A Study on the Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography.

In the medical field, it is delicate to anticipate good performance in using deep learning due to the lack of large-scale training data and class imbalance. In particular, ultrasound, which is a key breast cancer diagnosis method, is delicate to diagnose accurately as the quality and interpretation of images can vary depending on the operator's experience and proficiency. Therefore, computer-aided diagnosis technology can facilitate diagnosis by visualizing abnormal information such as tumors and masses in ultrasound images. In this study, we implemented deep learning-based anomaly detection methods for breast ultrasound images and validated their effectiveness in detecting abnormal regions. Herein, we specifically compared the sliced-Wasserstein autoencoder with two representative unsupervised learning models autoencoder and variational autoencoder. The anomalous region detection performance is estimated with the normal region labels. Our experimental results showed that the sliced-Wasserstein autoencoder model outperformed the anomaly detection performance of others. However, anomaly detection using the reconstruction-based approach may not be effective because of the occurrence of numerous false-positive values. In the following studies, reducing these false positives becomes an important challenge.

Prediction of Implant Size Based on Breast Volume Using Mammography with Fully Automated Measurements and Breast MRI.

BACKGROUND: Determination of implant size is crucial for patients with breast cancer undergoing one-stage breast reconstruction. The purpose of this study is to predict the implant size based on the breast volume measured by mammography (MG) with a fully automated method, and by breast magnetic resonance imaging (MRI) with a semi-automated method, in breast cancer patients with direct-to-implant reconstruction. PATIENTS AND METHODS: This retrospective study included 84 patients with breast cancer who underwent direct-to-implant reconstruction after nipple-sparing or skin-sparing mastectomy and preoperative MG and MRI between April 2015 and April 2019. Breast volume was measured using (a) MG with a fully automated commercial software and (b) MRI with an in-house semi-automated software program. Multivariable regression analyses including breast volume and patient weight (P < 0.05 in univariable analysis) were conducted to predict implant size. RESULTS: MG and MRI breast volume was highly correlated with both implant size (correlation coefficient 0.862 and 0.867, respectively; P values < 0.001) and specimen weight (correlation coefficient 0.802 and 0.852, respectively; P values < 0.001). Mean absolute difference between the MR breast volume and implant size was 160 cc, which was significantly higher than that between the MG breast volume and implant size of 118 cc (P < 0.001). On multivariable analyses, only breast volume measured by both MG and MRI was significantly associated with implant size in any implant type (all P values < 0.001). CONCLUSION: Breast volume measured by MG and MRI can be used to predict appropriate implant size in breast cancer patients undergoing direct-to-implant reconstruction in an efficient and objective manner.

Clinical adaptation of synthetic MRI-based whole brain volume segmentation in children at 3 T: comparison with modified SPM segmentation methods.

PURPOSE: To validate the use of synthetic magnetic resonance imaging (SyMRI) volumetry by comparing with child-optimized SPM 12 volumetry in 3 T pediatric neuroimaging. METHODS: In total, 106 children aged 4.7-18.7 years who underwent both synthetic and 3D T1-weighted imaging and had no abnormal imaging/neurologic findings were included for the SyMRI vs. SPM T1-only segmentation (SPM T1). Forty of the 106 children who underwent an additional 3D T2-weighted imaging were included for the SyMRI vs. SPM multispectral segmentation (SPM multi). SPM segmentation using an age-appropriate atlas and inverse-transforming template-space intracranial mask was compared with SyMRI segmentation. Volume differences between SyMRI and SPM T1 were plotted against age to evaluate the influence of age on volume difference. RESULTS: Measurements derived from SyMRI and two SPM methods showed excellent agreements and strong correlations except for the CSF volume (CSFV) (intraclass correlation coefficients = 0.87-0.98; r = 0.78-0.96; relative volume difference other than CSFV = 6.8-18.5% [SyMRI vs. SPM T1] and 11.3-22.7% [SyMRI vs. SPM multi]). Dice coefficients of all brain tissues (except CSF) were in the range 0.78-0.91. The Bland-Altman plot and age-related volume difference change suggested that the volume differences between the two methods were influenced by the volume of each brain tissue and subject's age (p < 0.05). CONCLUSION: SyMRI and SPM segmentation results were consistent except for CSFV, which supports routine clinical use of SyMRI-based volumetry in pediatric neuroimaging. However, caution should be taken in the interpretation of the CSF segmentation results.

