Rationale and Objectives
We sought to investigate the utility of phase-contrast diffuse optical tomography (PCDOT) for differentiation of malignant and benign breast masses in humans and to compare PCDOT with conventional diffuse optical tomography (DOT) for analysis of breast masses in humans.
Materials and Methods
Thirty-five breast masses were imaged in 33 patients (mean age, 51 years; range, 22–80) using PCDOT. Images characterizing the tissue refractive index, and absorption and scattering coefficients of breast masses were obtained with a finite element-based reconstruction algorithm. Theses images were then analyzed and compared with the biopsy/pathology results for all the cases examined.
Results
Malignant lesions tended to have a decreased refractive index, allowing them to be discriminated from benign lesions in most cases, whereas absorption and scattering images were unable to accurately discriminate benign from malignant lesions. The sensitivity, specificity, false-positive value, and overall accuracy for refractive index imaging were 81.8%, 70.8%, 29.2%, and 74.3%, respectively. The accuracy of refractive index imaging increases with increasing patient age.
Conclusion
Refractive index is a new parameter for optical imaging that may be helpful in differentiating between malignant and benign masses in the breast.
The low specificity of x-ray mammography, the current clinical tool for breast imaging, suggests that many women without cancer will receive recommendations to undergo a breast biopsy (ie, false-positive examinations). This results in four or five benign breast biopsy results for every one malignancy that is detected ( ). In addition, mammography has an unacceptable false-negative rate for patients with radiodense breast tissues ( ). For example, the sensitivity of screening mammography decreases from a high of 88% in the predominantly fatty breast to 62% in the dense breast ( ). Thus, there is a critical need to develop new technologies that can improve the sensitivity and specificity of mammography. Several other conventional techniques are currently under investigation for breast cancer detection, including ultrasound (US), magnetic resonance imaging (MRI), and computed tomography (CT) ( ). Among these conventional alternatives or supplements, MRI is the most widely studied and potentially promising solution to dense breast imaging. A recent MRI study of 821 women showed a sensitivity of 88% and corresponding specificity of 68% regardless of breast density ( ). Similar high sensitivities of MRI for breast cancer have also been found in other studies involving targeted imaging of high-risk populations ( ). Although MRI appears to offer high sensitivity in the dense breast, its specificity has been far more modest. In addition, MRI is costly ( ) and not suitable for breast screening.
Near-infrared (NIR) light–based diffuse optical tomography (DOT) is emerging as a nonconventional alternative for breast cancer detection. The ability of DOT techniques to noninvasively image and analyze both tissue structure and function, as well as the advantages of low cost and portability, has great potential to make DOT an ideal candidate for routine breast screening. Although DOT has been shown to have high sensitivity for breast tumor detection, its specificity is limited ( ). Detection of tumors by DOT is so far primarily based on tissue absorption and scattering parameters or absorption-derived functional parameters. However, these imaging parameters available from the current DOT do not appear to be able to fully characterize breast tissue, which results in limited sensitivity and specificity.
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Materials and methods
Patient Examinations
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Table 1
Characteristics of Malignant Lesions: Pathology, Mammography, and Phase-contrast Diffuse Optical Tomography
Biopsy Findings Lesion Size † (cm) BIRADS Score ⁎ The Difference of RI Between Lesion and Normal Tissue 2 3 4 5 Δ n < 0 Δ n > 0 Lobular carcinoma ( n = 3) 0.5, 1.0, 2.0 1 1 3 0 Infiltrating ductal carcinoma ( n = 6) 5, 2, 2, 10, 1.9 3 1 4 2 Extensive intraductal breast carcinoma ( n = 1) 2.5 1 1 0 Invasive carcinoma with mixed ductal and lobular features ( n = 1) 0.8 1 1 0
BIRADS, Breast Imaging Reporting and Data System; RI, refractive index.
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Table 2
Characteristics of Benign Lesions as Determined at Biopsy, Mammography, and Phase-contrast Diffuse Optical Tomography
Imaging Findings Pathology Findings Lesion Size † (cm) BIRADS Score ⁎ The difference of RI Between Lesion and Normal Tissue 1 2 3 4 Δ n < 0 Δ n > 0 Mass Adipose tissue with focal fibrosis ( n = 1) N/A 0 1 Mass or lump ( n = 4) 1.3, 2 2 1 3 Cysts ( n = 6) 1.6, 0.3, 0.8 2 1 1 5 Lymph node ( n = 1) 2.1 1 0 1 Fibroadenomas ( n = 2) 2, 3 1 1 2 0 Infarcted intraductal papilloma ( n = 1) 1 1 0 1 Asymmetric density Fibrocystic mastophy ( n = 1) 2.3 1 0 1 Fibroadipose tissue ( n = 5) 1.8, 0.8 2 3 1 4 Fibroadenomatoid change and microcalcifications ( n = 1) N/A 1 0 Calcifications Microcalcification, atypical ductal hyperplasia present ( n = 1) N/A 1 1 0 Benign calcification ( n = 1) 0.3 1 0 1
BIRADS, Breast Imaging Reporting and Data System; RI, refractive index.
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Image Reconstruction Methods
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∇⋅D∇Φ(r)+2Dn∇n⋅∇Φ(r)−μaΦ(r)=−S0δ(r−r0) ∇
⋅
D
∇
Φ
(
r
)
+
2
D
n
∇
n
⋅
∇
Φ
(
r
)
−
μ
a
Φ
(
r
)
=
−
S
0
δ
(
r
−
r
0
)
where Φ is the photon density; n is the refractive index; D and μ a are the diffusion and absorption coefficients, respectively; and S 0 is the source strength. For PCDOT, the reconstruction algorithm is similar to that of conventional DOT ( ); that is, we use a regularized Newton’s method to update an initial RI distribution iteratively to minimize an object function composed of a weighted sum of the squared difference between computed and measured optical data at the surface of the medium. The computed optical data (i.e., photon density) are obtained by solving Equation 1 with the finite element method. Tissue absorption and diffusion or scattering coefficients were reconstructed separately with conventional DOT. The algorithm has been successfully tested using extensive tissue-mimicking phantom measurements with different contrasts of RI between the target and background ( ).
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Statistical Analysis
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Results
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Table 3
Differentiation of Benign from Malignant Tumors Based on Refractive Index Images
True Positives True Negatives False Positives False Negatives Sensitivity Specificity FPR Overall Accuracy 9 17 7 2 81.8% 70.8% 29.2% 74.3%
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Table 4
Accuracy of Phase-contrast Diffuse Optical Tomography According to Tumor Size, Age, or Size of Breast (Imaging Plane)
No. of Cases True False Accuracy Lesion size (cm) >1 20 15 5 0.75 (15/20) <1 10 8 2 0.8 (8/10) Unknown 5 3 2 0.6 (3/5) Age (yr) <40 7 4 3 0.5714 (4/7) 41–49 8 5 3 0.625 (5/8) 50–59 10 8 2 0.8 (8/10) >60 10 9 1 0.9 (9/10) Size of breast (radius of image plane) (mm) <40 17 12 5 0.7059 (12/17) 40.5–59 12 10 2 0.8333 (10/12) >59.5 6 4 2 0.6667 (4/6)
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Discussion
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Conclusions
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