The cone-beam breast computed tomography characteristics of breast non-mass enhancement lesions

Detectability of Breast Cancer in Dedicated Breast CT Compared With Mammography Dependent on Breast Density

OBJECTIVES

To evaluate the detectability of non-contrast-enhanced and contrast-enhanced spiral breast computed tomography ([non]-CE-SBCT) compared with mammography. Secondary objectives are to determine detectability depending on breast density and to evaluate appearance of breast malignancies according to BI-RADS descriptors.

METHODS

This retrospective institutional review board-approved study included 90 women with 105 biopsy-proven malignant breast lesions. Breast density, BI-RADS descriptors, and detectability were evaluated by 2 independent readers. Diagnostic confidence was rated on a 4-point Likert scale.

RESULTS

For readers 1 and 2, detectability was 83.8% and 80.0% for mammography, 99.1% and 99.1% for CE-SBCT ( P < 0.05), and 66.7% and 61.9% for non-CE-SBCT ( P < 0.05). With both readers, detectability in CE-SBCT was high for density A/B/C/D (both 100%/100%/100%/87.5%). Detectability of readers declined with increasing density for mammography (density A = 100%, B = 89.1% and 95.1%, C = 73.1%, D = 50.0% and 71.4%; P < 0.05) and for non-CE-SBCT (density A = 87.5% and 90.7%, B = 65.5% and 69.1%, C = 54.8% and 60.0%, D = 37.5%; P < 0.05). Mass lesions were detected with CT as often as with mammography, whereas architectural distortions and microcalcifications were detected less often with SBCT. Diagnostic confidence was very high or high in 97.2% for CE-SBCT, in 74.1% for non-CE-SBCT, and in 81.4% for mammography.

CONCLUSIONS

Detectability and diagnostic confidence were very high in CE-SBCT, regardless of breast density. The detectability of non-CE-SBCT was lower than that of mammography and declined with increasing breast density.

Clinical and Imaging Characteristics of Contrast-enhanced Mammography and MRI to Distinguish Microinvasive Carcinoma from Ductal Carcinoma In situ

RATIONALE AND OBJECTIVES

The prognosis of ductal carcinoma in situ with microinvasion (DCISM) is more similar to that of small invasive ductal carcinoma (IDC) than to pure ductal carcinoma in situ (DCIS). It is particularly important to accurately distinguish between DCISM and DCIS. The present study aims to compare the clinical and imaging characteristics of contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) between DCISM and pure DCIS, and to identify predictive factors of microinvasive carcinoma, which may contribute to a comprehensive understanding of DCISM in clinical diagnosis and support surveillance strategies, such as surgery, radiation, and other treatment decisions.

MATERIALS AND METHODS

Forty-seven female patients diagnosed with DCIS were included in the study from May 2019 to August 2023. Patients were further divided into two groups based on pathological diagnosis: DCIS and DCISM. Clinical and imaging characteristics of these two groups were analyzed statistically. The independent clinical risk factors were selected using multivariate logistic regression and used to establish the logistic model [Logit(P)]. The diagnostic performance of independent predictors was assessed and compared using receiver operating characteristic (ROC) analysis and DeLong's test.

RESULTS

In CEM, the maximum cross-sectional area (CSAmax), the percentage signal difference between the enhancing lesion and background in the craniocaudal and mediolateral oblique projection (%RSCC, and %RSMLO) were found to be significantly higher for DCISM compared to DCIS (p = 0.001; p < 0.001; p = 0.008). Additionally, there were noticeable statistical differences in the patterns of enhancement morphological distribution (EMD) and internal enhancement pattern (IEP) between DCIS and DCISM (p = 0.047; p = 0.008). In MRI, only CSAmax (p = 0.012) and IEP (p = 0.020) showed significant statistical differences. The multivariate regression analysis suggested that CSAmax (in CEM or MR) and %RSCC were independent predictors of DCISM (all p < 0.05). The area under the curve (AUC) of CSAmax (CEM), %RSCC (CEM), Logit(P) (CEM), and CSAmax (MR) were 0.764, 0.795, 0.842, and 0.739, respectively. There were no significant differences in DeLong's test for these values (all p > 0.10). DCISM was significantly associated with high nuclear grade, comedo type, high axillary lymph node (ALN) metastasis, and high Ki-67 positivity compared to DCIS (all p < 0.05).

CONCLUSION

The tumor size (CSAmax), enhancement index (%RS), and internal enhancement pattern (IEP) were highly indicative of DCISM. DCISM tends to express more aggressive pathological features, such as high nuclear grade, comedo-type necrosis, ALN metastasis, and Ki-67 overexpression. As with MRI, CEM has the capability to help predict when DCISM is accompanying DCIS.

Radiomics in cone-beam breast CT for the prediction of axillary lymph node metastasis in breast cancer: a multi-center multi-device study

OBJECTIVES

To develop a radiomics model in contrast-enhanced cone-beam breast CT (CE-CBBCT) for preoperative prediction of axillary lymph node (ALN) status and metastatic burden of breast cancer.

