A multiparametric approach to predict triple-negative breast cancer including parameters derived from ultrafast dynamic contrast-enhanced MRI.

OBJECTIVE: Triple-negative breast cancer (TNBC) is a highly proliferative breast cancer subtype. We aimed to identify TNBC among invasive cancers presenting as masses using maximum slope (MS) and time to enhancement (TTE) measured on ultrafast (UF) DCE-MRI, ADC measured on DWI, and rim enhancement on UF DCE-MRI and early-phase DCE-MRI. METHODS: This retrospective single-center study, between December 2015 and May 2020, included patients with breast cancer presenting as masses. Early-phase DCE-MRI was performed immediately after UF DCE-MRI. Interrater agreements were evaluated using the intraclass correlation coefficient (ICC) and Cohen's kappa. Univariate and multivariate logistic regression analyses of the MRI parameters, lesion size, and patient age were performed to predict TNBC and create a prediction model. The programmed death-ligand 1 (PD-L1) expression statuses of the patients with TNBCs were also evaluated. RESULTS: In total, 187 women (mean age, 58 years ± 12.9 [standard deviation]) with 191 lesions (33 TNBCs) were evaluated. The ICC for MS, TTE, ADC, and lesion size were 0.95, 0.97, 0.83, and 0.99, respectively. The kappa values of rim enhancements on UF and early-phase DCE-MRI were 0.88 and 0.84, respectively. MS on UF DCE-MRI and rim enhancement on early-phase DCE-MRI remained significant parameters after multivariate analyses. The prediction model created using these significant parameters yielded an area under the curve of 0.74 (95% CI, 0.65, 0.84). The PD-L1-expressing TNBCs tended to have higher rim enhancement rates than the non-PD-L1-expressing TNBCs. CONCLUSION: A multiparametric model using UF and early-phase DCE-MRI parameters may be a potential imaging biomarker to identify TNBCs. CLINICAL RELEVANCE STATEMENT: Prediction of TNBC or non-TNBC at an early point of diagnosis is crucial for appropriate management. This study offers the potential of UF and early-phase DCE-MRI to offer a solution to this clinical issue. KEY POINTS: • It is crucial to predict TNBC at an early clinical period. • Parameters on UF DCE-MRI and early-phase conventional DCE-MRI help in predicting TNBC. • Prediction of TNBC by MRI may be useful in determining appropriate clinical management.

Comparison of Ultrafast Dynamic Contrast-Enhanced (DCE) MRI with Conventional DCE MRI in the Morphological Assessment of Malignant Breast Lesions.

Ultrafast (UF) dynamic contrast-enhanced (DCE)-MRI offers the potential for a faster and, therefore, less expensive examination of breast lesions; however, there are no reports that have evaluated whether UF DCE-MRI can be used the same as conventional DCE-MRI in the reading of morphological information. This study evaluated the agreement in morphological information obtained from malignant breast mass lesions between UF DCE-MRI and conventional DCE-MRI. UF DCE-MRI data were obtained over the first 60 s post-contrast injection, followed by the conventional DCE images. Two readers evaluated the size and morphology of the lesions in the final phase of the UF DCE-MRI and the early phase of the conventional DCE-MRI. Inter-method agreement in morphological information was evaluated for the two readers using the intraclass correlation coefficient for size, and the kappa statistics for the morphological descriptors. Differences in the proportion of each descriptor were examined using Fisher's test of independence. Most inter-method agreements were higher than substantial. UF DCE-MRI showed a circumscribed margin and homogeneous enhancement more often than conventional imaging. However, the percentages of readings showing the same morphology assessment between the UF DCE-MRI and conventional DCE-MRI were 71.2% (136/191) for Reader 1 and 69.1% (132/191) for Reader 2. We conclude that UF DCE-MRI may replace conventional DCE-MRI to evaluate the morphological information of malignant breast mass lesions.

Evaluation of breast lesions based on modified BI-RADS using high-resolution readout-segmented diffusion-weighted echo-planar imaging and T2/T1-weighted image.

