Tumor characteristics of ductal carcinoma in situ of breast visualized on [F-18] fluorodeoxyglucose-positron emission tomography/computed tomography: Results from a retrospective study

Relationship between Volpara Density Grade and Compressed Breast Thickness in Japanese Patients with Breast Cancer

BACKGROUND

High breast density found using mammographs (MGs) reduces positivity rates and is considered a risk factor for breast cancer. Research on the relationship between Volpara density grade (VDG) and compressed breast thickness (CBT) in the Japanese population is still lacking. Moreover, little attention has been paid to pseudo-dense breasts with CBT < 30 mm among high-density breasts. We investigated VDG, CBT, and apparent high breast density in patients with breast cancer.

METHODS

Women who underwent MG and breast cancer surgery at our institution were included. VDG and CBT were measured. VDG was divided into a non-dense group (NDG) and a dense group (DG).

RESULTS

This study included 419 patients. VDG was negatively correlated with CBT. The DG included younger patients with lower body mass index (BMI) and thinner CBT. In the DG, patients with CBT < 30 mm had lower BMI and higher VDG; however, no significant difference was noted in the positivity rate of the two groups.

CONCLUSIONS

Younger women tend to have higher breast density, resulting in thinner CBT, which may pose challenges in detecting breast cancer on MGs. However, there was no significant difference in the breast cancer detection rate between CBT < 30 mm and CBT ≥ 30 mm.

Feasibility of Portable Microwave Imaging Device for Breast Cancer Detection

Purpose: Microwave radar-based breast imaging technology utilizes the principle of radar, in which radio waves reflect at the interface between target and normal tissues, which have different permittivities. This study aims to investigate the feasibility and safety of a portable microwave breast imaging device in clinical practice. Materials and methods: We retrospectively collected the imaging data of ten breast cancers in nine women (median age: 66.0 years; range: 37–78 years) who had undergone microwave imaging examination before surgery. All were Japanese and the tumor sizes were from 4 to 10 cm. Using a five-point scale (1 = very poor; 2 = poor; 3 = fair; 4 = good; and 5 = excellent), a radiologist specialized in breast imaging evaluated the ability of microwave imaging to detect breast cancer and delineate its location and size in comparison with conventional mammography and the pathological findings. Results: Microwave imaging detected 10/10 pathologically proven breast cancers, including non-invasive ductal carcinoma in situ (DCIS) and micro-invasive carcinoma, whereas mammography failed to detect 2/10 breast cancers due to dense breast tissue. In the five-point evaluation, median score of location and size were 4.5 and 4.0, respectively. Conclusion: The results of the evaluation suggest that the microwave imaging device is a safe examination that can be used repeatedly and has the potential to be useful in detecting breast cancer.

Investigating the Image Quality and Utility of Synthetic MRI in the Breast

Purpose

Synthetic MRI reconstructs multiple sequences in a single acquisition. In the present study, we aimed to compare the image quality and utility of synthetic MRI with that of conventional MRI in the breast.

Methods

We retrospectively collected the imaging data of 37 women (mean age: 55.1 years; range: 20–78 years) who had undergone both synthetic and conventional MRI of T2-weighted, T1-weighted, and fat-suppressed (FS)-T2-weighted images. Two independent breast radiologists evaluated the overall image quality, anatomical sharpness, contrast between tissues, image homogeneity, and presence of artifacts of synthetic and conventional MRI on a 5-point scale (5 = very good to 1 = very poor). The interobserver agreement between the radiologists was evaluated using weighted kappa.

Results

For synthetic MRI, the acquisition time was 3 min 28 s. On the 5-point scale evaluation of overall image quality, although the scores of synthetic FS-T2-weighted images (4.01 ± 0.56) were lower than that of conventional images (4.95 ± 0.23; P < 0.001), the scores of synthetic T1- and T2-weighted images (4.95 ± 0.23 and 4.97 ± 0.16) were comparable with those of conventional images (4.92 ± 0.27 and 4.97 ± 0.16; P = 0.484 and 1.000, respectively). The kappa coefficient of conventional MRI was fair (0.53; P < 0.001), and that of conventional MRI was fair (0.46; P < 0.001).

Conclusion

The image quality of synthetic T1- and T2-weighted images was similar to that of conventional images and diagnostically acceptable, whereas the quality of synthetic T2-weighted FS images was inferior to conventional images. Although synthetic MRI images of the breast have the potential to provide efficient image diagnosis, further validation and improvement are required for clinical application.

Classification of Breast Masses on Ultrasound Shear Wave Elastography using Convolutional Neural Networks

We aimed to use deep learning with convolutional neural networks (CNNs) to discriminate images of benign and malignant breast masses on ultrasound shear wave elastography (SWE). We retrospectively gathered 158 images of benign masses and 146 images of malignant masses as training data for SWE. A deep learning model was constructed using several CNN architectures (Xception, InceptionV3, InceptionResNetV2, DenseNet121, DenseNet169, and NASNetMobile) with 50, 100, and 200 epochs. We analyzed SWE images of 38 benign masses and 35 malignant masses as test data. Two radiologists interpreted these test data through a consensus reading using a 5-point visual color assessment (SWEc) and the mean elasticity value (in kPa) (SWEe). Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated. The best CNN model (which was DenseNet169 with 100 epochs), SWEc, and SWEe had a sensitivity of 0.857, 0.829, and 0.914 and a specificity of 0.789, 0.737, and 0.763 respectively. The CNNs exhibited a mean AUC of 0.870 (range, 0.844-0.898), and SWEc and SWEe had an AUC of 0.821 and 0.855. The CNNs had an equal or better diagnostic performance compared with radiologist readings. DenseNet169 with 100 epochs, Xception with 50 epochs, and Xception with 100 epochs had a better diagnostic performance compared with SWEc (P = 0.018-0.037). Deep learning with CNNs exhibited equal or higher AUC compared with radiologists when discriminating benign from malignant breast masses on ultrasound SWE.

