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SRI Profiles

Ali Sadeghi-Naini
Ali Sadeghi-Naini, PhD

Scientist

Sunnybrook Health Sciences Centre
2075 Bayview Ave., Room M6 605
Toronto, ON
M4N 3M5

Phone: 416-480-6100, ext. 1018
Fax: 416-480-6002

Administrative Assistant: Lorelie Lacson
Phone: 416-480-4619
Email: lorelie.lacson@sunnybrook.ca

Education:

  • M.Sc., 2006, artificial intelligence, Tehran Polytechnic University, Iran
  • PhD, 2011, biomedical engineering, Western University, Canada
  • Postdoctoral fellowship, 2015, medical biophysics and radiation oncology, University of Toronto, Canada

Appointments and Affiliations:

Research Foci:

  • Image-guided personalized cancer therapeutics
  • Quantitative multimodal cancer imaging
  • Modelling intra-tumour heterogeneity
  • Computer-aided minimally-invasive cancer interventions

Research Summary:

The focus of Dr. Sadeghi-Naini's research is on developing computer-aided image-guided technologies to improve personalized cancer therapeutics. In particular, he is interested in developing integrated imaging and computational frameworks to detect and characterize cancer, to facilitate cancer-targeting interventions and to evaluate response to treatment.

In this context, he is investigating novel methods of multimodal cancer imaging to explore different stages during cancer development and decay from various structural and functional perspectives.

Specifically, he is developing integrated frameworks to adapt complementary aspects of quantitative ultrasound imaging, optical spectroscopy, elastography, computed tomography and MRI to characterize a tumour in terms of its micro-structure, physiology, perfusion, metabolism and biomechanical properties. Further, he is investigating alterations in such tumour characteristics to develop sensitive biomarkers of cancer response to treatment.

Dr. Sadeghi-Naini is also transforming multimodal imaging within computational frameworks to facilitate the planning and navigation of interventional procedures such as biopsy, brachytherapy and radiation therapy.

A particular interest is in developing ad hoc models for quantification of spatial heterogeneity in cancer imaging. Alterations within a tumour during its formation or degeneration are frequently inhomogeneous. Therefore, quantifying intra-tumour heterogeneity can provide further insights into tumour characteristics or rapidly flag a change in tumour state within its life cycle. To quantify intra-tumour heterogeneity noninvasively, Dr. Sadeghi-Naini is developing novel image-processing techniques to model and analyze the texture within tumour images. He is adapting machine learning techniques to determine how to correspond these textural features to specific tumour characteristics, or to a change that indicates tumour response to treatment.

Selected Publications:

See current publications list at PubMed.

  1. Sadeghi-Naini A, Vorauer E, Chin L, Falou O, Tran WT, Wright FC, Gandhi S, Yaffe MJ, Czarnota GJ. Early detection of chemotherapy-refractory patients by monitoring textural alterations in diffuse optical spectroscopic images. Med Phys. 2015;42(11):6130–6146.
  2. Sadeghi-Naini A, Sofroni E, Papanicolau N, Falou O, Sugar L, Morton G, Yaffe M, Nam R, Sadeghian A, Kolios MC, Chung HT, Czarnota GJ. Quantitative ultrasound spectroscopic imaging for characterization of disease extent in prostate cancer patients. Transl Oncol. 2015;8(1):25–34.
  3. Sadeghi-Naini A, Papanicolau N, Falou O, Zubovits J, Dent R, Verma S, Trudeau ME, Boileau JF, Spayne J, Iradji S, Sofroni E, Lee J, Lemon-Wong S, Yaffe MJ, Kolios MC, Czarnota GJ. Quantitative ultrasound evaluation of tumour cell death response in locally advanced breast cancer patients receiving chemotherapy. Clin Cancer Res. 2013;19(8):2163–2174.
  4. Sadeghi-Naini A, Falou O, Tadayyon H, Al-Mahrouki A, Tran WT, Papanicolau N, Kolios MC, Czarnota GJ. Conventional-frequency ultrasonic biomarkers of cancer treatment response in vivo. Transl Oncol. 2013;6(3):234–243.
  5. Sadeghi-Naini A, Patel RV, Samani A. Measurement of lung hyperelastic properties using inverse finite element approach. IEEE Trans Biomed Eng. 2011; 58(10):2852–2859.

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