Usefulness of feature analysis of breast-specific gamma imaging for predicting malignancy

Clinical impact of molecular breast imaging as adjunct diagnostic modality in evaluation of indeterminate breast abnormalities and unresolved diagnostic concerns

PURPOSE

Improvements in molecular breast imaging (MBI) have increased the use of MBI as adjunct diagnostic modality and alternative to MRI. We aimed to assess the value of MBI in patients with equivocal breast lesions on conventional imaging, especially in terms of its ability to rule out malignancy.

METHODS

We selected patients who underwent MBI in addition to conventional diagnostics due to equivocal breast lesions between 2012 and 2015. All patients underwent digital mammography, target ultrasound and MBI. MBI was performed using a single-head Dilon 6800 gamma camera after administration of 600 MBq 99m Tc-sestamibi. Imaging was reported according to BI-RADS classification and compared with pathology or follow-up of ≥6 months.

RESULTS

Of 226 women included, pathology was obtained in 106 (47%) and (pre)malignant lesions were found in 25 (11%). Median follow-up was 5.4 years (IQR 3.9-7.1). Sensitivity was higher for MBI compared to conventional diagnostics (84% vs. 32%; P  = 0.002), identifying malignancy in 21 and 6 patients, respectively, but specificity did not differ (86% vs. 81%; P  = 0.161). Positive and negative predictive value were 43% and 98% for MBI and 17% and 91% for conventional diagnostics. MBI was discordant with conventional diagnostics in 68 (30%) patients and correctly changed diagnosis in 46 (20%) patients, identifying 15 malignant lesions. In subgroups with nipple discharge ( N  = 42) and BI-RADS 3 lesions ( N  = 113) MBI detected 7 of 8 occult malignancies.

CONCLUSION

MBI correctly adjusted treatment in 20% of patients with diagnostic concerns after conventional work-up, and could rule out malignancy with a high negative predictive value of 98%.

Comparison of BSGI, MRI, mammography, and ultrasound for the diagnosis of breast lesions and their correlations with specific molecular subtypes in Chinese women

Background

Breast cancer is a leading cause of cancer in females, and is the second leading cancer-related cause of death in this group. Early diagnosis is essential to breast cancer to be effectively treated, and ultrasound, mammography, and magnetic resonance imaging (MRI) represent three key technologies that are utilized for the diagnosis of breast lesions. Breast-specific gamma imaging (BSGI) is an approach to molecular breast imaging that allows for high-resolution radio-imaging that is not adversely impacted by breast tissue density. This study was therefore designed to assess the relative diagnostic efficacy of BSGI, MRI, mammography, and ultrasound in different molecular subtypes of breast cancer among Chinese women.

Methods

Diagnostic findings from 390 patients that had undergone diagnosis and treatment in our breast surgery department were retrospectively reviewed. Patients had been diagnosed via BSGI, mammography, ultrasound, and MRI. The diagnostic efficacy of these different imaging modalities and their associated biological characteristics were compared in the present study.

Results

A total of 229 of these 390 patients (58.7%) were diagnosed with malignant breast cancer, with the remaining 161 (41.3%) cases having been found to be benign. BSGI, MRI, mammography, and ultrasound yielded respective sensitivity values of 91.7, 92.5, 77.3, and 82.1%, while the respective specificity values for these imaging modalities were 80.7, 69.7, 74.5, and 70.8%. For lesions > 1 cm, BSGI offered a sensitivity of 92.5%. For mammographic breast density A, B, C, and D, BSGI offered a sensitivity of 93.3, 94.0, 91.5, and 89.3%, respectively. BSGI also yielded a significantly higher lesion-to-normal lesion ratio (LNR) for malignant lesions relative to benign lesions (2.76 ± 1.32 vs 1.46 ± 0.49).

Conclusions

These findings confirm that BSGI is highly sensitive and is superior to mammography in the detection and diagnosis of ductal carcinomas in situ (DCIS). Such diagnostic efficacy can be further improved by using BSGI as an auxiliary modality to mammography and ultrasound, potentially improving the reliability of breast lesion diagnosis, thereby ensuring that patients receive rapid and effective treatment without the risk of misdiagnosis or unnecessary surgical treatment.

