Carrie B. Hruska

Dedicated Dual-Head Gamma Imaging for Breast Cancer Screening in Women with Mammographically Dense Breasts

PURPOSE To compare performance characteristics of dedicated dual-head gamma imaging and mammography in screening women with mammographically dense breasts. MATERIALS AND METHODS Asymptomatic women (n = 1007) who had heterogeneously or extremely dense breasts on prior mammograms and additional risk factors provided informed consent to enroll in an institutional review board-approved HIPAA-compliant protocol. Participants underwent mammography and gamma imaging after a 740-mBq (20-mCi) technetium 99m sestamibi injection. Reference standard (more severe cancer diagnosis or 12-month follow-up findings) was available for 936 of 969 eligible participants. Diagnostic yield, sensitivity, specificity, and positive predictive values (PPVs) were determined for mammography, gamma imaging, and both combined. RESULTS Of 936 participants, 11 had cancer (one with mammography only, seven with gamma imaging only, two with both combined, and one with neither). Diagnostic yield was 3.2 per 1000 (95% confidence interval [CI]: 1.1, 9.3) for mammography, 9.6 per 1000 (95% CI: 5.1, 18.2) for gamma imaging, and 10.7 per 1000 (95% CI: 5.8, 19.6) for both (P = .016 vs mammography alone). One participant had a second ipsilateral cancer detected with gamma imaging only. Prevalent screening gamma imaging demonstrated equivalent specificity relative to incident screening mammography (93% [861 of 925] vs 91% [840 of 925], P = .069). Of eight cancers detected with gamma imaging only, six (75%) were invasive (median size, 1.1 cm; range, 0.4-5.1 cm); all were node negative. The ratio of the number of patients with breast cancer per number of screening examinations with abnormal findings was 3% (three of 88) for mammography and 12% (nine of 73) for gamma imaging (P = .01). The number of breast cancers diagnosed per number of biopsies performed was 18% (three of 17) for mammography and 28% (10 of 36) for gamma imaging (P = .36). CONCLUSION Addition of gamma imaging to mammography significantly increased detection of node-negative breast cancer in dense breasts by 7.5 per 1000 women screened (95% CI: 3.6, 15.4). To be clinically important, gamma imaging will need to show equivalent performance at decreased radiation doses.

Molecular breast imaging: use of a dual-head dedicated gamma camera to detect small breast tumors.

OBJECTIVE Molecular breast imaging with a single-head cadmium zinc telluride (CZT) gamma camera has previously been shown to have good sensitivity for the detection of small lesions. To further improve sensitivity, we developed a dual-head molecular breast imaging system using two CZT detectors to simultaneously acquire opposing breast views and reduce lesion-to-detector distance. We determined the incremental gain in sensitivity of molecular breast imaging with dual detectors. SUBJECTS AND METHODS Patients with BI-RADS category 4 or 5 lesions < 2 cm that were identified on mammography or sonography and scheduled for biopsy underwent molecular breast imaging as follows: After injection of 740 MBq of technetium-99m ((99m)Tc) sestamibi, 10-minute craniocaudal and mediolateral oblique views of each breast were acquired. Blinded reviews were performed using images from both detectors 1 and 2 and images from detector 1 only (simulating a single-head system). Lesions were scored on a scale of 1-5; 2 or higher was considered positive. RESULTS Of the 150 patients in the study, 128 cancers were confirmed in 88 patients. Averaging the results from the three blinded readers, the sensitivity of dual-head molecular breast imaging was 90% (115/128), whereas the sensitivity from review of only single-head molecular breast imaging was 80% (102/128). The sensitivity for the detection of cancers < or = 10 mm in diameter was 82% (50/61) for dual-head molecular breast imaging and 68% (41/61) for single-head molecular breast imaging. On average, 13 additional cancers were seen on dual-head images and the tumor uptake score increased by 1 or more in 60% of the identified tumors. CONCLUSION Gains in sensitivity with the dual-head system molecular breast imaging are partially due to increased confidence in lesion detection. Molecular breast imaging can reliably detect breast lesions < 2 cm and dual-head molecular breast imaging can significantly increase sensitivity for subcentimeter lesions.

NEMA NU 2-2007 performance measurements of the Siemens Inveon preclinical small animal PET system.

National Electrical Manufacturers Association (NEMA) NU 2-2007 performance measurements were conducted on the Inveon preclinical small animal PET system developed by Siemens Medical Solutions. The scanner uses 1.51 x 1.51 x 10 mm LSO crystals grouped in 20 x 20 blocks; a tapered light guide couples the LSO crystals of a block to a position-sensitive photomultiplier tube. There are 80 rings with 320 crystals per ring and the ring diameter is 161 mm. The transaxial and axial fields of view (FOVs) are 100 and 127 mm, respectively. The scanner can be docked to a CT scanner; the performance characteristics of the CT component are not included herein. Performance measurements of spatial resolution, sensitivity, scatter fraction and count rate performance were obtained for different energy windows and coincidence timing window widths. For brevity, the results described here are for an energy window of 350-650 keV and a coincidence timing window of 3.43 ns. The spatial resolution at the center of the transaxial and axial FOVs was 1.56, 1.62 and 2.12 mm in the tangential, radial and axial directions, respectively, and the system sensitivity was 36.2 cps kBq(-1) for a line source (7.2% for a point source). For mouse- and rat-sized phantoms, the scatter fraction was 5.7% and 14.6%, respectively. The peak noise equivalent count rate with a noisy randoms estimate was 1475 kcps at 130 MBq for the mouse-sized phantom and 583 kcps at 74 MBq for the rat-sized phantom. The performance measurements indicate that the Inveon PET scanner is a high-resolution tomograph with excellent sensitivity that is capable of imaging at a high count rate.

JOURNAL CLUB: Molecular Breast Imaging at Reduced Radiation Dose for Supplemental Screening in Mammographically Dense Breasts

OBJECTIVE. The purpose of this study was to assess the diagnostic performance of supplemental screening molecular breast imaging (MBI) in women with mammographically dense breasts after system modifications to permit radiation dose reduction. SUBJECTS AND METHODS. A total of 1651 asymptomatic women with mammographically dense breasts on prior mammography underwent screening mammography and adjunct MBI performed with 300-MBq (99m)Tc-sestamibi and a direct-conversion (cadmium zinc telluride) gamma camera, both interpreted independently. The cancer detection rate, sensitivity, specificity, and positive predictive value of biopsies performed (PPV3) were determined. RESULTS. In 1585 participants with a complete reference standard, 21 were diagnosed with cancer: two detected by mammography only, 14 by MBI only, three by both modalities, and two by neither. Of 14 participants with cancers detected only by MBI, 11 had invasive disease (median size, 0.9 cm; range, 0.5-4.1 cm). Nine of 11 (82%) were node negative, and two had bilateral cancers. With the addition of MBI to mammography, the overall cancer detection rate (per 1000 screened) increased from 3.2 to 12.0 (p < 0.001) (supplemental yield 8.8). The invasive cancer detection rate increased from 1.9 to 8.8 (p < 0.001) (supplemental yield 6.9), a relative increase of 363%, while the change in DCIS detection was not statistically significant (from 1.3 to 3.2, p =0.250). For mammography alone, sensitivity was 24%; specificity, 89%; and PPV3, 25%. For the combination, sensitivity was 91% (p < 0.001); specificity, 83% (p < 0.001); and PPV3, 28% (p = 0.70). The recall rate increased from 11.0% with mammography alone to 17.6% (p < 0.001) for the combination; the biopsy rate increased from 1.3% for mammography alone to 4.2% (p < 0.001). CONCLUSION. When added to screening mammography, MBI performed using a radiopharmaceutical activity acceptable for screening (effective dose 2.4 mSv) yielded a supplemental cancer detection rate of 8.8 per 1000 women with mammographically dense breasts.

