Literature DB >> 26937708

Assessment of Functional Differences in Malignant and Benign Breast Lesions and Improvement of Diagnostic Accuracy by Using US-guided Diffuse Optical Tomography in Conjunction with Conventional US.

Quing Zhu1, Andrew Ricci1, Poornima Hegde1, Mark Kane1, Edward Cronin1, Alex Merkulov1, Yan Xu1, Behnoosh Tavakoli1, Susan Tannenbaum1.   

Abstract

Purpose To investigate ultrasonography (US)-guided diffuse optical tomography to distinguish the functional differences of hemoglobin concentrations in a wide range of malignant and benign breast lesions and to improve breast cancer diagnosis in conjunction with conventional US. Materials and Methods The study protocol was approved by the institutional review boards and was HIPAA compliant. Written informed consent was obtained from all patients. Patients (288 women; mean age, 50 years; range, 17-94 years) who underwent US-guided biopsy were imaged with a handheld US and optical probe. The US-imaged lesion was used to guide reconstruction of light absorption maps at four wavelengths, and total hemoglobin (tHb), oxygenated hemoglobin (oxyHb), and deoxygenated hemoglobin (deoxyHb) were computed from the absorption maps. A threshold (80 μmol/L) was chosen on the basis of this study population. Two radiologists retrospectively evaluated US images on the basis of the US Breast Imaging Reporting and Data System lexicon, and a lesion was considered malignant when a score of 4C or 5 was given or a lesion had tHb greater than 80 μmol/L. A two-sample t test was used to calculate significance between groups, and Spearman ρ was computed between hemoglobin parameters and tumor pathologic grades. Results Three tumors were Tis, 37 were T1, 19 were T2-T4 carcinomas, and 233 were benign lesions. The mean maximum tHb, oxyHb, and deoxyHb of Tis-T1 and T2-T4 groups were 89.3 μmol/L ± 20.2 (standard deviation), 65.0 μmol/L ± 20.8, and 33.5 μmol/L ± 11.3, respectively, and 84.7 μmol/L ± 32.8, 57.1 μmol/L ± 19.8, and 34.7 μmol/L ± 18.9, respectively. The corresponding values of benign lesions were 54.1 μmol/L ± 23.5, 38.0 μmol/L ± 17.4, and 25.2 μmol/L ± 13.8, respectively. The mean maximum tHb, oxyHb, and deoxyHb were significantly higher in the malignant groups than the benign group (P <.001, <.001, and .041, respectively). For malignant lesions, the mean maximum tHb moderately correlated with tumor histologic grade and nuclear grade (ρ = 0.283 and 0.315, respectively). The mean maximum oxyHb moderately correlated with tumor nuclear grade (ρ = 0.267). When radiologists' US diagnosis and the tHb were used together, the sensitivity, specificity, positive predictive value, and negative predictive value were 96.6%-100%, 77.3%-83.3%, 52.7%-59.4%, and 99.0%-100%, respectively, for the combined malignant group. Conclusion The tHb and oxyHb correlate with breast cancer pathologic grade and can be used as an adjunct to US to improve sensitivity and negative predictive value in breast cancer diagnosis. (©) RSNA, 2016 Online supplemental material is available for this article.

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Year:  2016        PMID: 26937708      PMCID: PMC4976463          DOI: 10.1148/radiol.2016151097

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  34 in total

1.  Characterization of female breast lesions from multi-wavelength time-resolved optical mammography.

Authors:  Lorenzo Spinelli; Alessandro Torricelli; Antonio Pifferi; Paola Taroni; Gianmaria Danesini; Rinaldo Cubeddu
Journal:  Phys Med Biol       Date:  2005-05-18       Impact factor: 3.609

2.  Dynamic optical breast imaging: a new technique to visualise breast vessels: comparison with breast MRI and preliminary results.

Authors:  Alexandra Athanasiou; Daniel Vanel; Corinne Balleyguier; Laure Fournier; Marie Christine Mathieu; Suzette Delaloge; Clarisse Dromain
Journal:  Eur J Radiol       Date:  2005-04       Impact factor: 3.528

3.  Imaging breast adipose and fibroglandular tissue molecular signatures by using hybrid MRI-guided near-infrared spectral tomography.

Authors:  Ben Brooksby; Brian W Pogue; Shudong Jiang; Hamid Dehghani; Subhadra Srinivasan; Christine Kogel; Tor D Tosteson; John Weaver; Steven P Poplack; Keith D Paulsen
Journal:  Proc Natl Acad Sci U S A       Date:  2006-05-26       Impact factor: 11.205

Review 4.  Benign breast diseases: classification, diagnosis, and management.

Authors:  Merih Guray; Aysegul A Sahin
Journal:  Oncologist       Date:  2006-05

5.  Sensitivity of MRI-guided near-infrared spectroscopy clinical breast exam data and its impact on diagnostic performance.

