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Quantification of Tc-99m sestamibi distribution in normal breast tissue using dedicated breast SPECT-CT

Publication ,  Journal Article
Mann, SD; Perez, KL; McCracken, EKE; Shah, JP; Choudhury, KR; Wong, TZ; Tornai, MP
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
August 15, 2012

The use of Tc-99m-Sestamibi in molecular breast imaging is common due to its preferential uptake in malignant tissue. However, quantification of the baseline uptake in normal, healthy breast tissue is not possible using planar-imaging devices. Using our dedicated breast SPECT-CT system, an IRB approved pilot study is underway to quantify mean activity in normal breast tissue, and to differentiate uptake between adipose and glandular tissues. A cohort of patients at normal breast cancer risk undergoing another diagnostic Sestamibi study was imaged using the breast SPECT-CT system. SPECT images were corrected and quantitatively reconstructed using previously developed methods, and registered with the CT images. The CT images were segmented, and the average activity concentration was measured for glandular, adipose, and total breast tissue. Results indicate no preferential uptake between tissues and low average uptake, which may be used to determine a universal threshold for cancer detection. © 2012 Springer-Verlag Berlin Heidelberg.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

August 15, 2012

Volume

7361 LNCS

Start / End Page

402 / 409

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Mann, S. D., Perez, K. L., McCracken, E. K. E., Shah, J. P., Choudhury, K. R., Wong, T. Z., & Tornai, M. P. (2012). Quantification of Tc-99m sestamibi distribution in normal breast tissue using dedicated breast SPECT-CT. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7361 LNCS, 402–409. https://doi.org/10.1007/978-3-642-31271-7_52
Mann, S. D., K. L. Perez, E. K. E. McCracken, J. P. Shah, K. R. Choudhury, T. Z. Wong, and M. P. Tornai. “Quantification of Tc-99m sestamibi distribution in normal breast tissue using dedicated breast SPECT-CT.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7361 LNCS (August 15, 2012): 402–9. https://doi.org/10.1007/978-3-642-31271-7_52.
Mann SD, Perez KL, McCracken EKE, Shah JP, Choudhury KR, Wong TZ, et al. Quantification of Tc-99m sestamibi distribution in normal breast tissue using dedicated breast SPECT-CT. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012 Aug 15;7361 LNCS:402–9.
Mann, S. D., et al. “Quantification of Tc-99m sestamibi distribution in normal breast tissue using dedicated breast SPECT-CT.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7361 LNCS, Aug. 2012, pp. 402–09. Scopus, doi:10.1007/978-3-642-31271-7_52.
Mann SD, Perez KL, McCracken EKE, Shah JP, Choudhury KR, Wong TZ, Tornai MP. Quantification of Tc-99m sestamibi distribution in normal breast tissue using dedicated breast SPECT-CT. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012 Aug 15;7361 LNCS:402–409.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

August 15, 2012

Volume

7361 LNCS

Start / End Page

402 / 409

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences