Investigation of imaging features in contrast-enhanced magnetic resonance imaging of benign and malignant breast lesions.

PURPOSE: This study aimed to enhance the diagnostic accuracy of contrast-enhanced breast magnetic resonance imaging (MRI) using gadobutrol for differentiating benign breast lesions from malignant ones. Moreover, this study sought to address the limitations of current imaging techniques and criteria based on the Breast Imaging Reporting and Data System (BI-RADS). MATERIALS AND METHODS: In a multicenter retrospective study conducted in Japan, 200 women were included, comprising 100 with benign lesions and 100 with malignant lesions, all classified under BI-RADS categories 3 and 4. The MRI protocol included 3D fast gradient echo T1- weighted images with fat suppression, with gadobutrol as the contrast agent. The analysis involved evaluating patient and lesion characteristics, including age, size, location, fibroglandular tissue, background parenchymal enhancement (BPE), signal intensity, and the findings of mass and non-mass enhancement. In this study, univariate and multivariate logistic regression analyses were performed, along with decision tree analysis, to identify significant predictors for the classification of lesions. RESULTS: Differences in lesion characteristics were identified, which may influence malignancy risk. The multivariate logistic regression model revealed age, lesion location, shape, and signal intensity as significant predictors of malignancy. Decision tree analysis identified additional diagnostic factors, including lesion margin and BPE level. The decision tree models demonstrated high diagnostic accuracy, with the logistic regression model showing an area under the curve of 0.925 for masses and 0.829 for non-mass enhancements. CONCLUSION: This study underscores the importance of integrating patient age, lesion location, and BPE level into the BI-RADS criteria to improve the differentiation between benign and malignant breast lesions. This approach could minimize unnecessary biopsies and enhance clinical decision-making in breast cancer diagnostics, highlighting the effectiveness of gadobutrol in breast MRI evaluations.

Computerized Segmentation Method for Nonmasses on Breast DCE-MRI Images Using ResUNet++ with Slice Sequence Learning and Cross-Phase Convolution.

The purpose of this study was to develop a computerized segmentation method for nonmasses using ResUNet++ with a slice sequence learning and cross-phase convolution to analyze temporal information in breast dynamic contrast material-enhanced magnetic resonance imaging (DCE-MRI) images. The dataset consisted of a series of DCE-MRI examinations from 54 patients, each containing three-phase images, which included one image that was acquired before contrast injection and two images that were acquired after contrast injection. In the proposed method, the region of interest (ROI) slice images are first extracted from each phase image. The slice images at the same position in each ROI are stacked to generate a three-dimensional (3D) tensor. A cross-phase convolution generates feature maps with the 3D tensor to incorporate the temporal information. Subsequently, the feature maps are used as the input layers for ResUNet++. New feature maps are extracted from the input data using the ResUNet++ encoders, following which the nonmass regions are segmented by a decoder. A convolutional long short-term memory layer is introduced into the decoder to analyze a sequence of slice images. When using the proposed method, the average detection accuracy of nonmasses, number of false positives, Jaccard coefficient, Dice similarity coefficient, positive predictive value, and sensitivity were 90.5%, 1.91, 0.563, 0.712, 0.714, and 0.727, respectively, larger than those obtained using 3D U-Net, V-Net, and nnFormer. The proposed method achieves high detection and shape accuracies and will be useful in differential diagnoses of nonmasses.

The Japanese breast cancer society clinical practice guidelines for breast cancer screening and diagnosis, 2022 edition.

This article provides updates to readers based on the newly published Japanese Breast Cancer Society Clinical Practice Guidelines for Breast Cancer Screening and Diagnosis, 2022 Edition. These guidelines incorporate the latest evaluation of evidence from studies of diagnostic accuracy. For each clinical question, outcomes for benefits and harms were established, and qualitative or quantitative systematic reviews were conducted. Recommendations were determined through voting by a multidisciplinary group, and guidelines were documented to facilitate shared decision-making among patients and medical professionals. The guidelines address screening, surveillance, and pre- and postoperative diagnosis of breast cancer. In an environment that demands an integrated approach, decisions are needed on how to utilize modalities, such as mammography, ultrasound, MRI, and PET/CT. Additionally, it is vital to understand the appropriate use of new technologies, such as tomosynthesis, elastography, and contrast-enhanced ultrasound, and to consider how best to adapt these methods for individual patients.