PURPOSE: To evaluate the diagnostic performance of a non-contrast magnetic resonance imaging (MRI) protocol combining high-resolution diffusion-weighted images (HR-DWI) using readout-segmented echo planar imaging, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI), using our modified Breast Imaging-Reporting and Data System (modified BI-RADS). METHODS: Two experienced radiologists, blinded to the final pathological diagnosis, categorized a total of 108 breast lesions (61 malignant and 47 benign) acquired with the above protocol using the modified BI-RADS with a diagnostic decision tree. The decision tree included subcategories of category 4, as in mammography (categories 2, 3, 4A, 4B, 4C, and 5). These results were compared with the pathological diagnoses. RESULTS: The area under the ROC curve (AUC) was 0.89 (95% confidence interval [CI]: 0.83-0.95) for reader 1, and 0.89 (95% CI: 0.82-0.96) for reader 2. When categories 4C and above were classified as malignant, the sensitivity, specificity, and accuracy were 73.8%, 93.6%, and 82.4%, for reader 1; and 82.0%, 89.4%, and 85.2% for reader 2, respectively. CONCLUSION: Our results suggest that using HR-DWI, T1WI/T2WI analyzed with a modified BI-RADS and a decision tree showed promising diagnostic performance in breast lesions, and is worthy of further study.

Biomarkers Predictive of Distant Disease-free Survival Derived from Diffusion-weighted Imaging of Breast Cancer.

PURPOSE: To investigate whether intravoxel incoherent motion (IVIM) and/or non-Gaussian diffusion parameters are associated with distant disease-free survival (DDFS) in patients with invasive breast cancer. METHODS: From May 2013 to March 2015, 101 patients (mean age 60.0, range 28-88) with invasive breast cancer were evaluated prospectively. IVIM parameters (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion parameters (theoretical apparent diffusion coefficient [ADC] at a b value of 0 s/mm2 [ADC0] and kurtosis [K]) were estimated using a diffusion-weighted imaging series of 16 b values up to 2500 s/mm2. Shifted ADC values (sADC200-1500) and standard ADC values (ADC0-800) were also calculated. The Kaplan-Meier method was used to generate survival analyses for DDFS, which were compared using the log-rank test. Univariable Cox proportional hazards models were used to assess any associations between each parameter and distant metastasis-free survival. RESULTS: The median observation period was 80 months (range, 35-92 months). Among the 101 patients, 12 (11.9%) developed distant metastasis, with a median time to metastasis of 79 months (range, 10-92 months). Kaplan-Meier analysis showed that DDFS was significantly shorter in patients with K > 0.98 than in those with K ≤ 0.98 (P = 0.04). Cox regression analysis showed a marginal statistical association between K and distant metastasis-free survival (P = 0.05). CONCLUSION: Non-Gaussian diffusion may be associated with prognosis in invasive breast cancer. A higher K may be a marker to help identify patients at an elevated risk of distant metastasis, which could guide subsequent treatment.

Evaluation of pathological complete response after neoadjuvant systemic treatment of invasive breast cancer using diffusion-weighted imaging compared with dynamic contrast-enhanced based kinetic analysis.

PURPOSE: This study compared the performance of diffusion-weighted imaging (DWI) to dynamic contrast-enhanced (DCE)-MRI for diagnosing pathological complete response (pCR) before surgery. METHOD: Overall, 133 lesions from 133 patients who underwent pre-surgical MRI evaluation after neoadjuvant systemic treatment were included. Two readers blinded to the pathological diagnosis evaluated the images. MR images were obtained using a routine protocol sequence that included DWI and DCE-MRI. DWI of the target lesion was scored using a three-point scale. Kinetic patterns of lesions on DCE-MRI were scored using a four-point scale. The capacities of DWI and kinetic parameters for discriminating pCR and non-pCR were assessed via receiver operating characteristic (ROC) analysis. RESULTS: For DWI scores, ROC analysis showed areas under the ROC curve (AUCs) of 0.84 (95% confidence interval: 0.77-0.90) and 0.85 (0.77-0.90) for readers 1 and 2, respectively; corresponding AUCs of kinetic scores were 0.89 (0.82-0.94) and 0.88 (0.81-0.93). Among the triple-negative subtype, the AUCs of DWI scores were 0.84 (0.70-0.93) and 0.88 (0.75-0.96) for readers 1 and 2, respectively; corresponding AUCs of kinetic scores were 0.94 (0.83-0.99) and 0.93 (0.82-0.99). Among the luminal subtype, the AUCs of DWI scores were 0.85 (0.71-0.94) and 0.82 (0.68-0.92) for readers 1 and 2, respectively; corresponding AUCs of kinetic scores were 0.82 (0.68-0.92) and 0.72 (0.56-0.85). CONCLUSIONS: Our DWI-based visual score and kinetic score showed similar diagnostic performances. Both DWI and kinetic scores tended to perform better in predicting pCR for the triple-negative subtype.