A Case Study of Quantizing Convolutional Neural Networks for Fast Disease Diagnosis on Portable Medical Devices.

Recently, the amount of attention paid towards convolutional neural networks (CNN) in medical image analysis has rapidly increased since they can analyze and classify images faster and more accurately than human abilities. As a result, CNNs are becoming more popular and play a role as a supplementary assistant for healthcare professionals. Using the CNN on portable medical devices can enable a handy and accurate disease diagnosis. Unfortunately, however, the CNNs require high-performance computing resources as they involve a significant amount of computation to process big data. Thus, they are limited to being used on portable medical devices with limited computing resources. This paper discusses the network quantization techniques that reduce the size of CNN models and enable fast CNN inference with an energy-efficient CNN accelerator integrated into recent mobile processors. With extensive experiments, we show that the quantization technique reduces inference time by 97% on the mobile system integrating a CNN acceleration engine.

Axillary Nodal Burden Assessed with Pretreatment Breast MRI Is Associated with Failed Sentinel Lymph Node Identification after Neoadjuvant Chemotherapy for Breast Cancer.

Background After publication of the findings of the American College of Surgeons Oncology Group Z1071 trial, sentinel lymph node biopsy (SLNB) has been increasingly performed in patients with breast cancer after neoadjuvant chemotherapy (NAC). Purpose To investigate the pretreatment breast MRI and clinical-pathologic characteristics associated with failed sentinel node identification after NAC in patients with breast cancer. Materials and Methods Patients who underwent SLNB after NAC between January 2015 and January 2019 were retrospectively identified. Two radiologists independently reviewed the characteristics of axillary nodes (number, perinodal infiltration, cortical thickness, and maximal diameter) at pretreatment breast MRI. The associations of the clinical-pathologic and imaging characteristics of the axillary nodes with sentinel node identification were assessed by using the χ2 test and/or the χ2 test for trend and multivariable logistic regression with odds ratio (OR) calculation. Results A total of 276 women (mean age ± standard deviation, 48 years ± 9; range, 27-68 years) were included. Sentinel nodes were identified in 252 of the 276 patients (91%). Multivariable analysis showed that higher (stage 3 or 4) clinical T stages (OR = 5.2, P = .004 for radiologist 1; OR = 4.6, P = .01 for radiologist 2), use of a single tracer (OR = 4.3, P = .04 for radiologist 1; OR = 3.9, P = .046 for radiologist 2), a greater number (10 or more) of suspicious axillary nodes (OR = 11.5, P = .002 for radiologist 1; OR = 8.3, P = .01 for radiologist 2), and the presence of perinodal infiltration (OR = 7.0, P = .002 for radiologist 1; OR = 7.5, P = .003 for radiologist 2) were associated with failed sentinel node identification. Conclusion A greater number of suspicious axillary nodes and the presence of perinodal infiltration at pretreatment MRI, higher clinical T stages, and use of a single tracer were independently associated with failed sentinel node identification after neoadjuvant chemotherapy in patients with breast cancer. © RSNA, 2020 See also the editorial by Imbriaco in this issue.

Efficacy of breast MRI for surgical decision in patients with breast cancer: ductal carcinoma in situ versus invasive ductal carcinoma.