Design of optimal collimation for dedicated molecular breast imaging systems

Molecular breast imaging (MBI) is a functional imaging technique that uses specialized small field-of-view gamma cameras to detect the preferential uptake of a radiotracer in breast lesions. MBI has potential to be a useful adjunct method to screening mammography for the detection of occult breast cancer. However, a current limitation of MBI is the high radiation dose (a factor of 7-10 times that of screening mammography) associated with current technology. The purpose of this study was to optimize the gamma camera collimation with the aim of improving sensitivity while retaining adequate resolution for the detection of sub-10-mm lesions. Square-hole collimators with holes matched to the pixilated cadmium zinc telluride detector elements of the MBI system were designed. Data from MBI patient studies and parameters of existing dual-head MBI systems were used to guide the range of desired collimator resolutions, source-to-collimator distances, pixel sizes, and collimator materials that were examined. General equations describing collimator performance for a conventional gamma camera were used in the design process along with several important adjustments to account for the specialized imaging geometry of the MBI system. Both theoretical calculations and a Monte Carlo model were used to measure the geometric efficiency (or sensitivity) and resolution of each designed collimator. Results showed that through optimal collimation, collimator sensitivity could be improved by factors of 1.5-3.2, while maintaining a collimator resolution of either < or =5 or < or = 7.5 mm at a distance of 3 cm from the collimator face. These gains in collimator sensitivity permit an inversely proportional drop in the required dose to perform

Molecular Breast Imaging: Advantages and Limitations of a Scintimammographic Technique in Patients with Small Breast Tumors

Abstract:  Preliminary studies from our laboratory showed that molecular breast imaging (MBI) can reliably detect tumors <2 cm in diameter. This study extends our work to a larger patient population and examines the technical factors that influence the ability of MBI to detect small breast tumors. Following injection of 740 MBq Tc‐99m sestamibi, MBI was performed on 100 patients scheduled for biopsy of a lesion suspicious for malignancy that measured <2 cm on mammography or sonography. Using a small field of view gamma camera, patients were imaged in the standard mammographic views using light pain‐free compression. Subjective discomfort, breast thickness, the amount of breast tissue in the detector field of view, and breast counts per unit area were measured and recorded. Follow‐up was obtained in 99 patients; 53 patients had 67 malignant tumors confirmed at surgery. Of these, 57 of 67 were detected by MBI (sensitivity 85%). Sensitivity was 29%, 86%, and 97% for tumors <5, 6–10, and ≥11 mm in diameter, respectively. In seven patients, MBI identified eight additional mammographically occult tumors. Of 47 patients with no evidence of cancer at biopsy or surgery, there were 36 true negative and 11 false positive scans on MBI. MBI has potential for the regular detection of malignant breast tumors less than 2 cm in diameter. Work in progress to optimize the imaging parameters and technique may further improve sensitivity and specificity.

Proof of concept for low-dose molecular breast imaging with a dual-head CZT gamma camera. Part II. Evaluation in patients