Visual Evaluation of Ultrafast MRI in the Assessment of Residual Breast Cancer after Neoadjuvant Systemic Therapy: A Preliminary Study Association with Subtype.

The purpose of this study was to investigate the diagnostic performance of ultrafast DCE (UF-DCE) MRI after the completion of neoadjuvant systemic therapy (NST) in breast cancer. In this study, MR examinations of 55 post-NST breast cancers were retrospectively analyzed. Residual tumor sizes were measured in the 20th phase of UF-DCE MRI, early and delayed phases of conventional DCE MRI, and high spatial-resolution CE MRI (UF, early, delayed, and HR, respectively). The diagnostic performance for the detection of residual invasive cancer was calculated by ROC analysis. The size difference between MRI and pathological findings was analyzed using the Wilcoxon signed-rank test with the Bonferroni correction. The overall AUC was highest for UF (0.86 and 0.88 for readers 1 and 2, respectively). The difference in imaging and pathological sizes for UF (5.7 ± 8.2 mm) was significantly smaller than those for early, delayed, and HR (p < 0.01). For luminal subtype breast cancer, the size difference was significantly smaller for UF and early than for delayed (p < 0.01). UF-DCE MRI demonstrated higher AUC and specificity for the more accurate detection of residual cancer and the visualization of tumor extent than conventional DCE MRI.

The Rate of Apparent Diffusion Coefficient Change With Diffusion Time on Breast Diffusion-Weighted Imaging Depends on Breast Tumor Types and Molecular Prognostic Biomarker Expression.

INTRODUCTION: The aim of this study was to investigate the variation of apparent diffusion coefficient (ADC) values with diffusion time according to breast tumor type and prognostic biomarkers expression. MATERIALS AND METHODS: A total of 201 patients with known or suspected breast tumors were prospectively enrolled in this study, and 132 breast tumors (86 malignant and 46 benign) were analyzed. Diffusion-weighted imaging scans with 2 diffusion times were acquired on a clinical 3-T magnetic resonance imaging scanner using oscillating and pulsed diffusion-encoding gradients (effective diffusion times, 4.7 and 96.6 milliseconds) and b values of 0 and 700 s/mm2. Diagnostic performances to differentiate malignant and benign breast tumors for ADC values at short and long diffusion times (ADCshort and ADClong), ΔADC (the rate of change in ADC values with diffusion time), ADC0-1000 (ADC value from a standard protocol), and standard reading including dynamic contrast-enhanced magnetic resonance imaging (BI-RADS) were investigated. The correlations of ADCshort, ADClong, and ΔADC values with hormone receptor expression and breast cancer subtypes were also analyzed. RESULTS: The ADC values were lower, and ΔADC was higher in malignant tumors compared with benign tumors. The specificity of ADC values at all diffusion times and ΔADC values for differentiating malignant and benign breast tumors was superior to that of BI-RADS (87.0%-95.7% vs 73.9%), whereas the sensitivity was inferior (87.2%-90.7% vs 100%). Lower ADCshort and ADC0-1000 in ER-positive compared with ER-negative cancers (false discovery rate [FDR]-adjusted P = 0.037 and 0.018, respectively) and lower ADCshort, ADClong, and ADC0-1000 in progesterone receptor-positive compared with progesterone receptor-negative cancers (FDR-adjusted P = 0.037, 0.036, and 0.018, respectively) were found. Ki-67-positive cancers had larger ΔADCs than Ki-67-negative cancers (FDR-adjusted P = 0.018). CONCLUSIONS: The ADC values vary with different diffusion time and vary in correlation with molecular biomarkers, especially Ki-67. Those results suggest that the diffusion time, which should be reported, might be a useful parameter to consider for breast cancer management.

Subcategory classifications of Breast Imaging and Data System (BI-RADS) category 4 lesions on MRI.