BACKGROUND: Preoperative breast magnetic resonance imaging (MRI) provides more information than mammography and ultrasonography for determining the surgical plan for patients with breast cancer. This study aimed to determine whether breast MRI is more useful for patients with ductal carcinoma in situ (DCIS) lesions than for those with invasive ductal carcinoma (IDC). METHODS: A total of 1113 patients with breast cancer underwent mammography, ultrasonography, and additional breast MRI before surgery. The patients were divided into 2 groups: DCIS (n = 199) and IDC (n = 914), and their clinicopathological characteristics and oncological outcomes were compared. Breast surgery was classified as follows: conventional breast-conserving surgery (Group 1), partial mastectomy with volume displacement (Group 2), partial mastectomy with volume replacement (Group 3), and total mastectomy with or without reconstruction (Group 4). The initial surgical plan (based on routine mammography and ultrasonography) and final surgical plan (after additional breast MRI) were compared between the 2 groups. The change in surgical plan was defined as group shifting between the initial and final surgical plans. RESULTS: Changes (both increasing and decreasing) in surgical plans were more common in the DCIS group than in the IDC group (P <  0.001). These changes may be attributed to the increased extent of suspicious lesions on breast MRI, detection of additional daughter nodules, multifocality or multicentricity, and suspicious findings on mammography or ultrasonography but benign findings on breast MRI. Furthermore, the positive margin incidence in frozen biopsy was not different (P = 0.138). CONCLUSIONS: Preoperative breast MRI may provide more information for determining the surgical plan for patients with DCIS than for those with IDC.

Effect of neoadjuvant chemotherapy on breast tissue composition: a longitudinal mammographic study with automated volumetric measurement.

OBJECTIVES: To investigate the effect of neoadjuvant chemotherapy (NAC) on breast tissue composition with mammographic automated volumetric measurement. METHODS: This retrospective study included 168 breast cancer patients who were treated with NAC and underwent serial mammography (pre-treatment, mid-treatment, and post-treatment) between January 2015 and October 2018. Automated volumetric measurements of the contralateral breast volume (BV), fibroglandular volume (FGV), and breast density (BD) were performed using Volpara software. BD grades were divided into 4 groups by Volpara density grade (VDG). The longitudinal changes in BV, FGV, BD, and their associated factors were evaluated. RESULTS: Repeated-measures analysis of variance demonstrated a significant reduction in BV, FGV, and BD over time (p < 0.001, p < 0.001, and p = 0.002, respectively). BV showed a greater reduction in the second half than in the first half (- 28.6 cm3 vs. - 15.2 cm3), BD showed a greater reduction in the first half than in the second half (- 0.8% vs. - 0.1%), and FGV steadily decreased (- 4.6 cm3 and - 3.9 cm3 in the first and second halves). On multivariable linear regression analysis, chemotherapy regimen was associated with BV change between pre- and post-treatment (p = 0.002); age (p = 0.024) and VDG (p = 0.027) were associated with FGV change; age (p = 0.037), VDG (p = 0.002), and chemotherapy regimen (p = 0.003) were associated with BD change. CONCLUSIONS: NAC affects breast tissue composition, reflected as reductions in BV, FGV, and BD. Mammography with automated volumetric measurement can capture quantitative changes in these breast tissue parameters during NAC. KEY POINTS: • Neoadjuvant chemotherapy (NAC) affects breast tissue composition with different patterns of reduction in breast volume, fibroglandular volume, and breast density. • Age, Volpara density grades, and NAC regimen were independent factors associated with breast density change between pre-treatment and post-treatment. • Mammography with automated volumetric measurement enables identification of longitudinal changes in breast tissue composition.

Ultrasound-guided dual-localization for axillary nodes before and after neoadjuvant chemotherapy with clip and activated charcoal in breast cancer patients: a feasibility study.

BACKGROUND: We report on our experience of ultrasound (US)-guided dual-localization for axillary nodes before and after neoadjuvant chemotherapy (NAC) with clip and activated charcoal to guide axillary surgery in breast cancer patients. METHODS: Between November 2017 and May 2018, a dual-localization procedure was performed under US guidance for the most suspicious axillary nodes noted at initial staging (before NAC, with clip) and restaging (after NAC, with activated charcoal) in 28 cytologically proven node-positive breast cancer patients. Patients underwent axillary sampling or dissection, which involved removing not only the sentinel nodes (SNs), but also clipped nodes (CNs) and tattooed nodes (TNs). Success (or failure) rates of biopsies of SNs, CNs, and TNs and inter-nodal concordance rates were determined. Sensitivities for the individual and combined biopsies were calculated. RESULTS: SN biopsy failed in four patients (14%), whereas the CN biopsy failed in one patient (4%). All TNs were identified in the surgical field. Concordance rates were 79% for CNs-TNs, 63% for CNs-SNs, and 58% for TNs-SNs. Sensitivity for SN, CN, and TN biopsy was 73%, 67%, and 67%, respectively. Sensitivity was 80% for any combination of biopsies (SN plus CN, SN plus TN, SN plus CN plus TN). CONCLUSIONS: US-guided dual-localization of axillary nodes before and after NAC with clip and activated charcoal was a feasible approach that might facilitate more reliable nodal staging with less-invasive strategies in node-positive breast cancer patients.