METHODS

Two hundred and seventy-four patients who underwent CE-CBBCT examination with two scanners between 2012 and 2021 from two institutions were enrolled. The primary tumor was annotated in each patient image, from which 1781 radiomics features were extracted with PyRadiomics. After feature selection, support vector machine models were developed to predict ALN status and metastatic burden. To avoid overfitting on a specific patient subset, 100 randomly stratified splits were made to assign the patients to either training/fine-tuning or test set. Area under the receiver operating characteristic curve (AUC) of these radiomics models was compared to those obtained when training the models only with clinical features and combined clinical-radiomics descriptors. Ground truth was established by histopathology.

RESULTS

One hundred and eighteen patients had ALN metastasis (N + (≥ 1)). Of these, 74 had low burden (N + (1~2)) and 44 high burden (N + (≥ 3)). The remaining 156 patients had none (N0). AUC values across the 100 test repeats in predicting ALN status (N0/N + (≥ 1)) were 0.75 ± 0.05 (0.67~0.93, radiomics model), 0.68 ± 0.07 (0.53~0.85, clinical model), and 0.74 ± 0.05 (0.67~0.88, combined model). For metastatic burden prediction (N + (1~2)/N + (≥ 3)), AUC values were 0.65 ± 0.10 (0.50~0.88, radiomics model), 0.55 ± 0.10 (0.40~0.80, clinical model), and 0.64 ± 0.09 (0.50~0.90, combined model), with all the ranges spanning 0.5. In both cases, the radiomics model was significantly better than the clinical model (both p < 0.01) and comparable with the combined model (p = 0.56 and 0.64).

CONCLUSIONS

Radiomics features of primary tumors could have potential in predicting ALN metastasis in CE-CBBCT imaging.

CLINICAL RELEVANCE STATEMENT

The findings support potential clinical use of radiomics for predicting axillary lymph node metastasis in breast cancer patients and addressing the limited axilla coverage of cone-beam breast CT.

KEY POINTS

• Contrast-enhanced cone-beam breast CT-based radiomics could have potential to predict N0 vs. N + (≥ 1) and, to a limited extent, N + (1~2) vs. N + (≥ 3) from primary tumor, and this could help address the limited axilla coverage, pending future verifications on larger cohorts. • The average AUC of radiomics and combined models was significantly higher than that of clinical models but showed no significant difference between themselves. • Radiomics features descriptive of tumor texture were found informative on axillary lymph node status, highlighting a higher heterogeneity for tumor with positive axillary lymph node.

CT values of contrast-enhanced CBBCT: A useful diagnostic tool for benign and malignant breast lesions

BACKGROUND

Computed tomography (CT) value studies of cone-beam breast CT (CBBCT) mainly focus on the enhancement value or enhancement rate, and there has been no study on the CT value (Hounsfield units [HU]) of the lesion itself.

PURPOSE

To investigate the CT values under contrast-enhanced CBBCT (CE-CBBCT) and non-contrast-enhanced CBBCT (NC-CBBCT) in scanning for the differential diagnosis of benign and malignant breast lesions.

MATERIAL AND METHODS

A retrospective analysis was performed on 189 cases of mammary glandular tissues that underwent NC-CBBCT and CE-CBBCT examination. The qualitative CT values of the lesions, standardized Δ(L-A), standardized Δ*(L - G), standardized Δ(L-A) (Post 1st-Pre), and standardized Δ*(L-G) (Post 2nd-Post 1st) between the benign and malignant groups were compared. Prediction performance was evaluated using receiver operating characteristic (ROC) curves.

RESULTS

In total, 58 cases were included in the benign group, 79 cases were included in the malignant group, and 52 cases were included in the normal group. The best diagnostic thresholds of CT values for L (Post 1st-Pre), Δ(L-A) (Post 1st-Pre), and Δ*(L-G) (Post 1st-Pre) were 49.5, 44, and 64.8 HU, respectively. The Δ(L-A) Post-1st rate values of CBBCT had medium diagnostic efficacy (AUC = 0.74, sensitivity = 76.6%, specificity = 69.4%).

CONCLUSION

CE-CBBCT can improve the diagnostic efficiency of breast lesions compared with NC-CBBCT. The CT values (HU) of lesions do not need to be standardized with fat and can be directly used in clinical differential diagnosis. The first contrast phase (60 s) is recommended to reduce the radiation exposure.

Contrast-Enhanced Cone-Beam Breast CT: An Analysis of Diagnostic Value in Predicting Breast Lesion With Rim Enhancement Malignancy

Background

The objective of the current study was to investigate the diagnostic value of contrast-enhanced cone-beam breast computed tomography (CE-CBBCT) for breast lesion with rim enhancement (RE).

Methods

All 36 patients were examined by non-contrast (NC-CBBCT) and contrast-enhanced CBBCT (CE-CBBCT) after contrast media (CM) injection. Qualitative morphological enhancement parameters and quantitative enhancement parameters were compared between malignant and benign groups. Multivariable logistic regression analysis was performed to identify independent factors that could predict breast lesion with RE malignancy. Receiver operating curve (ROC) was used to evaluate prediction performance.