Breast-specific gamma imaging or ultrasonography as adjunct imaging diagnostics in women with mammographically dense breasts

BACKGROUND

Mammography (MMG) shows decreased diagnostic accuracy in dense breast tissue, and thus, ultrasonography (US) and breast-specific gamma imaging (BSGI) have gradually been adopted for women with mammographically dense breasts. However, these two adjunct modalities have not been directly compared in previous studies. Hence, we investigated the adjunctive efficacy of US and BSGI in mammographically dense breasts.

METHODS

This retrospective, comparative study recruited women with mammographically dense breasts. All enrolled women underwent US and BSGI as adjunctive imaging, and the comparative sensitivity, specificity, and diagnostic accuracy of combined MMG plus BSGI versus MMG plus US were evaluated. McNemar's test was used for paired binary data in this comparative analysis.

RESULTS

From April 2013 to April 2016, 364 women with mammographically dense breasts and a final surgical or biopsy pathological diagnosis were recruited, comprising 218 cases of malignant disease (59.9%) and 146 cases of benign disease (40.1%). There was no difference between BSGI and US in enhancing the sensitivity of MMG diagnosis (Se-Difference 3.2%, p = 0.23), but the diagnostic specificity of MMG plus BSGI was superior to that of MMG plus US (Sp-Difference 10.3%, p = 0.003). The area under the ROC curve showed that MMG plus BSGI had better diagnostic accuracy than MMG plus US (0.90 vs. 0.83, p = 0.0019).

CONCLUSIONS

For women with mammographically dense breasts, MMG plus BSGI or US can improve the diagnostic accuracy. In addition, BSGI has high specificity and could reduce invasive biopsies and thus may represent a viable diagnostic imaging alternative for mammographically dense breasts.

KEY POINTS

• Both BSGI and US can be applied as adjunct imaging diagnostics in women with mammographically dense breasts. • The diagnostic accuracy of MMG plus BSGI was higher than that of MMG plus US. • BSGI has the potential to be used as an adjunct diagnostic modality in women with mammographically dense breasts.

Histogram analysis with computed tomography angiography for discriminating soft tissue sarcoma from benign soft tissue tumor

To investigate the feasibility of histogram analysis with computed tomography angiography (CTA) in distinguishing between soft tissue sarcomas and benign soft tissue tumors. Fourty nine patients (23 men, mean age = 44.3 years, age range = 25-64) with pathologically-confirmed soft tissue sarcoma (n = 24) or benign soft tissue tumors (n = 25) in the lower extremities undergoing CTA for tumor evaluation were retrospectively analyzed. Two radiologists separately performed histogram analyses of CT density with CTA images by drawing a region of interest (ROI). The 10th (P10), 25th (P25), 50th (P50), 75th (P75), 90th percentiles (P90), mean, and standard deviations (SD) of measured tumor density were obtained along with measurements of the absolute value of kurtosis (AVK), absolute value of skewness (AVS), and inhomogeneity for each tumor. Intra-class correlation coefficients (ICC) were calculated to determine inter- and intra-reader variability in parameter measurements. The Mann-Whitney U test was used to compare histogram parameters between soft tissue sarcomas and benign soft tissue tumors. Receiver operator characteristic (ROC) curves were constructed to evaluate the accuracy of tumor discrimination. ICC was greater than 0.7 for AVS, AVK, and inhomogeneity, and >0.9 for mean, SD, and all percentile measures. There was no significant difference in P10, P25, P50, P75, P90, mean, or SD between soft tissue sarcomas and benign tumors (P > .05). AVS, AVK, and inhomogeneity were significantly higher in soft tissue sarcomas (P < .05). Areas under the curve (AUC) were 0.81, 0.83, and 0.84 for AVS, AVK, and inhomogeneity respectively. AUC were below 0.6 for mean, SD, and all percentiles.Skewness, kurtosis, and inhomogeneity measurements derived from histogram analysis from CTA distinguish between soft tissue sarcomas and benign soft tissue tumors.