PURPOSE: Category 4 in BI-RADS for magnetic resonance imaging (MRI) has a wide range of probabilities of malignancy, extending from > 2 to < 95%. We classified category 4 lesions into three subcategories and analyzed the positive predictive value (PPV) of malignancy in a tertiary hospital. MATERIALS AND METHODS: This retrospective study included 346 breast MRIs with 434 category 2-5 lesions. All enhancing lesions were classified as category 2 (0% probability of malignancy), 3 (> 0%, ≤ 2%), 4 (> 2%, < 95%) and 5 (≥ 95%); category 4 lesions were further subcategorized into 4A (> 2%, ≤ 10%), 4B (> 10%, ≤ 50%) and 4C (> 50%, < 95%) at the time of diagnosis. Radiological and pathological reports were retrospectively analyzed, and the PPVs were calculated. RESULTS: We included 149 malignant and 285 benign lesions. The PPVs of subcategories 4A, 4B and 4C were 1.8%, 11.8% and 67.5%, respectively. The PPVs were higher for lesions coexisting with category 5 or 6 lesions compared with those for isolated lesions. CONCLUSION: Category 4 lesions can be classified into three subcategories depending on the likelihood of malignancy. Lesions coexisting with category 5 or 6 lesions are more likely to be malignant.

Evaluation of Malignant Breast Lesions Using High-resolution Readout-segmented Diffusion-weighted Echo-planar Imaging: Comparison with Pathology.

PURPOSE: We aimed to investigate the performance of high resolution-diffusion-weighted imaging (HR-DWI) using readout-segmented echo-planar imaging in visualizing malignant breast lesions and evaluating their extent, using pathology as a reference. METHODS: This retrospective study included patients who underwent HR-DWI with surgically confirmed malignant breast lesions. Two radiologists blinded to the final diagnosis evaluated HR-DWI independently and identified the lesions, measuring their maximum diameters. Another radiologist confirmed if those lesions were identical to the pathology. The maximum diameters of the lesions between HR-DWI and pathology were compared, and their correlations were calculated using Spearman's correlation coefficient. Apparent diffusion coefficient (ADC) values of the lesions were measured. RESULTS: Ninety-five mass/64 non-mass lesions were pathologically confirmed in 104 females. Both radiologists detected the same 93 mass lesions (97.9%). Spearman's correlation coefficient for mass lesions were 0.89 and 0.90 (P < 0.0001 and 0001) for the two radiologists, respectively. The size differences within 10 mm were 90.3% (84/93) and 94.6% (88/93) respectively. One radiologist detected 35 non-mass lesions (54.7%) and another radiologist detected 32 non-mass lesions (50.0%), of which 28 lesions were confirmed as identical. Spearman's correlation coefficient for non-mass lesions were 0.59 and 0.22 (P = 0.0002 and 0.22), respectively. The mean ADC value of mass lesions and non-mass lesions were 0.80 and 0.89 × 10-3 mm2/s, respectively. CONCLUSION: Using HR-DWI, malignant mass lesions were depicted with excellent agreement with the pathological evaluation. Approximately half of the non-mass lesions could not be identified, suggesting a current limitation of HR-DWI.

Background parenchymal enhancement and its effect on lesion detectability in ultrafast dynamic contrast-enhanced MRI.

PURPOSE: Background parenchymal enhancement (BPE) often affects interpretation of dynamic contrast-enhanced (DCE) MRI. There is limited evidence that reduced BPE is a feature of ultrafast DCE (UF-DCE) MRI. We aimed to evaluate the effect of BPE levels on lesion detectability on UF-DCE MRI in comparison with conventional DCE MRI. METHOD: MRIs of 70 patients with histologically proven breast lesions were retrospectively evaluated. The total number of analyzed lesions was 84 (56 malignant and 28 benign). Using 3 T MRI, 20 phases of UF-DCE MRI based on the three-dimensional gradient-echo VIBE sequence combined with a compressed sensing reconstruction were acquired followed by conventional DCE MRI. Three maximum intensity projection (MIP) images were generated from the 12th phase, the 20th phase of UF-DCE MRI and the initial phase of conventional DCE MRI. Two radiologists independently evaluated the degree of BPE and lesion detectability of the three MIP images for each breast with histologically confirmed lesions. The degree of BPE was scored on a four-point scale and lesion detectability (conspicuity and confidence levels) was scored on a three-point scale. Data were analyzed using the Wilcoxon signed-rank test with Bonferroni correction. RESULTS: BPE was lower on UF-DCE MRI than on conventional DCE MRI. Lesion detectability was higher on UF-DCE MRI among patients with higher BPE on conventional DCE MRI or premenopausal women. CONCLUSIONS: Images with lower BPE can be achieved using UF-DCE MRI and may be advantageous when assessing breast lesions among patients with higher BPE or premenopausal women.