Restaging the axilla after neo-adjuvant chemotherapy for breast cancer: Predictive factors for residual metastatic lymph node disease with negative imaging findings.

To evaluate predictive factors for residual metastatic axillary lymph node (ALN) disease in patients with negative imaging findings after neo-adjuvant chemotherapy (NAC) for breast cancer. From January 2011 to December 2015, 206 patients underwent imaging including ultrasonography, MRI, and PET/CT for restaging the axilla after NAC. Data collected included preoperative information regarding histologic grade, hormone receptor (HR) status, and human epidermal growth factor receptor 2 (HER2) status. Multivariate logistic regression analysis was performed to compare patients with and without residual metastatic ALN disease among patients who showed negative imaging findings after NAC. Of the 181 and 25 patients with initially node-positive and node-negative disease, 131 (72.4%) and 23 (92.0%), respectively, showed negative imaging findings after NAC. Among these 131 and 23 patients, 53 (40.5%) and two patients (8.7%), respectively, had residual metastatic ALN disease. Low to moderate tumor grade (odds ratio [OR] = 5.2, P = 0.009), positive HR status (OR = 6.6, P = 0.003), and negative HER2 status (OR = 2.6, P = 0.048) were associated with residual metastatic ALN disease. Low to moderate histologic grade, positive HR status, and negative HER2 status may serve as predictors of residual metastatic ALN disease in patients with negative imaging findings after NAC for breast cancer.

Invasive Breast Cancer: Prognostic Value of Peritumoral Edema Identified at Preoperative MR Imaging.

Purpose To determine the prognostic value of peritumoral edema identified at preoperative breast magnetic resonance (MR) imaging for disease recurrence in patients with invasive breast cancer. Materials and Methods Between January 2011 and December 2012, 353 women (median age, 49 years; range, 27-77 years) with invasive breast cancer who had undergone preoperative MR imaging and mastectomy or breast-conserving surgery were identified. Two radiologists independently reviewed peritumoral edema on the basis of the degree of the signal intensity surrounding the tumor on T2-weighted images. The association of disease recurrence with peritumoral edema and clinical-pathologic features was assessed by using the multivariate Cox proportional hazards model and the integrated discrimination improvement (IDI) and continuous net reclassification improvement (NRI) indexes. Results Twenty-four patients (6.8%) had disease recurrence after 27.2 months of median follow-up. At multivariate analysis, higher N stage (hazard ratio = 4.84, P = .002) and the presence of lymphovascular invasion (hazard ratio = 2.48, P = .044) and peritumoral edema (hazard ratio = 2.77, P = .022) were independent factors associated with disease recurrence. IDI and continuous NRI showed significant improvement in the accuracy of the association with disease recurrence when peritumoral edema was added to established clinical-pathologic features (IDI = 0.061, P < .001; continuous NRI = 0.334, P = .012). Conclusion Peritumoral edema identified at preoperative MR imaging is independently associated with disease recurrence. Peritumoral edema assessment may provide better prognostication in patients with invasive breast cancer. © RSNA, 2018.

Ultrasound-Guided Restaging and Localization of Axillary Lymph Nodes After Neoadjuvant Chemotherapy for Guidance of Axillary Surgery in Breast Cancer Patients: Experience with Activated Charcoal.

