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Non-invasive breast tumour grading using ultrasound frequency-dependent backscatter analysis

Non-invasive breast tumour grading using ultrasound frequency-dependent backscatter analysis. Hadi Tadayyon June 11, 2012. Locally advanced breast cancer (LABC). Clinical challenge High risk for metastasis Characterized as: > 5 cm long axis Skin/chest wall involvement

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Non-invasive breast tumour grading using ultrasound frequency-dependent backscatter analysis

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  1. Non-invasive breast tumour grading using ultrasound frequency-dependent backscatter analysis HadiTadayyon June 11, 2012

  2. Locally advanced breast cancer (LABC) • Clinical challenge • High risk for metastasis • Characterized as: • > 5 cm long axis • Skin/chest wall involvement • Lymph node involvement • Tumour grade – a histological feature that is a prognostic indicator and is important for treatment design • Determined from pathological examination of biopsy sample • Higher grade  higher degree of malignancy / poorer prognosis • Our goal: ultrasonically detect variation in tumour grades

  3. Quantitative ultrasound characterization of cancers • Midband fit, slope, and intercept used to differentiate: • Prostate cancer from benign tumours1 • Metastic from non-metastatic lymph nodes2 • Acoustic scatterer spacing used to characterize breast lesions as benign or malignant3 Feleppa et al., 2004 IEEE Trans UFFC, 43(4), 609-619, (1996) Mamou et al., Ultrasound in Med. & Biol., 37(3), 345–357, (2011) Y. Bige et al., Ultrasonics 44 , 211–215, (2006)

  4. Research Question • Can LABC tumours be characterized in terms of grade using quantitative ultrasound? • Given: • Retrospective in-vivo clinical breast data (N=43) • A diagnostic ultrasound machine

  5. Methods: data collection and classification • 10 MHz fc linear array transducer (Ultrasonix, Canada) • 4-7 cm depth • 5 MHz 50% bandwidth GI (N=3) Tumour ROI QUS Midband fit (MBF) Slope (SS) Intercept (SI) Scatterer spacing (SAS) GII (N = 22) Normal tissue ROI Normal breast ROI GIII (N = 18) 1 cm

  6. Methods: Spectral analysis • Discrete depth spectral normalization (reference reflector) • Auto-regressive (AR) spectral estimation and autocorrelation-derived scatterer spacing • Depth-dependent spectral normalization (reference phantom) • Variable bandwidth linear regression

  7. Results: QUS distributions among tumour grades Mann-Whitney test: p = 0.032

  8. Results: parametric images of scatterer spacing GIII GII GI NT 1 cm 0.5 SAS (mm) 0 10 um

  9. The link of scatterer spacing to biology Mean spacing between glandular islands = 200 um 100 um

  10. Discussion & conclusion • A potential method to non-invasively characterize tumour grade was proposed • Scatterer spacing statistically different among tumour grades (ANOVA test & Mann-Whitney test) • Scatterer spacing is linked to spacing between glandular islands • Small sample size for GI • In large population study – 362/1409 = 25% • In our study, 3/43 = 7% • Cannot evaluate classification due to insufficient parameters • Future directions: investigate other QUS parameters

  11. Acknowledgments CzarnotaLab, University of Toronto • Dr. Czarnota • Dr. Omar Falou • Mike Papanicolau • Sara Iradji • ErvisSofroni CGSD Ryerson University • Dr. Lauren Wirtzfeld University of Illinois • Dr. Michael Oelze

  12. Tumour grade Grade I Grade II Grade III Total score 3-5 6-7 Increasing risk of metastasis 8-9

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