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Objective@#To investigate whether reader training improves the performance and agreement of radiologists in interpreting unenhanced breast magnetic resonance imaging (MRI) scans using diffusion-weighted imaging (DWI). @*Materials and Methods@#A study of 96 breasts (35 cancers, 24 benign, and 37 negative) in 48 asymptomatic women was performed between June 2019 and October 2020. High-resolution DWI with b-values of 0, 800, and 1200 sec/mm 2 was performed using a 3.0-T system. Sixteen breast radiologists independently reviewed the DWI, apparent diffusion coefficient maps, and T1-weighted MRI scans and recorded the Breast Imaging Reporting and Data System (BI-RADS) category for each breast. After a 2-h training session and a 5-month washout period, they re-evaluated the BI-RADS categories. A BI-RADS category of 4 (lesions with at least two suspicious criteria) or 5 (more than two suspicious criteria) was considered positive.The per-breast diagnostic performance of each reader was compared between the first and second reviews. Inter-reader agreement was evaluated using a multi-rater κ analysis and intraclass correlation coefficient (ICC). @*Results@#Before training, the mean sensitivity, specificity, and accuracy of the 16 readers were 70.7% (95% confidence interval [CI]: 59.4–79.9), 90.8% (95% CI: 85.6–94.2), and 83.5% (95% CI: 78.6–87.4), respectively. After training, significant improvements in specificity (95.2%; 95% CI: 90.8–97.5; P = 0.001) and accuracy (85.9%; 95% CI: 80.9–89.8; P = 0.01) were observed, but no difference in sensitivity (69.8%; 95% CI: 58.1–79.4; P = 0.58) was observed. Regarding inter-reader agreement, the κ values were 0.57 (95% CI: 0.52–0.63) before training and 0.68 (95% CI: 0.62–0.74) after training, with a difference of 0.11 (95% CI: 0.02–0.18; P = 0.01). The ICC was 0.73 (95% CI: 0.69–0.74) before training and 0.79 (95% CI: 0.76–0.80) after training (P = 0.002). @*Conclusion@#Brief reader training improved the performance and agreement of interpretations by breast radiologists using unenhanced MRI with DWI.
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Despite recent advances in artificial intelligence (AI) software with improved performance in mammography screening for breast cancer, insufficient data are available on its performance in detecting cancers that were initially missed on mammography. In this study, we aimed to determine whether AI software-aided mammography could provide additional value in identifying cancers detected through supplemental screening ultrasound. We searched our database from 2017 to 2018 and included 238 asymptomatic patients (median age, 50 years; interquartile range, 45–57 years) diagnosed with breast cancer using supplemental ultrasound. Two unblinded radiologists retrospectively reviewed the mammograms using commercially available AI software and identified the reasons for missed detection.Clinicopathological characteristics of AI-detected and AI-undetected cancers were compared using univariate and multivariate logistic regression analyses. A total of 253 cancers were detected in 238 patients using ultrasound. In an unblinded review, the AI software failed to detect 187 of the 253 (73.9%) mammography cases with negative findings in retrospective observations. The AI software detected 66 cancers (26.1%), of which 42 (63.6%) exhibited indiscernible findings obscured by overlapping dense breast tissues, even with the knowledge of magnetic resonance imaging and post-wire localization mammography. The remaining 24 cases (36.4%) were considered interpretive errors by the radiologists. Invasive tumor size was associated with AI detection after multivariable analysis (odds ratio, 2.2; 95% confidence intervals, 1.5–3.3; p < 0.001). In the control group of 160 women without cancer, the AI software identified 19 false positives (11.9%, 19/160). Although most ultrasound-detected cancers were not detected on mammography with the use of AI, the software proved valuable in identifying breast cancers with indiscernible abnormalities or those that clinicians may have overlooked.