OBJECTIVE: The aim of this study was to review our experience with ultrasound (US)-guided localization of axillary lymph nodes using activated charcoal for the guidance of axillary surgery after neoadjuvant chemotherapy (NAC) in clinically node-positive breast cancer patients. METHODS: Between April 2016 and April 2017, US-guided localization of the most suspicious axillary lymph nodes at restaging US using activated charcoal (Charcotrace™) was performed in 45 consecutive, clinically node-positive breast cancer patients who had less than two suspicious nodes after NAC and axillary surgery with sentinel node biopsy. Sentinel nodes were defined as radioactive nodes or nodes containing blue dye. The concordance between final pathological results for both the tattooed and sentinel nodes was analyzed. RESULTS: Sentinel node biopsy failed in five patients (11%) in whom axillary surgery was performed under the guidance of the tattooed node. The tattooed nodes were identified in the surgical field in 44 patients (98%). Of the 44 tattooed nodes, 25 (57%) were concordant with the sentinel nodes and 19 (43%) were non-sentinel nodes, including the five nodes with failed sentinel node biopsy. In the final pathological results, 18 patients (40%) had metastatic nodes. The sensitivities for detecting axillary metastasis of the sentinel node biopsy, tattooed node biopsy, and the sentinel and/or tattooed node biopsy were 61% (11/18), 67% (12/18), and 78% (14/18), respectively. CONCLUSION: US-guided localization of axillary lymph nodes using activated charcoal at restaging after NAC in clinically node-positive breast cancer patients is a useful technique to guide axillary surgery, with a high identification rate.

Mammographic density changes following discontinuation of tamoxifen in premenopausal women with oestrogen receptor-positive breast cancer.

OBJECTIVES: To evaluate the changes in mammographic density after tamoxifen discontinuation in premenopausal women with oestrogen receptor-positive breast cancers and the underlying factors METHODS: A total of 213 consecutive premenopausal women with breast cancer who received tamoxifen treatment after curative surgery and underwent three mammograms (baseline, after tamoxifen treatment, after tamoxifen discontinuation) were included. Changes in mammographic density after tamoxifen discontinuation were assessed qualitatively (decrease, no change, or increase) by two readers and measured quantitatively by semi-automated software. The association between % density change and clinicopathological factors was evaluated using univariate and multivariate regression analyses. RESULTS: After tamoxifen discontinuation, a mammographic density increase was observed in 31.9% (68/213, reader 1) to 22.1% (47/213, reader 2) by qualitative assessment, with a mean density increase of 1.8% by quantitative assessment compared to density before tamoxifen discontinuation. In multivariate analysis, younger age (≤ 39 years) and greater % density decline after tamoxifen treatment (≥ 17.0%) were independent factors associated with density change after tamoxifen discontinuation (p < .001 and p = .003, respectively). CONCLUSIONS: Tamoxifen discontinuation was associated with mammographic density change with a mean density increase of 1.8%, which was associated with younger age and greater density change after tamoxifen treatment. KEY POINTS: • Increased mammographic density after tamoxifen discontinuation can occur in premenopausal women. • Mean density increase after tamoxifen discontinuation was 1.8%. • Density increase is associated with age and density decrease after tamoxifen.

Diagnostic performance of tomosynthesis and breast ultrasonography in women with dense breasts: a prospective comparison study.

PURPOSE: To compare the diagnostic performances of tomosynthesis and ultrasonography as adjunctives to digital mammography in women with dense breasts. METHODS: A total of 778 women with dense breasts underwent digital mammography with tomosynthesis and ultrasonography for screening and diagnostic purposes. The findings of tomosynthesis and ultrasonography were evaluated independently. The primary endpoint was overall diagnostic accuracy determined by area under the receiver operating characteristic curve (AUC). Secondary endpoints included sensitivity, specificity, and predictive values. RESULTS: Of the 778 participants, 698 women (140 breast cancers) were included in the analysis. Based on the AUC findings, the non-inferiority of tomosynthesis to ultrasonography was established in the overall group as well as in all subgroups except for that comprising women with extremely dense breast composition. There were no significant differences in AUC between tomosynthesis and ultrasonography among asymptomatic participants and participants who underwent imaging for screening (0.912 vs. 0.934 [P = 0.403] and 0.987 vs. 0.950 [P = 0.270], respectively). Tomosynthesis exhibited lower sensitivity (91.4 vs. 96.4%; P = 0.039), and higher specificity (83.9 vs. 70.4%; P < 0.001) and positive predictive value (58.7 vs. 45.0%; P < 0.001) than ultrasonography. CONCLUSIONS: Tomosynthesis exhibits comparable performance to ultrasonography as an adjunct to mammography for diagnosis of breast cancer, except among women with extremely dense breasts.