A multiparametric approach to diagnosing breast lesions using diffusion-weighted imaging and ultrafast dynamic contrast-enhanced MRI.

PURPOSE: To evaluate the diagnostic performance of a multiparametric approach to breast lesions including apparent diffusion coefficient (ADC) from diffusion-weighted images (DWI), maximum slope (MS) from ultrafast dynamic contrast enhanced (UF-DCE) MRI, lesion size, and patient's age. MATERIALS AND METHODS: In total, 96 lesions (73 malignant, 23 benign) were evaluated. UF-DCE MRI was acquired using a prototype 3D-gradient-echo volumetric interpolated breath-hold examination (VIBE) with compressed sensing. Images were obtained up to 1 min after gadolinium injection. MS was calculated as the percentage relative enhancement/s. An ADC map was automatically generated from DWI at b = 0 and b = 1000 s/mm2. MS and ADC values were measured by two radiologists independently. Interrater agreement was evaluated using intraclass correlation coefficients. Univariate and multivariate logistic regression analyses were performed using MS, ADC, lesion size, and the patient's age. The parameters of the prediction model were generated from the results of the multivariate logistic regression analysis. Area under the curve (AUC) was used to compare diagnostic performance of the prediction model and each parameter. RESULTS: Interrater agreements on MS and ADC were excellent (ICC 0.99 and 0.88, respectively). MS, ADC, and patient's age remained as significant parameters after univariate and multivariate logistic regression analysis. The prediction model using these significant parameters yielded an AUC of 0.90, significantly higher than that of MS (AUC 0.74, p = 0.01). The AUCs of ADC, MS, patient's age were 0.87, 0.74 and 0.73, respectively. CONCLUSIONS: A multiparametric model using ADC from DWI, MS from UF-DCE MRI, and patient's age showed excellent diagnostic performance, with greater contribution of ADC. Combining DWI and UF-DCE MRI might reduce scanning time while preserving diagnostic performance.

The comparison of high-resolution diffusion weighted imaging (DWI) with high-resolution contrast-enhanced MRI in the evaluation of breast cancers.

PURPOSE: We sought to investigate the performance of high resolution (HR) diffusion-weighted imaging (DWI) using readout-segmented echo-planar imaging (rs-EPI), compared with high-resolution contrast-enhanced MRI (HR CE-MRI) in terms of morphological accuracy, on the basis of the Breast Imaging and Reporting and Data System (BI-RADS) MRI descriptors and lesion size. METHODS: This retrospective study included the image data of 94 patients with surgically confirmed malignant breast lesions who had undergone high resolution diffusion-weighted imaging (HR-DWI) and HR CE-MRI. Two radiologists blinded to the final diagnosis independently identified the lesions on HR-DWI, described the morphology of the lesions according to BI-RADS descriptors, and measured lesion size. HR CE-MRI was subsequently evaluated using the same procedure. The inter-method agreement of the morphology was assessed using kappa statistics. Correlation on size was also assessed. RESULTS: Reader A detected 79 mass lesions and 37 non-mass lesions on HR-DWI and HR CE-MRI. Reader B detected 81 mass lesions and 33 non-mass lesions on HR-DWI and HR CE-MRI. Very high agreement (kappa = 0.81-0.89, p < .05) was observed in the shape and margin assessment of mass lesions, where agreement on internal enhancement/signals was moderate to substantial (kappa = 0.43-0.61, p < .05). Disagreement was mostly seen in the evaluation of rim enhancement. High agreement was observed for non-mass lesion distribution (kappa = 0.76-0.84, p < .05), and agreement on internal enhancement/signals was moderate to fair (kappa = 0.34-0.49, p < .05). Agreement among heterogeneous, clumped, and clustered-ring patterns was variable. Size assessment showed very strong correlation both in mass (Spearman's rho = 0.90-0.96, p < .0001) and non-mass lesions (Spearman's rho = 0.86, p < .0001). CONCLUSIONS: The findings in morphology and lesion extent showed high agreement between HR-DWI and HR CE-MRI for malignant breast lesions. These results imply the potential of applying HR-DWI for evaluation of malignant breast lesions using BI-RADS MRI.