Use of a deep learning algorithm for non-mass enhancement on breast MRI: comparison with radiologists' interpretations at various levels.

PURPOSE: To evaluate the diagnostic performance of deep learning using the Residual Networks 50 (ResNet50) neural network constructed from different segmentations for distinguishing malignant and benign non-mass enhancement (NME) on breast magnetic resonance imaging (MRI) and conduct a comparison with radiologists with various levels of experience. MATERIALS AND METHODS: A total of 84 consecutive patients with 86 lesions (51 malignant, 35 benign) presenting NME on breast MRI were analyzed. Three radiologists with different levels of experience evaluated all examinations, based on the Breast Imaging-Reporting and Data System (BI-RADS) lexicon and categorization. For the deep learning method, one expert radiologist performed lesion annotation manually using the early phase of dynamic contrast-enhanced (DCE) MRI. Two segmentation methods were applied: a precise segmentation was carefully set to include only the enhancing area, and a rough segmentation covered the whole enhancing region, including the intervenient non-enhancing area. ResNet50 was implemented using the DCE MRI input. The diagnostic performance of the radiologists' readings and deep learning were then compared using receiver operating curve analysis. RESULTS: The ResNet50 model from precise segmentation achieved diagnostic accuracy equivalent [area under the curve (AUC) = 0.91, 95% confidence interval (CI) 0.90, 0.93] to that of a highly experienced radiologist (AUC = 0.89, 95% CI 0.81, 0.96; p = 0.45). Even the model from rough segmentation showed diagnostic performance equivalent to a board-certified radiologist (AUC = 0.80, 95% CI 0.78, 0.82 vs. AUC = 0.79, 95% CI 0.70, 0.89, respectively). Both ResNet50 models from the precise and rough segmentation exceeded the diagnostic accuracy of a radiology resident (AUC = 0.64, 95% CI 0.52, 0.76). CONCLUSION: These findings suggest that the deep learning model from ResNet50 has the potential to ensure accuracy in the diagnosis of NME on breast MRI.

The diffusion MRI signature index is highly correlated with immunohistochemical status and molecular subtype of invasive breast carcinoma.

OBJECTIVES: To evaluate the relationship of the signature index (S-index), an advanced diffusion MRI marker, and the immunohistochemical (IHC) status, proliferation rate, and molecular subtype of invasive breast cancers. METHODS: A retrospective study of patients with invasive carcinoma was conducted between 2017 and 2021. All patients underwent dynamic contrast-enhanced MRI and DWI using a 3-T system. For DWI, three b values (0, 200, and 1500 s/mm2) were used to derive the S-index. Three-dimensional ROIs were manually placed over the whole tumor on DWI. Mean and 85th percentile S-index values were compared to the IHC status, proliferation rate, and molecular subtypes of lesions. RESULTS: The study included 153 patients (mean age, 60 ± 13 years) with 160 invasive carcinomas. S-index values were significantly higher in estrogen receptor-positive (mean, p = .005; 85th percentile, p < .001) and progesterone receptor-positive (mean, p = .003; 85th percentile, p < .001) tumors, and significantly lower in human epidermal growth factor receptor 2 (HER2) - positive tumors (mean, p = .023; 85th percentile, p < .001). Mean and 85th percentile S-index values were significantly different among breast cancer subtypes (mean, p = .015; 85th percentile, p = .002), and the AUC of these values for the prediction of IHC status were 0.64 and 0.66 for HER2, and 0.70 and 0.74 for hormone receptors, respectively. CONCLUSIONS: The DWI S-index showed significantly higher values in invasive carcinomas with immunohistochemical status associated with good prognosis, suggesting its usefulness as a noninvasive imaging biomarker to estimate IHC status and orient treatment. KEY POINTS: • The signature index, an advanced diffusion MRI marker, showed good discrimination of immunohistochemical status in invasive breast carcinomas. • The signature index has the potential to differentiate noninvasively invasive breast carcinoma subtypes and appears as an imaging biomarker of prognostic factors and molecular phenotypes.