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Purpose@#This study aimed to evaluate the role of Doppler ultrasound (US) and elastography to identify residual breast cancer for patients showing near complete response following chemotherapy on magnetic resonance imaging (MRI). @*Methods@#Between September 2016 and January 2018, 40 breast cancer patients who showed near complete response (either tumor size ≤0.5 cm or lesion-to-background parenchymal signal enhancement ratio ≤1.6) on MRI following neoadjuvant chemotherapy were prospectively enrolled. After excluding seven women who did not undergo Doppler US and elastography, 33 women (median age, 49 years; range, 32 to 67 years) were analyzed. On the day of surgery, women underwent Doppler US and elastography for tumor bed prior to US-guided core needle biopsy. Histopathologic results of biopsy and surgery were evaluated. Negative predictive value (NPV) and false negative rate (FNR) of biopsy and the combined Doppler US and elastography were analyzed, respectively. @*Results@#After surgery, nine women had residual cancers and 24 women had pathologic complete response. The NPV and FNR of biopsy were 92% (24 of 26) and 22% (2 of 9), respectively. The NPV and FNR of combined Doppler US and elastography were 100% (14 of 14) and 0% (0 of 9), respectively. All of nine women with residual cancers had positive vascularity or elasticity. Two women with false-negative biopsy results, having 0.3 cm or 2.5 cm ductal carcinoma in situ at surgery, showed positive vascularity or elasticity. @*Conclusion@#Tumor bed showing positive vascularity or elasticity indicates residual breast cancer for patients showing near complete response on MRI following chemotherapy.
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Objective@#To compare the outcomes of digital breast tomosynthesis (DBT) screening combined with ultrasound (US) with those of digital mammography (DM) combined with US in women with dense breasts. @*Materials and Methods@#A retrospective database search identified consecutive asymptomatic women with dense breasts who underwent breast cancer screening with DBT or DM and whole-breast US simultaneously between June 2016 and July 2019. Women who underwent DBT + US (DBT cohort) and DM + US (DM cohort) were matched using 1:2 ratio according to mammographic density, age, menopausal status, hormone replacement therapy, and a family history of breast cancer. The cancer detection rate (CDR) per 1000 screening examinations, abnormal interpretation rate (AIR), sensitivity, and specificity were compared. @*Results@#A total of 863 women in the DBT cohort were matched with 1726 women in the DM cohort (median age, 53 years; interquartile range, 40–78 years) and 26 breast cancers (9 in the DBT cohort and 17 in the DM cohort) were identified. The DBT and DM cohorts showed comparable CDR (10.4 [9 of 863; 95% confidence interval {CI}: 4.8–19.7] vs. 9.8 [17 of 1726;95% CI: 5.7–15.7] per 1000 examinations, respectively; P = 0.889). DBT cohort showed a higher AIR than the DM cohort (31.6% [273 of 863; 95% CI: 28.5%–34.9%] vs. 22.4% [387 of 1726; 95% CI: 20.5%–24.5%]; P < 0.001). The sensitivity for both cohorts was 100%. In women with negative findings on DBT or DM, supplemental US yielded similar CDRs in both DBT and DM cohorts (4.0 vs. 3.3 per 1000 examinations, respectively; P = 0.803) and higher AIR in the DBT cohort (24.8% [188 of 758; 95% CI: 21.8%–28.0%] vs. 16.9% [257 of 1516; 95% CI: 15.1%–18.9%; P < 0.001). @*Conclusion@#DBT screening combined with US showed comparable CDR but lower specificity than DM screening combined with US in women with dense breasts.
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Purpose@#To evaluate the axillary recurrence rate and usefulness of axillary ultrasound (AUS) during supplementary whole-breast ultrasound (US) screening in women with a personal history of breast cancer (PHBC). @*Methods@#A retrospective database search identified consecutive asymptomatic women who underwent postoperative supplemental whole-breast US screening, including that of the bilateral axillae, after negative findings on mammography between January and June 2017. Using the pathologic data or at least 1-year follow-up data as reference standards, the axillary recurrence rate, cancer detection rate (CDR), interval axillary recurrence rate per 1,000 screenings, sensitivity, specificity, and abnormal interpretation rate (AIR) were estimated. @*Results@#From the data of 4,430 women (mean age, 55.0 ± 10.1 years) analyzed in this study, there were five axillary recurrence cases (1.1/1,000) in the median follow-up period of 57.2 months. AUS showed a CDR of 0.2 (1/4,430; 95% confidence interval [CI], 0.01–1.3) and an interval axillary recurrence rate of 0.9 (4/4,402; 95% CI, 0.2–2.3) per 1,000 examinations. The sensitivity and specificity were 20.0% (1/5; 95% CI, 0.5–71.6), and 99.4% (4,398/4,425; 95% CI, 99.1–99.6), respectively, while the AIR was 0.6% (28/4,430; 95% CI, 0.4–0.9%). @*Conclusion@#In asymptomatic women with a PHBC and negative findings on mammography, axillary recurrence after breast cancer and axillary treatment was uncommon, and the supplemental AUS screening yielded 0.2 cancers per 1,000 examinations.
