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.

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.

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.

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.

A case of testicular seminoma in persistent Mullerian duct syndrome with transverse testicular ectopia.

We present a rare case of testicular seminoma in persistent Mullerian duct syndrome (PMDS) with transverse testicular ectopia (TTE). A 42-year-old man noticed scrotal swelling a few weeks earlier and underwent magnetic resonance imaging (MRI) on suspicion of testicular tumor. MRI revealed a normal left testis on the left side of the left scrotum and a heterogeneous mass on the right side within the left scrotum. No right testis was found in the right scrotum. A blind-ending tubular structure with thickened wall showed a three-layer appearance on T2-weighted imaging and extended from the prostate through the left inguinal canal to the left scrotum. Findings during surgery suggested right testicular tumor associated with right TTE. The histopathological and immunohistochemical diagnoses of the testicular tumor and blind-ending tubular structure were seminoma and persistent Mullerian duct, respectively. Testicular tumor in PMDS with TTE is rare but may possess a characteristic appearance on imaging. Proper knowledge of these diseases will allow correct preoperative diagnosis.

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.

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.

Phosphorus starvation induces post-transcriptional CHS gene silencing in Petunia corolla.

KEY MESSAGE: The corolla of Petunia 'Magic Samba' exhibits unstable anthocyanin expression depending on its phosphorus content. Phosphorus deficiency enhanced post-transcriptional gene silencing of chalcone synthase - A in the corolla. Petunia (Petunia hybrida) 'Magic Samba' has unstable red-white bicolored corollas that respond to nutrient deficiency. We grew this cultivar hydroponically using solutions that lacked one or several nutrients to identify the specific nutrient related to anthocyanin expression in corolla. The white area of the corolla widened under phosphorus (P)-deficient conditions. When the P content of the corolla grown under P-deficient conditions dropped to <2,000 ppm, completely white corollas continued to develop in >40 corollas until the plants died. Other elemental deficiencies had no clear effects on anthocyanin suppression in the corolla. After phosphate was resupplied to the P-deficient plants, anthocyanin was restored in the corollas. The expression of chalcone synthase-A (CHS-A) was suppressed in the white area that widened under P-suppressed conditions, whereas the expression of several other genes related to anthocyanin biosynthesis was enhanced more in the white area than in the red area. Reddish leaves and sepals developed under the P-deficient condition, which is a typical P-deficiency symptom. Two genes related to anthocyanin biosynthesis were enhanced in the reddish organs. Small interfering RNA analysis of CHS-A showed that the suppression resulted from post-transcriptional gene silencing (PTGS). Thus, it was hypothesized that the enhancement of anthocyanin biosynthetic gene expression due to P-deficiency triggered PTGS of CHS-A, which resulted in white corolla development.

Melatonin-induced changes in the expression of thyroid hormone-converting enzymes in hypothalamus depend on the timing of melatonin injections and genetic background in mice.

Recent studies have identified TSHB, Dio2, and Dio3 as key genes for the photoperiodic regulation of gonads. In mammals, the expression of these genes is controlled by melatonin. Surprisingly, this effect of melatonin was shown to be conserved in several reproductively non-photoperiodic laboratory mouse strains that have thus become a valuable model to decipher the mechanisms through which melatonin controls the expression of TSHB, Dio2, and Dio3. In this study, we assessed the effects of intraperitoneal melatonin injections and of their timing on the expression of TSHB, TSHR, Dio2, and Dio3 in the hypothalamo-hypophysial systems of melatonin-proficient CBA/N and melatonin-deficient C57BL/6J mice kept under long-day conditions. In CBA/N mice, Dio3 expression was induced by a daily melatonin injection at ZT14 only, whereas in C57BL/6J mice, a daily melatonin injection induced Dio3 expression at all time points investigated (ZT8, 14, and 20) without changes in TSHB expression in both strains. Dio2 expression was suppressed by a daily melatonin injection only in C57BL/6J mice and only at ZT8. Effect of a daily melatonin injection on TSHR expression was strain- and region- specific. Melatonin levels elevated in plasma and hypothalamus after intraperitoneal injections of melatonin at ZT8 for 7days in C57BL/6J returned to basal levels within 1h after the final injection, while in CBA/N mice melatonin levels in hypothalamus remained high for at least 1h. These data suggest that Dio2 and Dio3 expression in the hypothalamus is differentially regulated by the timing of melatonin injections through strain-specific mechanisms.