Myofibroblast distribution is associated with invasive growth types of colorectal cancer.

Both the invasive growth types of colorectal cancer (CRC) and the number of myofibroblasts have been associated with histopathological factors such as lymph node and liver metastasis, and local recurrence. However, there are few studies, that have assessed the association between invasive growth type and myofibroblast distribution in CRC. We aimed to evaluate the relationship between the clinicopathological factors of CRC and two invasive growth types, the expanding and infiltrating types. We categorized 150 cases of pT3 CRC into the expanding and infiltrating types and measured the myofibroblast density of three histological layers: the submucosa (SM), the muscularis propria (MP) and the subserosa (SS). We compared these two invasive growth types and analyzed the relationship between clinicopathological factors and myofibroblast density. Myofibroblast density was significantly higher in the infiltrating type than that in the expanding type (P<0.05). In the lymph node metastasis-positive group of the infiltrating type, myofibroblast density in MP was significantly higher than that in the lymph node metastasis-negative group (P<0.001). In the infiltrating type, the group with the higher level of lymphatic invasion had a significantly higher density of myofibroblasts in the MP than the group with the lower level of lymphatic invasion (P<0.01). These results suggest that myofibroblasts participate more in the infiltrating type compared with the expanding type of CRC. It would appear that myofibroblasts present in the MP play an important role in the malignant potential of the infiltrating type compared to the expanding type.

Myofibroblasts of the muscle layer stimulate the malignant potential of colorectal cancer.

Myofibroblasts of colorectal cancer (CRC) have been associated with histopathological factors such as lymph node metastasis, liver metastasis and local recurrence. However, few studies have assessed the association between these malignant potentials and the myofibroblast distribution in CRC. We aimed to evaluate the relationship between clinical factors and myofibroblast distribution around CRC invasive lesions. The study included 121 cases of pT3 CRC that were diagnosed at stage II or III. Myofibroblast density of the following three histological layers was measured: the submucosa (SM), muscularis propria (MP) and subserosa (SS). We analyzed the relationship between the clinicopathological factors and myofibroblast density by studying the histopathological features of the three layers. The myofibroblast density of the MP layer was significantly higher in the groups with high-frequency lymphatic and venous invasion than the groups with low-frequency lymphatic (P<0.001) and venous (P<0.01) invasion, respectively. In the positive lymph node metastasis group, the myofibroblast density at the MP layer was significantly higher than that in the negative lymph node metastasis group (P<0.001). The high myofibroblast density group at the MP layer was significantly associated with poor overall survival (P<0.003). Our study indicated that myofibroblasts are a type of cancer-associated fibroblasts and that the myofibroblast distribution contributes to the malignant potential of CRC. Furthermore, we demonstrated that myofibroblasts present at the MP layer play an important role in the malignant potential and poor prognosis of patients with CRC.

Clinicopathological significance of gastric poorly differentiated medullary carcinoma.

Poorly differentiated gastric adenocarcinoma of solid type is known to show a clinicopathological diversity, but its morphological characteristics have rarely been investigated. In this study, we defined poorly differentiated medullary carcinoma indicating the following three characteristics: (i) more than 90% of the entire tumor were composed of poorly differentiated adenocarcinoma in a medullary growth, (ii) the tumor exhibited an expansive growth at the tumor margin, and (iii) special types such as an α-fetoprotein-producing carcinoma, neuroendocrine carcinoma, and carcinoma with lymphoid stroma were excluded. Based on the definition, we subclassified the poorly differentiated gastric adenocarcinoma of solid type into the two groups: medullary carcinoma and non-medullary carcinoma, and clinicopathologically analyzed 23 cases of medullary carcinomas and 38 cases of non-medullary carcinomas. The medullary carcinomas less frequently displayed lymphatic invasion, venous invasion, and lymph node metastasis, compared with the non-medullary carcinoma (P < 0.001, P = 0.002, and P < 0.001, respectively). The patients with medullary carcinomas significantly showed better disease-free survival (P = 0.017). This is the first study to demonstrate that poorly differentiated adenocarcinoma of solid type can be subclassified into tumors with low and high malignant potentials. Gastric poorly differentiated medullary carcinoma is considered to be a novel histological type predicting good patients' prognosis.