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This study aimed to evaluate the imaging and pathological findings in axillary lymph nodes in patients with breast cancer who received concurrent ipsilateral coronavirus disease 2019 (COVID-19) vaccination. Of the 19 women with breast cancer who received concurrent COVID-19 vaccination shot in the arm ipsilateral to breast cancer, axillary lymphadenopathy was observed in 84.2% (16 of 19) of patients on ultrasound (US) and 71.4% (10 of 14) of patients on magnetic resonance imaging (MRI), and 21.0% (4 of 19) of patients were diagnosed with metastasis. Abnormal US and MRI findings of cortical thickening, effacement of the fatty hilum, round shape, and asymmetry in the number or size relative to the contralateral side were noted in more than half of the non-metastatic and metastatic lymph nodes; however, statistical significance was not noted. Axillary lymphadenopathy is commonly observed in patients with breast cancer who receive concurrent ipsilateral COVID-19 vaccination without specific differential imaging features. Thus, understanding the limitations of axillary imaging and cautious interpretation is necessary to avoid overestimation or underestimation of the axillary disease burden.
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Coronavirus disease 2019 (COVID-19) vaccine-induced lymphadenopathy is a critical side effect that should be a concern to clinicians, patients, radiologists, and oncologists. Vaccine-induced lymphadenopathy causes a diagnostic dilemma, especially for breast radiologists who examine both axillary regions during breast ultrasound examinations. Appropriate imaging guidelines are needed to manage vaccine-induced lymphadenopathy for patients undergoing screening examinations or symptomatic patients, including cancer patients.Current Concepts: For patients with axillary lymphadenopathy in the setting of recent ipsilateral vaccination, clinical follow-up is recommended. In other scenarios, short-term follow-up axillary ultrasound examinations are recommended if the clinical concerns persist for more than 6 weeks after vaccination. To mitigate the diagnostic dilemma of vaccine-induced lymphadenopathy, patients should schedule screening imaging examinations before the first vaccination or at least six weeks following the second vaccination. For clinicians and radiologists, documenting the patients’ vaccination status is critical to decreasing unnecessary follow-up imaging, biopsies, and patient’s anxiety.Discussion and Conclusion: Our proposal can help reduce patient anxiety, provider burden, and costs of unnecessary evaluation of enlarged lymph nodes in the setting of recent COVID-19 vaccination. Further, it can avoid delays in vaccination and breast cancer screening during the COVID-19 pandemic.
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Objective@#To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis. @*Materials and Methods@#Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies. @*Results@#Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86–0.93) and 0.90 (95% CI 0.84–0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68–0.83) and 0.83 (95% CI 0.73–0.89), respectively, for DM alone (p < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93–0.97) for DBT and 0.86 (95% CI 0.82–0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses. @*Conclusion@#Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.
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Objective@#To compare the screening performance of diffusion-weighted (DW) MRI and combined mammography and ultrasound (US) in detecting clinically occult contralateral breast cancer in women with newly diagnosed breast cancer. @*Materials and Methods@#Between January 2017 and July 2018, 1148 women (mean age ± standard deviation, 53.2 ± 10.8 years) with unilateral breast cancer and no clinical abnormalities in the contralateral breast underwent 3T MRI, digital mammography, and radiologist-performed whole-breast US. In this retrospective study, three radiologists independently and blindly reviewed all DW MR images (b = 1000 s/mm2 and apparent diffusion coefficient map) of the contralateral breast and assigned a Breast Imaging Reporting and Data System category. For combined mammography and US evaluation, prospectively assessed results were used. Using histopathology or 1-year follow-up as the reference standard, cancer detection rate and the patient percentage with cancers detected among all women recommended for tissue diagnosis (positive predictive value; PPV2) were compared. @*Results@#Of the 30 cases of clinically occult contralateral cancers (13 invasive and 17 ductal carcinoma in situ [DCIS]), DW MRI detected 23 (76.7%) cases (11 invasive and 12 DCIS), whereas combined mammography and US detected 12 (40.0%, five invasive and seven DCIS) cases. All cancers detected by combined mammography and US, except two DCIS cases, were detected by DW MRI. The cancer detection rate of DW MRI (2.0%; 95% confidence interval [CI]: 1.3%, 3.0%) was higher than that of combined mammography and US (1.0%; 95% CI: 0.5%, 1.8%; p = 0.009). DW MRI showed higher PPV2 (42.1%; 95% CI: 26.3%, 59.2%) than combined mammography and US (18.5%; 95% CI: 9.9%, 30.0%; p = 0.001). @*Conclusion@#In women with newly diagnosed breast cancer, DW MRI detected significantly more contralateral breast cancers with fewer biopsy recommendations than combined mammography and US.