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.

Photoperiod regulates dietary preferences and energy metabolism in young developing Fischer 344 rats but not in same-age Wistar rats.

The effects of photoperiod on dietary preference were examined using young growing Fischer 344 and Wistar rats, which are seasonal and nonseasonal breeders, respectively. Rats were provided a low-fat, high-carbohydrate diet (LFD: 66/10/24% energy as carbohydrate/fat/protein) and high-fat, low-carbohydrate diet (HFD: 21/55/24% energy as carbohydrate/fat/protein) simultaneously under long- (LD: 16 h light/day) and short-day (SD: 8 h light/day) conditions for 3 wk. Fischer 344 rats preferred the LFD to the HFD under the LD condition, whereas preference for both diets was equivalent under the SD condition. Consequently, their body weight and total energy intake exhibited 11-15 and 10-13% increases, respectively, under the LD condition. Calculation of energy intake from macronutrients revealed that rats under the LD condition consumed 20-24 and 9-13% higher energy of carbohydrates and proteins, respectively, than those under the SD condition. In contrast, Wistar rats preferred the LFD to the HFD irrespective of photoperiod and exhibited no photoperiodic changes in any parameters examined. Next, Fischer 344 rats were provided either the LFD or HFD for 3 wk under LD or SD conditions. Calorie intake was 10% higher in the rats fed the LFD than those fed the HFD under SD condition. However, rats under LD condition exhibited 5-10, 14, and 64% increases in body weight, epididymal fat mass, and plasma leptin levels, respectively, compared with those under the SD condition irrespective of dietary composition. In conclusion, photoperiod regulates feeding and energy metabolism in young growing Fischer 344 rats via the interactions with dietary macronutrient composition.

The role of breast MR imaging in pre-operative determination of invasive disease for ductal carcinoma in situ diagnosed by needle biopsy.

OBJECTIVES: To evaluate whether magnetic resonance (MR) imaging features can predict the presence of occult invasion in cases of biopsy-proven pure ductal carcinoma in situ (DCIS). METHODS: We retrospectively reviewed 92 biopsy-proven pure DCIS in 92 women who underwent MR imaging. The following MR imaging findings were compared between confirmed DCIS and invasive breast cancer (IBC): lesion size, type, morphological and kinetic assessments by ACR BI-RADS MRI, and findings of fat-suppressed T2-weighted (FS-T2W) imaging. RESULTS: Sixty-eight of 92 (74%) were non-mass-like enhancements (NMLE) and 24 were mass lesions on MR imaging. Twenty-one of 68 (31%) NMLE and 13 of 24 (54%) mass lesions were confirmed as IBC. In NMLE lesions, large lesions (P = 0.007) and higher signal intensities (SI) on FS-T2W images (P = 0.032) were significantly associated with IBC. Lesion size remained a significant independent predictor of invasion in multivariate analysis (P = 0.032), and combined with FS-T2W SIs showed slightly higher observer performances (area under the curve, AUC, 0.71) than lesion size alone (AUC 0.68). There were no useful findings that enabled the differentiation of mass-type lesions. CONCLUSIONS: Breast MR imaging is potentially useful to predict the presence of occult invasion in biopsy-proven DCIS with NMLE. KEY POINTS: MR mammography permits more precise lesion assessment including ductal carcinoma in situ A correct diagnosis of occult invasion before treatment is important for clinicians This study showed the potential of MR mammography to diagnose occult invasion Treatment and/or aggressive biopsy can be given with greater confidence MR mammography can lead to more appropriate management of patients.

Myoid hamartoma of the breast that proved difficult to diagnose: a case report.

