Postmortem validation of breast density using dual‐energy mammography

Molloi, Sabee; Ducote, Justin L.; Ding, Huanjun; Feig, Stephen A.

doi:10.1118/1.4890295

Cited by 14 publications

(25 citation statements)

References 78 publications

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“…The energy information basically addresses the limitations related to the uncertainty associated with segmentation of fibroglandular tissue purely based on image gray level. Previous phantom and postmortem breast studies have validated the accuracy of breast density measurement using dual energy and spectral mammography (28, 29, 34, 38). The results from dual-energy material decomposition measurements from right and left breasts in this study also showed that volume and breast density measurements were highly correlated.…”

Section: Discussionmentioning

confidence: 98%

“…A previously reported phantom study using spectral mammography has shown that accurate volumetric breast density measurements can be made using just a single exposure (34). Previous studies have also validated the accuracy of the dual energy mammography technique for breast density measurement using chemical analysis in postmortem breasts as the reference gold standard (29, 35). The postmortem breast studies have also shown excellent correlation of breast density between right and left breasts (29, 35).…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies have also validated the accuracy of the dual energy mammography technique for breast density measurement using chemical analysis in postmortem breasts as the reference gold standard (29, 35). The postmortem breast studies have also shown excellent correlation of breast density between right and left breasts (29, 35). The purpose of this retrospective study was to compare the precision of breast density measurement using reader assessment, histogram thresholding segmentation, fuzzy C-mean segmentation and dual-energy material decomposition.…”

Section: Introductionmentioning

confidence: 99%

“…It does not require any assumption for breast density measurement since glandular and adipose thickness measurements are based on two separate physical measurements using low and high energy image data. Previous studies have shown that accurate breast density measurements can be made using dual energy mammography (27–29). However, slightly higher radiation dose is required for dual energy mammography (27–29) and misregistration artifacts can result if the patient moves between acquisition of low and high energy images.…”

Section: Introductionmentioning

confidence: 99%

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Breast Density Evaluation Using Spectral Mammography, Radiologist Reader Assessment, and Segmentation Techniques

Molloi¹,

Ding²,

Feig³

2015

Academic Radiology

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Purpose The purpose of this study was to compare the precision of mammographic breast density measurement using radiologist reader assessment, histogram threshold segmentation, fuzzy C-mean segmentation and spectral material decomposition. Materials and Methods Spectral mammography images from a total of 92 consecutive asymptomatic women (50–69 years old) who presented for annual screening mammography were retrospectively analyzed for this study. Breast density was estimated using 10 radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm and spectral material decomposition. The breast density correlation between left and right breasts was used to assess the precision of these techniques to measure breast composition relative to dual-energy material decomposition. Results In comparison to the other techniques, the results of breast density measurements using dual-energy material decomposition showed the highest correlation. The relative standard error of estimate for breast density measurements from left and right breasts using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm and dual-energy material decomposition was calculated to be 1.95, 2.87, 2.07 and 1.00, respectively. Conclusion The results indicate that the precision of dual-energy material decomposition was approximately factor of two higher than the other techniques with regard to better correlation of breast density measurements from right and left breasts.

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Section: Discussionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Breast Density Evaluation Using Spectral Mammography, Radiologist Reader Assessment, and Segmentation Techniques

Molloi¹,

Ding²,

Feig³

2015

Academic Radiology

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“…Results based on computer simulation model, phantom and post-mortem breast studies seem promising; 26,27 although robustness and clinical utility have not been fully investigated.…”

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confidence: 99%

Volumetric breast density measurement: sensitivity analysis of a relative physics approach

Lau¹,

Ng²,

Aziz³

2016

BJR

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Gaussian noise was generated and introduced into the original images.Results: Errors in filter thickness, mAs, detector gain and offset had limited effects on FGV, BV and VBD. Significant effects in VBD were observed when CBT, kVp, detector offset and image noise were varied (p , 0.0001). Maximum shifts in the mean (1.2%) and median (1.1%) VBD of the study population occurred when CBT was varied. Conclusion: Volpara was robust to expected clinical variations, with errors in most investigated parameters giving limited changes in results, although extreme variations in CBT and kVp could lead to greater errors. Advances in knowledge: Despite Volpara's robustness, rigorous quality control is essential to keep the parameter errors within reasonable bounds. Volpara appears robust within those bounds, albeit for more advanced applications such as tracking density change over time, it remains to be seen how accurate the measures need to be.

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Quantitative contrast‐enhanced spectral mammography based on photon‐counting detectors: A feasibility study

Ding

Molloi

2017

Medical Physics

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Purpose To investigate the feasibility of accurate quantification of iodine mass thickness in contrast-enhanced spectral mammography. Materials and Methods A computer simulation model was developed to evaluate the performance of a photon-counting spectral mammography system in the application of contrast-enhanced spectral mammography. A figure-of-merit (FOM), which was defined as the decomposed iodine signal-to-noise ratio (SNR) with respect to the square root of the mean glandular dose (MGD), was chosen to optimize the imaging parameters, in terms of beam energy, splitting energy, and pre-filtrations for breasts of various thicknesses and densities. Experimental phantom studies were also performed using a beam energy of 40 kVp and a splitting energy of 34 keV with 3 mm Al pre-filtration. A two-step calibration method was investigated to quantify the iodine mass thickness, and was validated using phantoms composed of a mixture of glandular and adipose materials, for various breast thicknesses and densities. Finally, the traditional dual-energy log-weighted subtraction method was also studied as a comparison. The measured iodine signal from both methods was compared to the known value to characterize the quantification accuracy and precision. Results The optimal imaging parameters, which lead to the highest FOM, were found at a beam energy between 42 to 46 kVp with a splitting energy at 34 keV. The optimal tube voltage decreased as the breast thickness or the Al pre-filtration increased. The proposed quantification method was able to measure iodine mass thickness on phantoms of various thicknesses and densities with high accuracy. The root-mean-square (RMS) error for cm-scale lesion phantoms was estimated to be 0.20 mg/cm2. The precision of the technique, characterized by the standard deviation of the measurements, was estimated to be 0.18 mg/cm2. The traditional weighted subtraction method also predicted a linear correlation between the measured signal and the known iodine mass thickness. However, the correlation slope and offset values were strongly dependent on the total breast thickness and density. Conclusion The results of the current study suggest that iodine mass thickness for cm-scale lesions can be accurately quantified with contrast-enhanced spectral mammography. The quantitative information can potentially improve the differential power for malignancy.

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Postmortem validation of breast density using dual‐energy mammography

Cited by 14 publications

References 78 publications

Breast Density Evaluation Using Spectral Mammography, Radiologist Reader Assessment, and Segmentation Techniques

Breast Density Evaluation Using Spectral Mammography, Radiologist Reader Assessment, and Segmentation Techniques

Volumetric breast density measurement: sensitivity analysis of a relative physics approach

Quantitative contrast‐enhanced spectral mammography based on photon‐counting detectors: A feasibility study

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