student profile: Ms Christine Damases

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Thesis work

Thesis title: Causal Factors and Potential Clinical Implications of Variation in Mammographic Density Assessment

Supervisors: Mark MCENTEE , Patrick BRENNAN , Claudia MELLO-THOMS

Thesis abstract:

The thesis explores various measures of MBD assessment in digital mammography (DM) and assesses inter-�?reader variability using BI-�?RADS® and RANZCR scales based on four studies. Methods: In studies 1 and 2, 40 images from 20 US women—acquired one year apart—were processed using Volpara®densityTM software. Observers (20 experts) assessed the images using BI-�?RADS®. Study 1 used spearman’s correlation (ρ) to examine relationships between the systems for BI-�?RADS®, VDG, and AvBD%. Study 2 examined inter-�?observer agreement using BI-�?RADS® 4-�?point and binary scales. In study 3, 26 Australian radiologists assessed 40 images using RANZCR synoptic scales. Agreement on RANZCR scales between radiologists was expressed as Cohen’s Kappa (κ). Study 4 used a weighted Kappa (κw) statistic to test for agreement between MBD assessment schemes and pairs of observers based on BI-�?RADS® scores from 20 ABR examiners, 24 UK practitioners, and RANZCR radiologists. Results: In study 1, both BI-�?RADS® (ρ=0.904; p<0.001) and Volpara (ρ=0.978; p<0.001) showed positive correlations between the systems. Study 2 reported BI-�?RADS® inter-�?reader agreement of 0.565 [95% CI=0.519–0.610] on the 4-�?point scale and 0.855 [95% CI=0.824–0.866] on the binary scale. Study 3 reported RANZCR inter-�? reader agreement of 0.360 [95% CI=0.308–0.412] on the 4-�?point scale and 0.726 (95% CI=0.675–0.777) on the 2-�?point scale. Study 4 reported agreement (κw) of 0.10 [95% CI=-�? 1.13–0.43] between ABR and RANZCR radiologists, 0.25[95% CI=-�?0.42–0.61] between ABR and UK practitioners, and 0.95 [95% CI=0.91–0.97] between RANZCR radiologists and UK practitioners. Conclusion: Results show lesser variation on binary scale than on 4-�?point scale for both BI-�?RADS® and RANZCR. Volpara®densityTM MBD measurement shows better agreement between the imaging systems than BI-�?RADS®. This work provides insight into potential implications of inconsistency in MBD assessment on breast cancer risk stratification.

Selected publications

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Journals

  • Damases, C., Mello-Thoms, C., McEntee, M. (2016). Inter-observer variability in mammographic density assessment using Royal Australian and New Zealand College of Radiologists (RANZCR) synoptic scales. Journal of Medical Imaging and Radiation Oncology, 60(3), 329-336. [More Information]
  • Damases, C., Brennan, P., Mello-Thoms, C., McEntee, M. (2016). Mammographic Breast Density Assessment Using Automated Volumetric Software and Breast Imaging Reporting and Data System (BIRADS) Categorization by Expert Radiologists. Academic Radiology, 23(1), 70-77. [More Information]
  • Damases, C., Brennan, P., McEntee, M. (2015). Mammographic density measurements are not affected by mammography system. Journal of Medical Imaging, 2(1), 1-5. [More Information]

Conferences

  • Damases, C., Mello-Thoms, C., McEntee, M. (2016). Inter-observer variability within BI-RADS and RANZCR mammographic density assessment schemes. SPIE Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, USA: SPIE Publications. [More Information]
  • Damases, C., Brennan, P., McEntee, M. (2015). The impact of mammographic imaging systems on density measurement. SPIE Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment, Washington USA: SPIE Publications. [More Information]
  • McEntee, M., Damases, C. (2014). Mammographic density measurement: a comparison of automated volumetric density measurement to BIRADS. SPIE Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, Bellingham, Washington, USA: SPIE Publications. [More Information]

2016

  • Damases, C., Mello-Thoms, C., McEntee, M. (2016). Inter-observer variability in mammographic density assessment using Royal Australian and New Zealand College of Radiologists (RANZCR) synoptic scales. Journal of Medical Imaging and Radiation Oncology, 60(3), 329-336. [More Information]
  • Damases, C., Mello-Thoms, C., McEntee, M. (2016). Inter-observer variability within BI-RADS and RANZCR mammographic density assessment schemes. SPIE Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, USA: SPIE Publications. [More Information]
  • Damases, C., Brennan, P., Mello-Thoms, C., McEntee, M. (2016). Mammographic Breast Density Assessment Using Automated Volumetric Software and Breast Imaging Reporting and Data System (BIRADS) Categorization by Expert Radiologists. Academic Radiology, 23(1), 70-77. [More Information]

2015

  • Damases, C., Brennan, P., McEntee, M. (2015). Mammographic density measurements are not affected by mammography system. Journal of Medical Imaging, 2(1), 1-5. [More Information]
  • Damases, C., Brennan, P., McEntee, M. (2015). The impact of mammographic imaging systems on density measurement. SPIE Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment, Washington USA: SPIE Publications. [More Information]

2014

  • McEntee, M., Damases, C. (2014). Mammographic density measurement: a comparison of automated volumetric density measurement to BIRADS. SPIE Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, Bellingham, Washington, USA: SPIE Publications. [More Information]

Note: This profile is for a student at the University of Sydney. Views presented here are not necessarily those of the University.