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Objective@#To compare the performance of simulated abbreviated breast MRI (AB-MRI) and full diagnostic (FD)-MRI in distinguishing between benign and malignant lesions detected by MRI and investigate the features of discrepant lesions of the two protocols. @*Materials and Methods@#An AB-MRI set with single first postcontrast images was retrospectively obtained from an FD-MRI cohort of 111 lesions (34 malignant, 77 benign) detected by contralateral breast MRI in 111 women (mean age, 49.8. ± 9.8;range, 28–75 years) with recently diagnosed breast cancer. Five blinded readers independently classified the likelihood of malignancy using Breast Imaging Reporting and Data System assessments. McNemar tests and area under the receiver operating characteristic curve (AUC) analyses were performed. The imaging and pathologic features of the discrepant lesions of the two protocols were analyzed. @*Results@#The sensitivity of AB-MRI for lesion characterization tended to be lower than that of FD-MRI for all readers (58.8– 82.4% vs. 79.4–100%), although the findings of only two readers were significantly different (p 0.05). Fifteen percent (5/34) of the cancers were false-negatives on AB-MRI. More suspicious margins or internal enhancement on the delayed phase images were related to the discrepancies. @*Conclusion@#The overall performance of AB-MRI was similar to that of FD-MRI in distinguishing between benign and malignant lesions. AB-MRI showed lower sensitivity and higher specificity than FD-MRI, as 15% of the cancers were misclassified compared to FD-MRI.
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Objective@#To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis. @*Materials and Methods@#Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies. @*Results@#Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86–0.93) and 0.90 (95% CI 0.84–0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68–0.83) and 0.83 (95% CI 0.73–0.89), respectively, for DM alone (p < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93–0.97) for DBT and 0.86 (95% CI 0.82–0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses. @*Conclusion@#Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.
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Objective@#To compare the screening performance of diffusion-weighted (DW) MRI and combined mammography and ultrasound (US) in detecting clinically occult contralateral breast cancer in women with newly diagnosed breast cancer. @*Materials and Methods@#Between January 2017 and July 2018, 1148 women (mean age ± standard deviation, 53.2 ± 10.8 years) with unilateral breast cancer and no clinical abnormalities in the contralateral breast underwent 3T MRI, digital mammography, and radiologist-performed whole-breast US. In this retrospective study, three radiologists independently and blindly reviewed all DW MR images (b = 1000 s/mm2 and apparent diffusion coefficient map) of the contralateral breast and assigned a Breast Imaging Reporting and Data System category. For combined mammography and US evaluation, prospectively assessed results were used. Using histopathology or 1-year follow-up as the reference standard, cancer detection rate and the patient percentage with cancers detected among all women recommended for tissue diagnosis (positive predictive value; PPV2) were compared. @*Results@#Of the 30 cases of clinically occult contralateral cancers (13 invasive and 17 ductal carcinoma in situ [DCIS]), DW MRI detected 23 (76.7%) cases (11 invasive and 12 DCIS), whereas combined mammography and US detected 12 (40.0%, five invasive and seven DCIS) cases. All cancers detected by combined mammography and US, except two DCIS cases, were detected by DW MRI. The cancer detection rate of DW MRI (2.0%; 95% confidence interval [CI]: 1.3%, 3.0%) was higher than that of combined mammography and US (1.0%; 95% CI: 0.5%, 1.8%; p = 0.009). DW MRI showed higher PPV2 (42.1%; 95% CI: 26.3%, 59.2%) than combined mammography and US (18.5%; 95% CI: 9.9%, 30.0%; p = 0.001). @*Conclusion@#In women with newly diagnosed breast cancer, DW MRI detected significantly more contralateral breast cancers with fewer biopsy recommendations than combined mammography and US.