Ultrafast Dynamic Contrast-enhanced MRI of the Breast: How Is It Used?

Ultrafast dynamic contrast-enhanced (UF-DCE) MRI is a new approach to capture kinetic information in the very early post-contrast period with high temporal resolution while keeping reasonable spatial resolution. The detailed timing and shape of the upslope in the time-intensity curve are analyzed. New kinetic parameters obtained from UF-DCE MRI are useful in differentiating malignant from benign lesions and in evaluating prognostic markers of the breast cancers. Clinically, UF-DCE MRI contributes in identifying hypervascular lesions when the background parenchymal enhancement (BPE) is marked on conventional dynamic MRI. This review starts with the technical aspect of accelerated acquisition. Practical aspects of UF-DCE MRI include identification of target hypervascular lesions from marked BPE and diagnosis of malignant and benign lesions based on new kinetic parameters derived from UF-DCE MRI: maximum slope (MS), time to enhance (TTE), bolus arrival time (BAT), time interval between arterial and venous visualization (AVI), and empirical mathematical model (EMM). The parameters derived from UF-DCE MRI are compared in terms of their diagnostic performance and association with prognostic markers. Pitfalls of UF-DCE MRI in the clinical situation are also covered. Since UF-DCE MRI is an evolving technique, future prospects of UF-DCE MRI are discussed in detail by citing recent evidence. The topic covers prediction of treatment response, multiparametric approach using DWI-derived parameters, evaluation of tumor-related vessels, and application of artificial intelligence for UF-DCE MRI. Along with comprehensive literature review, illustrative clinical cases are used to understand the value of UF-DCE MRI.

Effects of gadobutrol on background parenchymal enhancement and differential diagnosis between benign and malignant lesions in dynamic magnetic resonance imaging of the breast.

BACKGROUND: The high concentration of gadolinium in gadobutrol, which is widely used in Japan, helps visualize signal enhancement of neoplastic lesions, however, there was concern that high T1 relaxivity could decrease the contrast between the lesion and the background mammary gland. We evaluate the effect of gadobutrol on background parenchymal enhancement (BPE) and differential diagnosis between benign and malignant lesions in dynamic MRI of the breast. METHODS: Ninety-nine patients were enrolled prospectively. Measurements of the following signal intensities (SIs) were obtained: breast tissue on a pre-contrast image (SIpre) and an early-phase image (SIearly); and the SIs of breast cancer on a pre-contrast image (SIpre-cancer) and an early-phase image (SIearly-cancer). We calculated the BPE ratio, i.e., (SIearly - SIpre)/SIpre and the cancer/BPE ratio, i.e., (SIearly-cancer - SIpre-cancer)/(SIearly on the affected side - SIpre on the affected side). These quantitative assessments were compared with the data from the recently published multicenter study (reference study without use of gadobutrol). In addition, two radiologists reinterpreted each of the MR images, and a third radiologist set the ROIs in the lesions and performed kinetic analysis as a Reader 3. RESULTS: While there was no significant difference in the SI of breast cancer in the premenopausal patients between the two studies, that in postmenopausal patients was significantly higher in the present study than in the reference study (p = 0.002). Although there was no significant difference in the cancer/BPE ratio in the postmenopausal patients between the two studies, the cancer/BPE ratio in the premenopausal patients was significantly higher in the reference study than in the present study (p = 0.028). For differentiation between benign and malignant masses, the mass margin was found to be the most important term (p < 0.001). According to the data of Reader 3, visual washout was observed in all 18 patients in whom the interpretation was changed from "plateau" to "washout". CONCLUSIONS: Gadobutrol may decrease the contrast between breast cancer and background parenchyma in premenopausal patients, and it may have a characteristic that "washout" does not easily occur, leading to "plateau" in patients with breast cancer.

Value of intra-tumor heterogeneity evaluated by diffusion-weighted MRI for predicting pathological stages and therapeutic responses to chemoradiotherapy in lower rectal cancer.