Authors:  Michael A Mastanduno; Junqing Xu; Fadi El-Ghussein; Shudong Jiang; Hong Yin; Yan Zhao; Kelly E Michaelsen; Ke Wang; Fang Ren; Brian W Pogue; Keith D Paulsen
Journal:  Biomed Opt Express       Date:  2014-08-22       Impact factor: 3.732

6.  Early-stage invasive breast cancers: potential role of optical tomography with US localization in assisting diagnosis.

Authors:  Quing Zhu; Poornima U Hegde; Andrew Ricci; Mark Kane; Edward B Cronin; Yasaman Ardeshirpour; Chen Xu; Andres Aguirre; Scott H Kurtzman; Peter J Deckers; Susan H Tannenbaum
Journal:  Radiology       Date:  2010-06-22       Impact factor: 11.105

7.  Solid breast lesions: clinical experience with US-guided diffuse optical tomography combined with conventional US.

Authors:  Wenxiang Zhi; Xingang Gu; Jianmin Qin; Peihao Yin; Xia Sheng; Sizhi Paul Gao; Qi Li
Journal:  Radiology       Date:  2012-09-25       Impact factor: 11.105

8.  Time-domain optical mammography SoftScan: initial results.

Authors:  Xavier Intes
Journal:  Acad Radiol       Date:  2005-08       Impact factor: 3.173

9.  US-guided optical tomography: correlation with clinicopathologic variables in breast cancer.

Authors:  Ji Soo Choi; Min Jung Kim; Ji Hyun Youk; Hee Jung Moon; Hee Jung Suh; Eun-Kyung Kim
Journal:  Ultrasound Med Biol       Date:  2012-12-04       Impact factor: 2.998

Review 10.  Breast ultrasonography: state of the art.

Authors:  Regina J Hooley; Leslie M Scoutt; Liane E Philpotts
Journal:  Radiology       Date:  2013-09       Impact factor: 11.105

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  22 in total

1.  Improving breast cancer diagnosis by reducing chest wall effect in diffuse optical tomography.

Authors:  Feifei Zhou; Atahar Mostafa; Quing Zhu
Journal:  J Biomed Opt       Date:  2017-03-01       Impact factor: 3.170

2.  Multimodal breast cancer imaging using coregistered dynamic diffuse optical tomography and digital breast tomosynthesis.

Authors:  Bernhard B Zimmermann; Bin Deng; Bhawana Singh; Mark Martino; Juliette Selb; Qianqian Fang; Amir Y Sajjadi; Jayne Cormier; Richard H Moore; Daniel B Kopans; David A Boas; Mansi A Saksena; Stefan A Carp
Journal:  J Biomed Opt       Date:  2017-04-01       Impact factor: 3.170

3.  Diffuse optical tomography reconstruction method using ultrasound images as prior for regularization matrix.

Authors:  Murad Althobaiti; Hamed Vavadi; Quing Zhu
Journal:  J Biomed Opt       Date:  2017-02-01       Impact factor: 3.170

Review 4.  A review of optical breast imaging: Multi-modality systems for breast cancer diagnosis.

Authors:  Quing Zhu; Steven Poplack
Journal:  Eur J Radiol       Date:  2020-05-18       Impact factor: 3.528

5.  Two step imaging reconstruction using truncated pseudoinverse as a preliminary estimate in ultrasound guided diffuse optical tomography.

Authors:  K M Shihab Uddin; Atahar Mostafa; Mark Anastasio; Quing Zhu
Journal:  Biomed Opt Express       Date:  2017-11-08       Impact factor: 3.732

6.  Diffuse optical tomography using semiautomated coregistered ultrasound measurements.

Authors:  Atahar Mostafa; Hamed Vavadi; K M Shihab Uddin; Quing Zhu
Journal:  J Biomed Opt       Date:  2017-12       Impact factor: 3.170

7.  Optimal breast cancer diagnostic strategy using combined ultrasound and diffuse optical tomography.

Authors:  K M Shihab Uddin; Menghao Zhang; Mark Anastasio; Quing Zhu
Journal:  Biomed Opt Express       Date:  2020-04-24       Impact factor: 3.732

8.  Automated data selection method to improve robustness of diffuse optical tomography for breast cancer imaging.

Authors:  Hamed Vavadi; Quing Zhu
Journal:  Biomed Opt Express       Date:  2016-09-14       Impact factor: 3.732

9.  Compact ultrasound-guided diffuse optical tomography system for breast cancer imaging.

Authors:  Hamed Vavadi; Atahar Mostafa; Feifei Zhou; K M Shihab Uddin; Murad Althobaiti; Chen Xu; Rajeev Bansal; Foluso Ademuyiwa; Steven Poplack; Quing Zhu
Journal:  J Biomed Opt       Date:  2018-10       Impact factor: 3.170

10.  Weighting function effects in a direct regularization method for image-guided near-infrared spectral tomography of breast cancer.

Authors:  Jinchao Feng; Shudong Jiang; Brian W Pogue; Keith Paulsen
Journal:  Biomed Opt Express       Date:  2018-06-25       Impact factor: 3.732

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