Preoperative MRI features associated with lymphovascular invasion in node-negative invasive breast cancer: A propensity-matched analysis.

PURPOSE: In node-negative disease, the presence of lymphovascular invasion (LVI) is reported to be an unfavorable prognostic factor. Thus, the aim of this study was to evaluate whether preoperative breast MRI features are associated with LVI in patients with node-negative invasive breast cancer by a propensity-matched analysis. MATERIALS AND METHODS: Among 389 patients with node-negative invasive ductal breast cancer who had preoperative breast 3.0 Tesla MRI with precontrast T2-weighted fat-suppressed, pre- and dynamic postcontrast T1-weighted fat-suppressed sequences, 61 patients with LVI (LVI group) were matched with 183 patients without LVI (no LVI group) at a ratio of 1:3 in terms of age, histologic grade, tumor size, and hormone receptor status. Two radiologists reviewed the MRI features, following profiles of focal breast edema (peritumoral, prepectoral, subcutaneous), intratumoral T2 signal intensity, adjacent vessel sign, and increased ipsilateral whole-breast vascularity, in addition to 2013 Breast Imaging Reporting and Data System lexicon. RESULTS: The presence of peritumoral edema (45.9% [28/61] versus 30.6% [56/183], P = 0.030) and adjacent vessel sign (82.0% [50/61] versus 68.3% [125/183], P = 0.041) was significantly associated with LVI. Prepectoral edema was also more frequently observed in the LVI group than in the no LVI group with borderline significance (26.2% [16/61] versus 15.3% [28/183], P = 0.055). In cases of nonmass enhancement, regional enhancement was more frequently found in the LVI group than in the no LVI group (60.0% [3/4] versus 5.9% [1/4], P = 0.042). CONCLUSION: Preoperative breast MRI features may be associated with LVI in patients with node-negative invasive breast cancer. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1037-1044.

Background echotexture classification in breast ultrasound: inter-observer agreement study.

Background According to the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS), background echotexture in breast ultrasound (US) can be categorized as homogeneous or heterogeneous. Purpose To prospectively evaluate the inter-observer agreement of a four-category classification in background echotexture assessments of breast US and to determine whether background echotexture is related to breast cancer risk factors, including mammography density. Material and Methods Thirty-eight healthy women (age range, 25-72) were recruited. Eleven radiologists performed breast US on all participants and classified each background echotexture into four categories (homogeneous, mild, moderate, and marked heterogeneous). The inter-observer agreement in the assessments was measured using kappa statistics (к). The association between background echotexture and breast cancer risk factors, including mammographic density, menopausal status, and parity, were evaluated using Spearman's correlation coefficient (ρ) and multiple linear regression analysis. Results There was moderate inter-observer agreement between the radiologists for the four categories of background echotexture (average к = 0.45). Heterogeneity of the background echotexture was positively correlated with mammographic density in both pre- and postmenopausal women (premenopausal, ρ = 0.42, P < 0.0001; postmenopausal, ρ = 0.56, P < 0.0001). Multiple linear regression analysis revealed that mammographic density and parity were significantly associated with background echotexture. Conclusion Background echotexture assessment of breast US using a four-category classification showed moderate inter-observer agreement, and more heterogeneous background echotexture was associated with denser breasts and lower parity.

Impact of prior mammograms on combined reading of digital mammography and digital breast tomosynthesis.