Aim: Diffusion-weighted MRI (DWI) has the potential to reveal intra-tumor structural heterogeneity consisting of stroma through an evaluation of uniformity on DWI. In present study, we examined the diagnostic value of intra-tumor heterogeneity evaluated by DWI in lower rectal cancer (LRC). Patients and Methods: A total of 172 LRC patients underwent radical surgery between 2009 and 2017. T1 tumors and cases without pre-operative MRI were excluded. Twenty-nine primary resection cases (PR) and 37 pre-operative chemoradiotherapy followed by radical surgery cases (pCRT) were targeted. Intra-tumor heterogeneity on DWI was quantified using a specific formula (HSD). Structural heterogeneity was objectively quantified by an image analysis of resected specimens using a digital microscope (HSP). The relationships between HSD and HSP, pathological factors, and tumor regression grades (TRG) of pCRT were evaluated. Results: The relationship between HSD and HSP was analyzed by a linear regression model in PR cases, revealing a positive correlation (R2=0.43). PR cases were divided into HSD-high and HSD-low according to the median. There were more pT3 or N(+) cases in HSD-high (p=0.038, 0.095). HSD before pCRT correlated with TRG (grade 1 versus 2/3) in pCRT cases (p=0.001). The diagnostic accuracy of HSD for predicting T and N stages and therapeutic grades was evaluated by cut-off values calculated using a ROC curve and revealed that each factor may be accurately diagnosed. Conclusion: Intra-tumor heterogeneity on DWI corresponded with stromal pathological heterogeneity. It is useful for predicting T3 or deeper tumor invasion, pathological N(+), and the therapeutic effects of pCRT.

Effects of different fat-suppression methods on T1 values in dynamic contrast-enhanced magnetic resonance imaging: a phantom study.

Dynamic contrast-enhanced MRI may yield variable longitudinal-relaxation time (T1) values depending on the precision of the fat-suppression (FS) technique. This study aimed to investigate the influences of FS methods on T1 value measurements on phantoms containing test tubes filled with mixtures of five volumes of fat, six amounts of contrast agent, and water. Volumetric interpolated images were obtained using several FS methods and flip angles. T1 maps were created based on the variable flip angle approach. The T1 values of water obtained by point-resolved single-voxel spectroscopy (SVS) were used as reference values. Notably, FS methods were shown to have substantial effects on the measurement of T1 values. Among the tested FS methods, the Dixon (water) method produced T1 values most similar to SVS, which can be considered as a reference value for clinical practice.

Adding a Model-free Diffusion MRI Marker to BI-RADS Assessment Improves Specificity for Diagnosing Breast Lesions.

Background The apparent diffusion coefficient (ADC) is a commonly used quantitative diffusion-weighted (DW) imaging marker in breast lesion assessment; however, reported ADC values to distinguish malignant and benign lesions show wide variability. Purpose To investigate the diagnostic performance of a tissue signature index (S-index) as a model-free diffusion marker to differentiate malignant and benign breast lesions. Materials and Methods This was a single-institution retrospective study of patients who underwent breast MRI from April 2017 to September 2018. Dynamic contrast-enhanced (DCE) MRI and DW imaging were performed with a 3-T MRI system. For DW imaging, three b values (0, 200, and 1500 sec/mm2) were used for Breast Imaging Reporting and Data Systems (BI-RADS) scoring and to calculate the S-index and a shifted ADC. The diagnostic performances of S-index, shifted ADC, and BI-RADS scoring were evaluated by using receiver operating coefficient analysis. Results The study involved 99 women (mean age, 54 years ± 14 [standard deviation]) with 69 malignant and 38 benign lesions. The S-index was higher for malignant lesions (mean, 75.9 ± 17.4) than for benign lesions (mean, 31.6 ± 21.0; P < .001). Overall diagnostic performance was identical for S-index and shifted ADC (area under the receiver operating characteristic curve [AUC], 0.95; 95% confidence interval [CI]: 0.91, 0.99) and slightly higher than for BI-RADS (AUC, 0.91; 95% CI: 0.87, 0.96; P = .22). The AUC of S-index combined with BI-RADS reached 0.98 (95% CI: 0.96, 1.00), higher than for BI-RADS alone (P < .001), yielding high sensitivity (65 of 69 [94%]; 95% CI: 85%, 98%) and specificity (36 of 38 [95%]; 95% CI: 81%, 99%). Significant differences were identified with the S-index for progesterone receptor and human epidermal growth factor receptor type 2 status (P = .003 and P < .001, respectively). Conclusion The signature index has the potential to enable classification of breast lesion types with high accuracy, especially in combination with dynamic contrast-enhanced MRI and correlates with histologic prognostic factors in invasive breast cancer. © RSNA, 2019 Online supplemental material is available for this article.