FDG PET Hybrid Imaging

Molecular imaging with positron emission tomography (PET) using tumour-seeking radiopharmaceuticals has gained wide acceptance in oncology with many clinical applications. The hybrid imaging modality PET/CT (computed tomography) allows assessing molecular as well as morphologic information at the same time. Therefore, PET/CT represents an efficient tool for whole-body staging and re-staging within one imaging modality. In oncology, the glucose analogue 18-F-fluorodeoxyglucose (FDG) is the most widely used PET/CT radiopharmaceutical in clinical routine. FDG PET and FDG PET/CT have been used for staging and re-staging of tumour patients in numerous studies. This chapter will discuss the use and the main indications of FDG PET/CT in oncology with special emphasis on lung cancer, lymphoma, head and neck cancer, melanoma and breast cancer (among other tumour entities). A review of the current literature is given with respect to primary diagnosis, staging and diagnosis of recurrent disease. Besides its integral role in diagnosis, staging and re-staging of disease in oncology, there is increasing evidence that FDG PET/CT can be used for therapy response assessment (possibly influencing therapeutic management and treatment planning) by evaluating tumour control, which will also be discussed in this chapter.

Is there a difference in FDG PET findings of invasive ductal carcinoma of the breast with and without coexisting DCIS?

OBJECTIVES

Studies have reported that invasive ductal carcinoma (IDC) with coexisting ductal carcinoma in situ (DCIS) show lower metastatic potential and recurrence and better overall survival than pure IDC. In this study, we assessed F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) images of patients with newly diagnosed IDC to determine if there is any difference in PET findings in IDC-DCIS and pure IDC cases.

METHODS

FDG PET/CT images of patients with newly diagnosed IDC of the breast who subsequently underwent breast surgery and had histopathology result in our records were further evaluated. Tumor grade, pathological staging, and presence of DCIS were noted from the histopathology results. Standardized uptake value (SUV) of the primary tumor (SUVmax and SULmax), other hypermetabolic foci in the breast, and ipsilateral normal breast were measured. Presence of axillary and distant metastases was noted.

RESULTS

Fifty seven (57) patients with IDC were included. Coexisting DCIS was present in 44 (IDC-DCIS) and not present in 13 (pure IDC) cases. Per histopathology, the primary tumor was unifocal in 33 IDC-DCIS (75%) and 12 pure IDC (92.3%) cases, and multifocal in 11 IDC-DCIS cases (25%), and 1 pure IDC case (7.7%). FDG uptake was multifocal in 20 IDC-DCIS cases (45.5%) and 1 pure IDC case (7.7%), and unifocal in 24 IDC-DCIS (54.5%), and 12 pure IDC (92.3%) cases. There was no significant difference in patient age, size of the primary tumor, SUVmax and SULmax of the primary tumor and SUVmax of the normal breast in IDC-DCIS and pure IDC cases (p>0.05). Pathology showed axillary metastasis in all 13 pure IDC (100%), and 27 IDC-DCIS (61.4%) cases. PET showed axillary uptake in 25 IDC-DCIS (56.8%), and 8 pure IDC (61.5%) cases, and abnormal/questionable distant uptake in 12 IDC-DCIS cases and 1 pure IDC case.

CONCLUSION

In our preliminary findings, multifocal breast FDG uptake and multifocal tumor appear to be more common in IDC-DCIS than pure IDC. There is no significant difference in SUV and size of the primary tumor in IDC-DCIS and pure IDC cases. Axillary metastases appear to be more common in pure IDC than IDC-DCIS cases.

Simultaneous comparison between strain and shear wave elastography of breast masses for the differentiation of benign and malignant lesions by qualitative and quantitative assessments

PURPOSE

To compare the addition of diagnostic strain elastography (SE) and shear wave elastography (SWE) values to the conventional B-mode ultrasonography in differentiating between benign and malignant breast masses by qualitative and quantitative assessments.

MATERIALS AND METHODS

B-mode ultrasound, SE, and SWE were simultaneously performed using one ultrasound system in 148 breast masses; 88 of them were malignant. The breast imaging reporting and data system category in the B-mode, Tsukuba score (SE_Tsu), Fat-Lesion-Ratio (SE_FLR) in SE, and five-point color assessment (SWE_col) and elasticity values (SWE_ela) in SWE were assessed. The results were compared using the area under the receiver-operating characteristic curve (AUC).

RESULT

The AUC for B-mode and each elastography were similar (B-mode, 0.889; SE_Tsu, 0.885; SE_FLR, 0.875; SWE_col, 0.881; SWE_ela, 0.885; P > 0.05). The combined sets between B-mode and either of the elastography technique showed good diagnostic performance (B-mode + SE_Tsu, 0.903; B-mode + SE_FLR, 0.909; B-mode + SWE_col, 0.919; B-mode + SWE_ela, 0.914). B-mode + SWE_col and B-mode + SWE_ela showed a higher AUC than B-mode alone (P = 0.026 and 0.029), and B-mode + SE_Tsu and B-mode + SE_FLR showed comparable AUC to B-mode alone (P = 0.196 and 0.085). There was no significant difference between qualitative and quantitative assessments for the combined sets of B-mode and elastography (P > 0.05).

CONCLUSION

The addition of both SE and SWE to B-mode ultrasound improved the diagnostic performance with increased AUC, and especially SWE was more useful than SE, and no significant difference was found between qualitative and quantitative assessments.