Background Although digital breast tomosynthesis (DBT) is an emerging technique yielding higher sensitivity and specificity compared to digital mammography (DM) alone, relative contribution of prior mammograms on the interpretation of DBT combined with DM has not been investigated. Purpose To retrospectively compare the diagnostic performances of DM, DM + DBT, and DM + DBT with prior mammograms. Material and Methods Three breast radiologists independently reviewed images of 116 patients with 24 cancers in the sequential order of DM, DM + DBT, and DM + DBT with prior mammograms using Breast Imaging Reporting and Data System (BI-RADS) assessment categories. Results The average areas under the receiver operating characteristic curve (AUC) of DM, DM + DBT, and DM + DBT with prior mammograms were 0.712, 0.777, and 0.816, respectively. Adding prior mammograms did not significantly affect the AUC of DM + DBT ( P = 0.108), whereas adding DBT significantly increased the AUC of DM ( P = 0.009). Sensitivity for DM, DM + DBT, and DM + DBT with prior mammograms was 58.3%, 69.4%, and 69.4%, and specificities were 84.1%, 85.9%, and 93.8%, respectively. Addition of DBT significantly increased the sensitivity ( P = 0.0090) of DM. Prior mammograms significantly improved the specificity of DM + DBT ( P = 0.0004), whereas adding prior mammogram did not affect sensitivity of DM + DBT ( P = 1.000). Conclusion DBT significantly increases the overall sensitivity and diagnostic performance of DM. Prior mammograms significantly increase the specificity of DM + DBT but have no significant effect on sensitivity and overall diagnostic performance.

Image quality at synthetic brain magnetic resonance imaging in children.

BACKGROUND: The clinical application of the multi-echo, multi-delay technique of synthetic magnetic resonance imaging (MRI) generates multiple sequences in a single acquisition but has mainly been used in adults. OBJECTIVE: To evaluate the image quality of synthetic brain MR in children compared with that of conventional images. MATERIALS AND METHODS: Twenty-nine children (median age: 6 years, range: 0-16 years) underwent synthetic and conventional imaging. Synthetic (T2-weighted, T1-weighted and fluid-attenuated inversion recovery [FLAIR]) images with settings matching those of the conventional images were generated. The overall image quality, gray/white matter differentiation, lesion conspicuity and image degradations were rated on a 5-point scale. The relative contrasts were assessed quantitatively and acquisition times for the two imaging techniques were compared. RESULTS: Synthetic images were inferior due to more pronounced image degradations; however, there were no significant differences for T1- and T2-weighted images in children <2 years old. The quality of T1- and T2-weighted images were within the diagnostically acceptable range. FLAIR images showed greatly reduced quality. Gray/white matter differentiation was comparable or better in synthetic T1- and T2-weighted images, but poorer in FLAIR images. There was no effect on lesion conspicuity. Synthetic images had equal or greater relative contrast. Acquisition time was approximately two-thirds of that for conventional sequences. CONCLUSION: Synthetic T1- and T2-weighted images were diagnostically acceptable, but synthetic FLAIR images were not. Lesion conspicuity and gray/white matter differentiation were comparable to conventional MRI.

Internal mammary node adenopathy on breast MRI and PET/CT for initial staging in patients with operable breast cancer: prevalence and associated factors.

PURPOSE: To evaluate the prevalence of and factors associated with internal mammary node (IMN) adenopathy on MRI and PET/CT used for initial staging in patients with operable breast cancer. METHODS: A total of 1320 patients diagnosed with invasive breast carcinoma between January 2011 and December 2015 underwent MRI and PET/CT for initial staging. The patients were considered to have IMN adenopathy when MRI revealed IMNs with the longest diameter of 5 mm or greater and a standardized uptake value greater than that of the mediastinal blood pool/contralateral parasternal area on PET/CT. The prevalence was determined as overall percentage of patients with IMN adenopathy, as well as percentages among patients who received neoadjuvant chemotherapy and those who did not. The association of IMN adenopathy with factors was evaluated using multivariate logistic regression analysis. RESULTS: Of the 1320 patients, 35 patients [2.7 %; 95 % confidence interval (CI) 1.8-3.6 %] had IMN adenopathy, with a total of 49 IMNs. Among patients without and with neoadjuvant chemotherapy (n = 1092 and n = 228, respectively), IMN adenopathy was identified in 13 (1.2 %; 95 % CI 0.6-2.0 %) and 22 patients (9.6 %; 95 % CI 6.0-14.6 %), respectively. Inner tumor location [odds ratio (OR) 5.9; P = .002] and positive axillary lymph node status (OR 4.4; P < .0001) were associated with IMN adenopathy. CONCLUSIONS: IMN adenopathy was identified at initial staging with PET/CT and MRI with a prevalence of 2.7 %. Inner tumor location and positive axillary lymph node status were associated with IMN adenopathy.