The split sign: The MRI equivalent of the bell clapper deformity.

METHODS:: The cases of eight patients who underwent MRI and surgery for acute scrotum between January 2010 and January 2017 were evaluated. We recorded whether hyperintense fluid on T2 weighted images existed between the posterior aspect of the epididymis and the scrotal wall ("split sign") and investigated if it correlated with BCD in surgical findings. RESULTS:: In one patient without hydrocele, readers were unable to evaluate the anatomy of the tunica vaginalis. Among seven patients with hydrocele, five had the split sign and all were surgically confirmed as BCD. In two patients with hydrocele but no split sign, one had normal scrotal anatomy and the other had a BCD with a necrotic testis adherent to the scrotal wall. CONCLUSION:: The split sign on MRI corresponded well to the lack of fixation of the epididymis to the scrotal wall and detected BCD with high sensitivity (5/6). ADVANCES IN KNOWLEDGE:: A hyperintense area on T2 weighted image between the posterior aspect of the epididymis and scrotal wall ("split sign") is a useful MRI finding for diagnosing BCD.

Diagnostic performance of initial enhancement analysis using ultra-fast dynamic contrast-enhanced MRI for breast lesions.

OBJECTIVES: To assess the diagnostic value and contribution to BI-RADS categorisation of initial enhancement on ultra-fast DCE-MRI for differentiating malignant and benign breast lesions. METHODS: The institutional review board approved this study, and written informed consent was obtained from each participant. Both ultra-fast DCE-MRI for initial enhancement analysis and conventional MRI were performed on 200 subjects with a total of 215 lesions (147 malignant and 68 benign). BI-RADS categorisation of enhancing lesions was performed using the conventional MRI. Two initial enhancement measures, time to enhancement (TTE) and maximum slope (MS), were derived from the ultra-fast DCE-MRI. Diagnostic performance and the additional diagnostic value of adding TTE and MS to BI-RADS were evaluated. RESULTS: Both TTE and MS showed significant differences between malignant and benign breast lesions in masses (TTE, p <.001; MS, p = .006) and non-mass enhancement (NME) (TTE, p <.001; MS, p <.001). For masses, the AUC of TTE+MS combined with BI-RADS (0.864) was better than BI-RADS alone (0.823, p = .065). For NME, the AUC of TTE+MS combined with BI-RADS (0.923) was significantly larger than BI-RADS alone (0.865, p = .036), and diagnostic specificity improved by 40.9% (p = .005), without a significant decrease in the sensitivity (p = .083). CONCLUSION: Initial enhancement analysis using ultra-fast DCE-MRI is especially useful for increasing the diagnostic performance of NME in breast MRI. KEY POINTS: • Ultra-fast dynamic MRI effectively differentiates benign from malignant breast lesions. • Ultra-fast dynamic MRI contributes to BI-RADS categorisation in non-mass enhancement. • Management of non-mass breast lesions becomes more appropriate.

Comparison of radiation dermatitis between hypofractionated and conventionally fractionated postoperative radiotherapy: objective, longitudinal assessment of skin color.