PURPOSE Molecular breast imaging (MBI) is a nuclear medicine technology that uses dual-head cadmium zinc telluride (CZT) gamma cameras to image functional uptake of a radiotracer, Tc-99m sestamibi, in the breast. An important factor in adoption of MBI in the screening setting is reduction of the necessary administered dose of Tc-99m sestamibi from the typically used dose of 740 MBq to approximately 148 MBq, such that MBIs whole-body effective dose is comparable to that of screening mammography. Methods that increase MBI count sensitivity may allow a proportional reduction in the necessary administered dose. Our objective was to evaluate the impact of two count sensitivity improvement methods on image quality by evaluating count sensitivity, spatial resolution, and lesion contrast in phantom simulations. METHODS Two dual-head CZT-based MBI systems were studied: LumaGem and Discovery NM 750b. Two count sensitivity improvement methods were implemented: registered collimators optimized for dedicated breast imaging and widened energy acceptance window optimized for use with CZT. System sensitivity, spatial resolution, and tumor contrast-to-noise ratio (CNR) were measured comparing standard collimation and energy window setting [126-154 keV (+10%, -10%)] with optimal collimation and a wide energy window [110-154 keV (+10%, -21%)]. RESULTS Compared to the standard collimator designs and energy windows for these two systems, use of registered optimized collimation and wide energy window increased system sensitivity by a factor of 2.8-3.6. Spatial resolution decreased slightly for both systems with new collimation. At 3 cm from the collimator face, LumaGems spatial resolution was 4.8 and 5.6 mm with standard and optimized collimation; Discovery NM 750bs spatial resolution was 4.4 and 4.6 mm with standard and optimized collimation, respectively. For both systems, at tumor depths of 1 and 3 cm, use of optimized collimation and wide energy window significantly improved CNR compared to standard settings for tumors 8.0 and 9.2 mm in diameter. At the closer depth of 1 cm, optimized collimation and wide energy window also significantly improved CNR for 5.9 mm tumors on Discovery NM 750b. CONCLUSIONS Registered optimized collimation and wide energy window yield a substantial gain in count sensitivity and measurable gain in CNR, with some loss in spatial resolution compared to the standard collimator designs and energy windows used on these two systems. At low-count densities calculated to represent doses of 148 MBq, this tradeoff results in adequate count density and lesion contrast for detection of lesions ≥8 mm in the middle of a typical breast (3 cm deep) and lesions ≥6 mm close to the collimator (1 cm deep).

Molecular breast imaging

Molecular breast imaging (MBI) is a new nuclear medicine technique that utilizes small semiconductor-based γ-cameras in a mammographic configuration to provide high-resolution functional images of the breast. Current studies with MBI have used Tc-99m sestamibi, which is an approved agent for breast imaging. The procedure is relatively simple to perform. Imaging can be performed within 5 min postinjection, with the breast lightly compressed between the two detectors. Images of each breast are acquired in the craniocaudal and mediolateral oblique projections facilitating comparison with mammography. Key studies have confirmed that MBI has a high sensitivity for the detection of small breast lesions. In patients with suspected breast cancer, MBI has an overall sensitivity of 90%, with a sensitivity of 82% for lesions less than 10 mm in size. Sensitivity was lowest for tumors less than 5 mm in size. Tumor detection does not appear to be dependent on tumor type, but rather on tumor size. Studies using MBI and breast-specific γ-imaging have shown that these methods have comparable sensitivity to breast MRI. A large clinical trial compared MBI with screening mammography in over 1000 women with mammographically dense breast tissue and increased risk of breast cancer and showed that MBI detected two-to three-times more cancers than mammography. In addition, MBI appears to have slightly better specificity than mammography in this trial. MBI provides high-resolution functional images of the breast and its potential applications range from evaluation of the extent of disease to a role as an adjunct screening technique in certain high-risk populations. MBI is highly complementary to existing anatomical techniques, such as mammography, tomosynthesis and ultrasound.

Comparison of radiation exposure and associated radiation-induced cancer risks from mammography and molecular imaging of the breast