Results

A total of 36 patients with 40 lesions underwent breast CE-CBBCT were enrolled. There were significant differences in most qualitative morphological enhancement parameters between the two groups. A multivariate logistic regression model showed that △standardized HU (INR_{phase 2}−INR_preCM) [odds ratio (OR) = 1.148, 95% CI = 1.034–1.276, p = 0.01] and △standardized HU (RP_{phase 2} − RP_{phase 1}) (OR = 0.891, 95% CI = 0.814–0.976, p = 0.013) were independent indicators in predicting breast lesion with RE malignancy. △standardized HU (INR_{phase 2} − INR_preCM) combined with △standardized HU (RP_{phase 2} − RP_{phase 1}) showed significant larger area under the receiver operating curve (AUC) and higher sensitivity than each alone (p < 0.001, AUC = 0.932, sensitivity = 92.59%, specificity = 92.31%). The regression equation of the prediction model was as follows: Logit (p) = 0.351 + 0.138X × △standardized HU (INR_{phase 2} − INR_preCM) − 0.115 × △standardized HU (RP_{phase 2} − RP_{phase 1}).

Conclusion

With the observation of qualitative morphological enhancement parameters and the comparison of quantitative enhancement parameters of CBBCT, a reliable basis for the diagnostic accuracy in predicting breast lesion with RE could be provided. These conclusions should be verified in large, well-designed studies.

Assessment of Cone-Beam Breast Computed Tomography for Predicting Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer: A Prospective Study

Background

Response surveillance of neoadjuvant chemotherapy is needed to facilitate treatment decisions. We aimed to assess the imaging features of cone-beam breast computed tomography (CBBCT) for predicting the pathologic response of breast cancer after neoadjuvant chemotherapy.

Methods

This prospective study included 81 women with locally advanced breast cancer who underwent neoadjuvant chemotherapy from August 2017 to January 2021. All patients underwent CBBCT before treatment, and 55 and 65 patients underwent CT examinations during the midtreatment (3 cycles) and late-treatment phases (7 cycles), respectively. Clinical information and quantitative parameters such as the diameter, volume, surface area, and CT density were compared between pathologic responders and nonresponders using the T–test and the Mann–Whitney U test. The performance of meaningful parameters was evaluated with the receiver operating characteristic curve, sensitivity, and specificity.

Results

The quantitative results for the segmented volume, segmented surface area, segmented volume reduction, maximum enhancement ratio, wash-in rate and two-minute enhancement value in the mid- and late-treatment periods had predictive value for pathologic complete response. The area under the curve for the prediction model after multivariate regression analysis was 0.874.

Conclusion

After comparing the outcomes of each timepoint, mid- and late-treatment parameters can be used to predict pathologic outcome. The late-treatment parameters showed significant value with a predictive model.

Dedicated breast CT: state of the art-Part II. Clinical application and future outlook

Dedicated breast CT is being increasingly used for breast imaging. This technique provides images with no compression, removal of tissue overlap, rapid acquisition, and available simultaneous assessment of microcalcifications and contrast enhancement. In this second installment in a 2-part review, the current status of clinical applications and ongoing efforts to develop new imaging systems are discussed, with particular emphasis on how to achieve optimized practice including lesion detection and characterization, response to therapy monitoring, density assessment, intervention, and implant evaluation. The potential for future screening with breast CT is also addressed. KEY POINTS: • Dedicated breast CT is an emerging modality with enormous potential in the future of breast imaging by addressing numerous clinical needs from diagnosis to treatment. • Breast CT shows either noninferiority or superiority with mammography and numerical comparability to MRI after contrast administration in diagnostic statistics, demonstrates excellent performance in lesion characterization, density assessment, and intervention, and exhibits promise in implant evaluation, while potential application to breast cancer screening is still controversial. • New imaging modalities such as phase-contrast breast CT, spectral breast CT, and hybrid imaging are in the progress of R & D.

Dedicated breast CT: state of the art-Part I. Historical evolution and technical aspects

Dedicated breast CT is an emerging 3D isotropic imaging technology for breast, which overcomes the limitations of 2D compression mammography and limited angle tomosynthesis while providing some of the advantages of magnetic resonance imaging. This first installment in a 2-part review describes the evolution of dedicated breast CT beginning with a historical perspective and progressing to the present day. Moreover, it provides an overview of state-of-the-art technology. Particular emphasis is placed on technical limitations in scan protocol, radiation dose, breast coverage, patient comfort, and image artifact. Proposed methods of how to address these technical challenges are also discussed. KEY POINTS: • Advantages of breast CT include no tissue overlap, improved patient comfort, rapid acquisition, and concurrent assessment of microcalcifications and contrast enhancement. • Current clinical and prototype dedicated breast CT systems differ in acquisition modes, imaging techniques, and detector types. • There are still details to be decided regarding breast CT techniques, such as scan protocol, radiation dose, breast coverage, patient comfort, and image artifact.