This study aimed to quantitatively compare radiation dermatitis due to hypofractionated (Hypo) and conventionally fractionated (Conv) external-beam radiotherapy in patients who underwent postoperative radiotherapy after breast-conserving surgery. Skin color changes, in terms of L* (brightness, white-black), a* (red-green), and b* (yellow-blue) values, due to external-beam radiotherapy were examined at alternate fractions using an objective method. Twenty-six patients were included in the Hypo group (42.56 Gy/16 fractions) and 46 in the Conv group (50 Gy/25 fractions). Radiotherapy decreased the L* value (darker) and increased the a* value (redder) gradually. These color alterations progressed linearly according to elapsed fractions and were similar between Hypo and Conv per fraction. The Hypo group showed significantly milder alterations in L* and a* values than the Conv group. The maximal dosage was significantly correlated to alterations in L* and a* values. Common Terminology Criteria for Adverse Events v4 assessment did not show a statistically significant difference between the Hypo (Grade 0:1:2 = 2:24:1) and Conv (1:39:6, p = 0.25) groups. The results of our objective analysis revealed that patients undergoing Hypo show milder color alteration than those undergoing Conv and that the maximal dosage is a useful predicator of color alteration.

Appropriate imaging utilization in Japan: a survey of accredited radiology training hospitals.

PURPOSE: To survey whether imaging is being performed appropriately in Japan, and to survey whether radiologists intervene to ensure imaging requests are appropriate. METHODS: An online survey was sent to radiologists at accredited radiology training hospitals. The survey included the radiologists' perspectives on whether imaging is performed appropriately at their institutions and whether they intervene if the indication for imaging is inappropriate/ambiguous. RESULTS: The response rate was 87.3% (165/189). We observed marked variability in the frequencies that imaging not recommended by the guidelines was performed among modalities and/or body parts; the responses "very frequently/frequently performed" were more common for breast cancer related imaging examinations and for head CT/MRI. The respondents frequently reported that inappropriate/ambiguous indications included requests to expand the craniocaudal range or to perform whole-body imaging. In 80% of the hospitals (132/165), radiologists contacted the physicians who requested unrecommended examinations; the number of CT and MRI examinations that full-time radiologists need to interpret in a half-day session was significantly smaller at these hospitals (median 18 vs 24, P = 0.032). CONCLUSION: We conducted a survey to investigate appropriate imaging utilization in Japan. At the hospitals with numerous examinations to interpret, full-time radiologists may find it difficult to ensure that examinations are ordered appropriately.

Clinical feasibility of simultaneous multi-slice imaging with blipped-CAIPI for diffusion-weighted imaging and diffusion-tensor imaging of the brain.

Background Simultaneous multi-slice (SMS) imaging is starting to be used in clinical situation, although evidence of clinical feasibility is scanty. Purpose To prospectively assess the clinical feasibility of SMS diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI) with blipped-controlled aliasing in parallel imaging for brain lesions. Material and Methods The institutional review board approved this study. This study included 156 hyperintense lesions on DWI from 32 patients. A slice acceleration factor of 2 was applied for SMS scans, which allowed shortening of the scan time by 41.3%. The signal-to-noise ratio (SNR) was calculated for brain tissue of a selected slice. The contrast-to-noise ratio (CNR), apparent diffusion coefficient (ADC), and fractional anisotropy (FA) were calculated in 36 hyperintense lesions with a diameter of three pixels or more. Visual assessment was performed for all 156 lesions. Tractography of the corticospinal tract of 29 patients was evaluated. The number of tracts and averaged tract length were used for quantitative analysis, and visual assessment was evaluated by grading. Results The SMS scan showed no bias and acceptable 95% limits of agreement compared to conventional scans in SNR, CNR, and ADC on Bland-Altman analyses. Only FA of the lesions was higher in the SMS scan by 9% ( P = 0.016), whereas FA of the surrounding tissues was similar. Quantitative analysis of tractography showed similar values. Visual assessment of DWI hyperintense lesions and tractography also resulted in comparable evaluation. Conclusion SMS imaging was clinically feasible for imaging quality and quantitative values compared with conventional DWI and DTI.

Reading efficiency can be improved by minor modification of assigned duties; a pilot study on a small team of general radiologists.

