrated to allow the estimation of the proportion of radiologically dense (stromal and epithelial tissue) and nondense (fatty) tissue represented in each pixel of the mammographic image. This information was combined with a measurement of breast thickness to calculate the volumes of these tissues. Women with newly diagnosed breast cancer (cases) identified on these mammography machines during the years 2000 to 2003 were compared with other women of the same age who did not have breast cancer (controls). Results: Three hundred sixty-four cases and 656 controls were recruited, epidemiologic data were collected, screen-film mammograms were digitized and measured using both a computer-assisted thresholding method, and the new measure of the volume of density. After adjustment for other risk factors, the odds ratio for those in the 5th quintile compared with the 1st quintile was 1.98 (95% confidence interval, 1.3-3.1) for the volume measure and 1.86 (95% CI, 1.1-3.0) for the area measurement. After inclusion of the volume and area measures in a predictive model, the volume measure lost significance, whereas the area measure remained significant. Conclusions: Contrary to our expectations, measurement of the volume of breast tissue did not improve prediction of breast cancer risk. (Cancer Epidemiol Biomarkers Prev 2009;18(6):1754–62)
Cancer Epidemiology, Biomarkers & Prevention | 2010
Zoe Aitken; Valerie McCormack; Ralph Highnam; Lisa Martin; Anoma Gunasekara; Olga Melnichouk; Gord Mawdsley; Chris Peressotti; Martin J. Yaffe; Norman F. Boyd; Isabel dos Santos Silva
Background: Mammographic density is a strong risk factor for breast cancer, usually measured by an area-based threshold method that dichotomizes the breast area on a mammogram into dense and nondense regions. Volumetric methods of breast density measurement, such as the fully automated standard mammogram form (SMF) method that estimates the volume of dense and total breast tissue, may provide a more accurate density measurement and improve risk prediction. Methods: In 2000-2003, a case-control study was conducted of 367 newly confirmed breast cancer cases and 661 age-matched breast cancer-free controls who underwent screen-film mammography at several centers in Toronto, Canada. Conditional logistic regression was used to estimate odds ratios of breast cancer associated with categories of mammographic density, measured with both the threshold and the SMF (version 2.2β) methods, adjusting for breast cancer risk factors. Results: Median percent density was higher in cases than in controls for the threshold method (31% versus 27%) but not for the SMF method. Higher correlations were observed between SMF and threshold measurements for breast volume/area (Spearman correlation coefficient = 0.95) than for percent density (0.68) or for absolute density (0.36). After adjustment for breast cancer risk factors, odds ratios of breast cancer in the highest compared with the lowest quintile of percent density were 2.19 (95% confidence interval, 1.28-3.72; Pt <0.01) for the threshold method and 1.27 (95% confidence interval, 0.79-2.04; Pt = 0.32) for the SMF method. Conclusion: Threshold percent density is a stronger predictor of breast cancer risk than the SMF version 2.2β method in digitized images. Cancer Epidemiol Biomarkers Prev; 19(2); 418–28
Medical Physics | 2008
Brian Keller; Chris Peressotti; Jean-Philippe Pignol
By providing superior localization and immobilization, stereotactic radiosurgery (SRS) is capable of delivering millimeter spheres of dose to intracranial targets with submillimeter precision. Several authors have proposed new SRS solutions to dramatically reduce beam penumbra to hundreds of microns. These solutions require new quality assurance methods capable of penumbra measurement at the micron scale. This article examines the capability of a digital microscope, with translation stage and associated software, to resolve dose gradients in Gafchromic EBT film at this level. To produce very steep penumbra, films were irradiated in phantom beneath pinhole collimators using lower energy x rays (100 kVp, 300 kVp, and Iridium-192) and minimal geometric penumbra contribution. For film analysis, a method was developed which improved the signal to noise ratio by finding the center of the irradiation spot, generating several radial dose profiles and averaging these to obtain the final off-axis dose profile. Optical density was converted to dose using a calibration curve. The experimentally determined off-axis dose profiles were compared with MCNP Monte Carlo simulations which replicated the irradiation geometry and served to validate our measured data. The measured 80%-20% penumbral widths were 46 microm +/- 26 microm (100 kVp, 2 mm field size), 69 microm +/- m 27 microm (300 kVp, 2 mm field size), and 241 microm +/-31 microm (Ir-192, 1 mm field size). These penumbral widths agreed with Monte Carlo simulations within experimental uncertainty. Our findings suggest that reading Gafchromic EBT films using a digital microscope with translation stage is suitable for the quality assurance of very sharp penumbra able to resolve gradients to within at least 30 microm.
Histopathology | 2011
Gina M. Clarke; Chris Peressotti; Claire Holloway; Judit T. Zubovits; Kela Liu; Martin J. Yaffe
Clarke G M, Peressotti C, Holloway C M B, Zubovits J T, Liu K & Yaffe M J (2011) Histopathology59, 116–128
Medical Physics | 2008
Brian Keller; Chris Peressotti; J‐P Pignol
Using superior localization and immobilization methods, stereotactic radiosurgery is capable of delivering spheres of dose as small as a few millimetres in diameter to intracranial targets. For targets abutting critical structures, the most conformal treatments minimize adverse radiation side effects and it is important, therefore, to ensure proper quality assurance prior to delivering high doses of radiation to eloquent brain locations in a single fraction. This work examines the capability of a digital microscope, with translation stage and associated software, to resolve dose gradients in Gafchromic EBT™ film at the micron level. In order to validate the microscope-film system from a radiation physics approach, films were irradiated to produce very steep penumbrae by using very small fields, lower photon energies and minimal geometric penumbra contribution. Orthovoltage film irradiations were done by placing films in phantom beneath pinhole collimators. The experimentally determined off-axis dose profiles were compared with Monte Carlo computer simulations which replicated the irradiation geometry and served to validate our measured data. The measured 80% - 20% penumbral widths were 46 μm ± 26 μm (100 kVp, 2 mm field size) and 69 μm ± 27 μm (300 kVp, 2 mm field size). In the energy range covered, the measured penumbral widths agreed with Monte Carlo computer simulations within experimental uncertainty. The effects of noise originating from both the film and the microscope system are discussed and improvements to this system suggested.
Medical Physics | 2009
Martin J. Yaffe; John M. Boone; Nathan J. Packard; Olivier Alonzo-Proulx; Shih Ying Huang; Chris Peressotti; Adil Al-Mayah; Kristy K. Brock
Medical Physics | 2009
Gordon E. Mawdsley; Albert H. Tyson; Chris Peressotti; Roberta A. Jong; Martin J. Yaffe
Current Oncology | 2008
Max R. Dahele; David M. Hwang; Chris Peressotti; Laibao Sun; Maggie Kusano; Shaista Okhai; Gail Darling; Martin J. Yaffe; Curtis Caldwell; Katherine Mah; Jennifer Hornby; L. Ehrlich; Simon Raphael; Ming-Sound Tsao; Abdollah Behzadi; Corey Weigensberg; Yee Ung
Physics in Medicine and Biology | 2006
Gina M. Clarke; Chris Peressotti; Gordon E. Mawdsley; Martin J. Yaffe
Computerized Medical Imaging and Graphics | 2011
Gina M. Clarke; Chris Peressotti; Paul Constantinou; Danoush Hosseinzadeh; Anne L. Martel; Martin J. Yaffe