A new histological therapeutic classification system to predict eradicated and residual lymph nodes in breast cancer after neoadjuvant chemotherapy.

The indication for neoadjuvant chemotherapy (NAC) has recently broadened to include its use in the treatment of initial stage breast cancer. Axillary lymph node metastasis after NAC in breast cancer is a poor prognostic factor. Thus, the prediction of lymph node metastasis is important to estimate the prognosis of breast cancer patients after NAC. Therefore, we focused on residual carcinoma patterns of primary breast tumors after NAC and examined the correlation between the patterns and lymph node metastasis. In this study, we examined 50 breast cancer specimens and associated dissected lymph nodes after NAC. We divided 40 cases into an eradicated lymph node group and a residual lymph node group to analyze residual carcinoma patterns of primary breast tumors. Residual carcinoma patterns were classified according to the cell density of carcinoma cells: dense, focal/nested and sporadic/in-situ. There were significant differences in residual carcinoma patterns (P<0.01) among the three pattern groups. There was a high incidence of dense patterns in the residual lymph node group and a high incidence of sporadic/in-situ patterns in the eradicated lymph node group. Analysis of residual carcinoma patterns of primary breast tumors and clinicopathological factors demonstrated that there were significant differences in tumor reduced ratio on CT (P<0.001), primary tumor area before NAC (P<0.01), primary tumor area after NAC (P<0.00001), intrinsic subtype (P<0.01), Ki-67 labeling index (P<0.01), histological grade (P<0.05) and mitotic count (P<0.01) between the dense and non-dense groups. Therefore, our results suggest that the residual carcinoma pattern is useful for predicting eradicated or residual lymph nodes and the malignant potential in breast cancer after NAC.

Disinfective process of strongly acidic electrolyzed product of sodium chloride solution against Mycobacteria.

Electrolyzed acid water (EAW) has been studied for its disinfective potential against pathogenic microbes; however, the bactericidal process against Mycobacteria has not been clearly presented. In this study, to clarify the disinfective process against Mycobacteria, EAW-treated bacteria were examined against laboratory strains of Mycobacterium bovis (M. bovis), Mycobacterium smegmatis (M. smegmatis), and Mycobacterium terrae (M. terrae) by recovery culture and observation of morphology, enzymatic assay, and the detection of DNA. All experiments were performed with the use of EAW containing 30 ppm free chlorine that kills Mycobacteria, including three pathogenic clinical isolates of Mycobacterium tuberculosis (M. tuberculosis) and six isolates of other Mycobacteria, within 5 min. In morphology, the bacterial surface became rough, and a longitudinal concavity-like structure appeared. The intrabacterial enzyme of EAW-contacted bacteria was inactivated, but chromosomal DNA was not totally denatured. These results suggest that the bactericidal effect of EAW against Mycobacteria occurs by degradation of the cell wall, followed by denaturation of cytoplasmic proteins, but degeneration of the nucleic acid is not always necessary.

False-positive accumulation of metaiodobenzylguanidine in a case with acute intermittent porphyria.

We report a 36-year-old woman presenting with hypertensive encephalopathy followed by bulbar palsy and quadriplegia. After an extensive screening for secondary causes of hypertension, the patient was suspected of having pheochromocytoma due to increased levels of catecholamines in the plasma and the urine, and positive (131)I-metaiodobenzylguanidine (MIBG) accumulation in the gallbladder. However, MIBG accumulation was not reproducible without any tumors accompanying this accumulation in the gallbladder. A diagnosis of acute intermittent porphyria was finally confirmed based on the characteristic pictures, increased urinary excretion of porphobilinogen, and identification of a heterozygous missense mutation of R173W in the hydroxymethylbilane synthase gene. This case highlights a pitfall in utilizing MIBG to detect a source of excessive catecholamine and also suggests the importance of having a complete clinical history and extensive work-up of any possible differential diagnosis. We also review the potential mechanism by which false-positive MIBG accumulation occurs.