Myoid hamartomas of the breast are extremely rare breast lesions, with a poorly understood pathogenesis. We describe the case of a 38-year-old premenopausal woman who presenting with a mass in the left breast. Mammography revealed an oval mass that was partly indistinct, and ultrasonography showed a hypoechoic mass with a slightly irregular margin. Bilateral breast dynamic magnetic resonance imaging was performed for a more detailed evaluation. The images showed rapid initial enhancement and a microlobulated margin. Because the suspicion of malignancy was strong at that time, core needle biopsy was performed. Histologically, the tumor was identified as fibroadenoma. A case of myoid hamartoma of the breast that proved difficult to diagnose is reported, and discussed with reference to the literature.

[A case of effective lapatinib/capecitabine therapy for HER2-positive breast cancer with multiple brain metastases].

A 63-year-old woman was suffering from HER2-positive and hormone receptor-negative breast cancer with bone metastasis. She received 16 cycles of paclitaxel(PTX 80mg/m2)plus trastuzumab(TRA 2mg/kg)on a 7-day cycle, and zoledronic acid(ZOL 4mg/body every 28 days), resulting in a near clinical complete response(cCR). Two years later, the patient complained of dizziness and nausea, and magnetic resonance imaging revealed multiple brain metastases. The prior treatments with PTX and TRA were changed to lapatinib(LAP)(orally at 1, 250mg/day every day)and capecitabine(CAP)(orally at 2, 000mg/m2 every day for 2 weeks, followed by a 1-week rest interval as 1 cycle)because of the multiple brain metastases. After 4 cycles of treatment, the number of brain lesions and the tumor sizes were significantly reduced. After 7 cycles, however, magnetic resonance imaging revealed the deterioration of some brain lesions. After whole-brain irradiation(30 Gy in 10 fractions)was added to the treatment, the outcome was near cCR. In conclusion, combination therapy of Lap and Cap may be an effective treatment option for brain metastasis of HER2-positive breast cancer.

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.

[A case of effective combination therapy with docetaxel, cyclophosphamide and trastuzumab as primary systemic therapy for locally advanced HER2-positive breast cancer].

We experienced a case of locally advanced breast cancer achieving a significant improvement by using a combination of docetaxel(DOC), cyclophosphamide(CPA)and trastuzumab as a primary systemic therapy.The patient was a 54-year-old woman suffering from a right breast mass, who was referred to our hospital and diagnosed with HER2-positive breast cancer with subclavicular lymph nodes metastases.The combination therapy of DOC(75 mg/m / 2), CPA(600 mg/m2)and trastuzumab(loading dose 8 mg/kg, then 6 mg/kg)for 6 courses at q3 week intervals, was started as the primary systemic therapy. After 6 courses of treatment, a right modified radical mastectomy was performed.There were a little breast cancer cells in the breast, and no axillary lymph node metastases.The combination chemotherapeutic regime with DOC, CPA and trastuzumab seems to be useful for treatment of HER2-positive breast cancer.

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.

Optimum b value for resolving crossing fibers: a study with standard clinical b value using 1.5-T MR.

INTRODUCTION: We sought to investigate the optimum b value for resolving crossing fiber using high-angular resolution diffusion imaging (HARDI)-based multi-tensor tractography. The study tested the standard b values that are commonly used in the routine clinical setting. METHODS: Ten normal volunteers (five men and five women) with a mean age of 26.3 years (range, 22-32 years) were scanned using a 1.5-T clinical magnetic resonance unit. Single-shot echo-planar imaging was used for diffusion-weighted imaging with a diffusion-sensitizing gradient in 32 orientations. The b values of 700, 1,400, 2,100, and 2,800 s/m(2) were used. Data postprocessing was performed using multi-tensor methods. The depiction of the optic nerves, optic tracts, and decussation of superior cerebellar peduncles were assessed. RESULTS: The depictions of the nerve fibers were independent of the b values tested. CONCLUSION: The depiction of crossing fibers by HARDI-based multi-tensor tractography is not substantially influenced by b values ranging from 700 to 2,800 s/m(2). Thus, the optimum b value within this range may be the lowest one considering the higher signal to noise ratio.