PURPOSE Recent studies have raised concerns about exposure to low-dose ionizing radiation from medical imaging procedures. Little has been published regarding the relative exposure and risks associated with breast imaging techniques such as breast specific gamma imaging (BSGI), molecular breast imaging (MBI), or positron emission mammography (PEM). The purpose of this article was to estimate and compare the risks of radiation-induced cancer from mammography and techniques such as PEM, BSGI, and MBI in a screening environment. METHODS The authors used a common scheme for all estimates of cancer incidence and mortality based on the excess absolute risk model from the BEIR VII report. The lifetime attributable risk model was used to estimate the lifetime risk of radiation-induced breast cancer incidence and mortality. All estimates of cancer incidence and mortality were based on a population of 100 000 females followed from birth to age 80 and adjusted for the fraction that survives to various ages between 0 and 80. Assuming annual screening from ages 40 to 80 and from ages 50 to 80, the cumulative cancer incidence and mortality attributed to digital mammography, screen-film mammography, MBI, BSGI, and PEM was calculated. The corresponding cancer incidence and mortality from natural background radiation was calculated as a useful reference. Assuming a 15%-32% reduction in mortality from screening, the benefit/risk ratio for the different imaging modalities was evaluated. RESULTS Using conventional doses of 925 MBq Tc-99m sestamibi for MBI and BSGI and 370 MBq F-18 FDG for PEM, the cumulative cancer incidence and mortality were found to be 15-30 times higher than digital mammography. The benefit/risk ratio for annual digital mammography was>50:1 for both the 40-80 and 50-80 screening groups, but dropped to 3:1 for the 40-49 age group. If the primary use of MBI, BSGI, and PEM is in women with dense breast tissue, then the administered doses need to be in the range 75-150 MBq for Tc-99m sestamibi and 35 MBq-70 MBq for F-18 FDG in order to obtain benefit/risk ratios comparable to those of mammography in these age groups. These dose ranges should be achievable with enhancements to current technology while maintaining a reasonable examination time. CONCLUSIONS The results of the dose estimates in this study clearly indicate that if molecular imaging techniques are to be of value in screening for breast cancer, then the administered doses need to be substantially reduced to better match the effective doses of mammography.

Comparison of Clinical and Automated Breast Density Measurements: Implications for Risk Prediction and Supplemental Screening

Purpose To compare the classification of breast density with two automated methods, Volpara (version 1.5.0; Matakina Technology, Wellington, New Zealand) and Quantra (version 2.0; Hologic, Bedford, Mass), with clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications and to examine associations of these measures with breast cancer risk. Materials and Methods In this study, 1911 patients with breast cancer and 4170 control subjects matched for age, race, examination date, and mammography machine were evaluated. Participants underwent mammography at Mayo Clinic or one of four sites within the San Francisco Mammography Registry between 2006 and 2012 and provided informed consent or a waiver for research, in compliance with HIPAA regulations and institutional review board approval. Digital mammograms were retrieved a mean of 2.1 years (range, 6 months to 6 years) before cancer diagnosis, with the corresponding clinical BI-RADS density classifications, and Volpara and Quantra density estimates were generated. Agreement was assessed with weighted κ statistics among control subjects. Breast cancer associations were evaluated with conditional logistic regression, adjusted for age and body mass index. Odds ratios, C statistics, and 95% confidence intervals (CIs) were estimated. Results Agreement between clinical BI-RADS density classifications and Volpara and Quantra BI-RADS estimates was moderate, with κ values of 0.57 (95% CI: 0.55, 0.59) and 0.46 (95% CI: 0.44, 0.47), respectively. Differences of up to 14% in dense tissue classification were found, with Volpara classifying 51% of women as having dense breasts, Quantra classifying 37%, and clinical BI-RADS assessment used to classify 43%. Clinical and automated measures showed similar breast cancer associations; odds ratios for extremely dense breasts versus scattered fibroglandular densities were 1.8 (95% CI: 1.5, 2.2), 1.9 (95% CI: 1.5, 2.5), and 2.3 (95% CI: 1.9, 2.8) for Volpara, Quantra, and BI-RADS classifications, respectively. Clinical BI-RADS assessment showed better discrimination of case status (C = 0.60; 95% CI: 0.58, 0.61) than did Volpara (C = 0.58; 95% CI: 0.56, 0.59) and Quantra (C = 0.56; 95% CI: 0.54, 0.58) BI-RADS classifications. Conclusion Automated and clinical assessments of breast density are similarly associated with breast cancer risk but differ up to 14% in the classification of women with dense breasts. This could have substantial effects on clinical practice patterns. (©) RSNA, 2015 Online supplemental material is available for this article.