PURPOSE: To assess whether alterations in the type of duty assignment system can affect the reading efficiency and stress level of diagnostic radiologists. MATERIALS AND METHODS: Fourteen board-certified diagnostic radiologists were enrolled. We investigated three different reading systems for 1 week each. System 1 is our default, in which there are no assigned duties and everyone finishes when all cases are done. In system 2, two late shift readers are assigned every day, and, after everyone else leaves at a fixed time (5:30 p.m.), they take all remaining cases until they are finished. In system 3, a dedicated single reader is assigned to finish 30 cases, and everyone else will read all remaining cases. The total time required for reading and the number of cases read were recorded. In addition, participants completed two questionnaires regarding work-related stress. RESULTS: There was a trend toward shorter finishing time in system 2 and 3 compared to system 1 (P = 0.072 and 0.012). In terms of working stress, the subjective burden was lighter when systems 2 or 3 were employed. CONCLUSION: Minor modification of the duty assignment system has the potential to improve working efficiency and may reduce the work-related stress of diagnostic radiologists.

Breast Volume Measurement by Recycling the Data Obtained From 2 Routine Modalities, Mammography and Magnetic Resonance Imaging.

Objective: Preoperative prediction of breast volume is important in the planning of breast reconstructive surgery. In this study, we prospectively estimated the accuracy of measurement of breast volume using data from 2 routine modalities, mammography and magnetic resonance imaging, by comparison with volumes of mastectomy specimens. Methods: The subjects were 22 patients (24 breasts) who were scheduled to undergo total mastectomy for breast cancer. Preoperatively, magnetic resonance imaging volume measurement was performed using a medical imaging system and the mammographic volume was calculated using a previously proposed formula. Volumes of mastectomy specimens were measured intraoperatively using a method based on Archimedes' principle and Newton's third law. Results: The average breast volumes measured on magnetic resonance imaging and mammography were 318.47 ± 199.4 mL and 325.26 ± 217.36 mL, respectively. The correlation coefficients with mastectomy specimen volumes were 0.982 for magnetic resonance imaging and 0.911 for mammography. Conclusions: Breast volume measurement using magnetic resonance imaging was highly accurate but requires data analysis software. In contrast, breast volume measurement with mammography requires only a simple formula and is sufficiently accurate, although the accuracy was lower than that obtained with magnetic resonance imaging. These results indicate that mammography could be an alternative modality for breast volume measurement as a substitute for magnetic resonance imaging.

Docetaxel, cyclophosphamide, and trastuzumab as neoadjuvant chemotherapy for HER2-positive primary breast cancer.

BACKGROUND: The standard primary systemic therapy for human epidermal growth factor receptor 2-positive (HER2+) breast cancer is anthracyclines and/or taxanes combined with trastuzumab, which demonstrates a high pathological complete response (pCR). A pCR is a predictive marker of prognosis. However, results slightly differ, depending on the hormone receptor status. The efficacy and tolerability of docetaxel, cyclophosphamide, and trastuzumab (HER-TC) as neoadjuvant chemotherapy (NAC) remain unclear. We performed a prospective multicenter study of HER-TC NAC for HER2+ primary breast cancer. METHODS: Eligible patients had a clinical diagnosis of HER2+ invasive breast cancer greater than 1 cm but less than 7 cm and a tumor stage of N0 or N1. T hey were diagnosed between July 2011 and February 2014. For NAC, four cycles of HER-TC (6 mg/kg loading dose, 8 mg/kg, 75, and 600 mg/m2) were administered intravenously every 3 weeks. We investigated the pCR of the primary breast tumors. A pCR was defined as no histological evidence of invasive carcinoma or the appearance of only ductal carcinoma in situ. RESULTS: We enrolled 42 patients. The completion rate for four cycles of HER-TC was 97.6 % (41/42 patients). The overall pCR rate was 43.9 % (18/41 patients). The pCR rate for patients with the luminal HER2 subtype [estrogen receptor (ER)-positive+, HER2+] and the HER2-enriched subtype (ER-, HER2+) was 40.0 % (8/20 patients) and 47.6 % (10/21 patients), respectively. A pCR was achieved with nearly the same probability for each subtype. CONCLUSIONS: Four cycles of HER-TC may be a NAC option for HER2-positive breast cancer.