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Axillary ultrasonography (US) is the most commonly used imaging modality for nodal evaluation in patients with breast cancer. No Axillary Surgical Treatment in Clinically Lymph Node-Negative Patients after Ultrasonography (NAUTILUS) is a prospective, multicenter, randomized controlled trial investigating whether sentinel lymph node biopsy (SLNB) can be safely omitted in patients with clinically and sonographically node-negative T1–2 breast cancer treated with breast-conserving therapy. In this trial, a standardized imaging protocol and criteria were established for the evaluation of axillary lymph nodes. Women lacking palpable lymph nodes underwent axillary US to dismiss suspicious nodal involvement.Patients with a round hypoechoic node with effaced hilum or indistinct margins were excluded. Patients with T1 tumors and a single node with a cortical thickness ≥ 3 mm underwent US-guided biopsy. Finally, patients with negative axillary US findings were included. The NAUTILUS axillary US nodal assessment criteria facilitate the proper selection of candidates who can omit SLNB.
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Objective@#To evaluate the clinical utility of ultrafast dynamic contrast-enhanced (DCE)-MRI compared to conventional DCEMRIby studying lesion conspicuity and size according to the level of background parenchymal enhancement (BPE). @*Materials and Methods@#This study included 360 women (median age, 54 years; range, 26–82 years) with 361 who had undergonebreast MRI, including both ultrafast and conventional DCE-MRI before surgery, between January and December 2017. Conspicuitywas evaluated using a five-point score. Size was measured as the single maximal diameter. The Wilcoxon signed-rank test wasused to compare median conspicuity score. To identify factors associated with conspicuity, multivariable logistic regressionwas performed. Absolute agreement between size at MRI and histopathologic examination was assessed using the intraclasscorrelation coefficient (ICC). @*Results@#The median conspicuity scores were 5 at both scans, but the interquartile ranges were significantly different (5-5 atultrafast vs. 4-5 at conventional, p < 0.001). Premenopausal status (odds ratio [OR] = 2.2, p = 0.048), non-mass enhancement(OR = 4.1, p = 0.001), moderate to marked BPE (OR = 7.5, p < 0.001), and shorter time to enhancement (OR = 0.9, p =0.043) were independently associated with better conspicuity at ultrafast scans. Tumor size agreement between MRI andhistopathologic examination was similar for both scans (ICC = 0.66 for ultrafast vs. 0.63 for conventional). @*Conclusion@#Ultrafast DCE-MRI could improve lesion conspicuity compared to conventional DCE-MRI, especially in womenwith premenopausal status, non-mass enhancement, moderate to marked BPE or short time to enhancement.
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Objective@#To compare the utility and diagnostic performance of automated breast ultrasound system (ABUS) with that of handheld ultrasound (HHUS) in evaluating pure non-mass enhancement (NME) lesions on breast magnetic resonance imaging (MRI). @*Materials and Methods@#One hundred twenty-six consecutive MRI-visible pure NME lesions of 122 patients with breast cancer were assessed from April 2016 to March 2017. Two radiologists reviewed the preoperative breast MRI, ABUS, and HHUS images along with mammography (MG) findings. The NME correlation rate and diagnostic performance of ABUS were compared with that of HHUS, and the imaging features associated with ABUS visibility were analyzed. @*Results@#Among 126 pure NME lesions, 100 (79.4%) were malignant and 26 (20.6%) were benign. The overall correlation rate was 87.3% (110/126) in ABUS and 92.9% (117/126) in HHUS. The sensitivity and specificity were 87% and 50% for ABUS and 92% and 42.3% for HHUS, respectively, with no significant differences (p = 0.180 and 0.727, respectively). Malignant NME was more frequently visualized than benign NME lesions on ABUS (93% vs. 65.4%, p = 0.001). Significant factors associated with the visibility of ABUS were the size of NME lesions on MRI (p < 0.001), their distribution pattern (p < 0.001), and microcalcifications on MG (p = 0.027). @*Conclusion@#ABUS evaluation of pure NME lesions on MRI in patients with breast cancer is a useful technique with high visibility, especially in malignant lesions. The diagnostic performance of ABUS was comparable with that of conventional HHUS in evaluating NME lesions.
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0.05).CONCLUSION: 2-VST of ABUS achieved comparable scan coverage and diagnostic performance to that of conventional 3-VST in women with small breasts.
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Feminino , Humanos , Neoplasias da Mama , Mama , Sensibilidade e Especificidade , UltrassonografiaRESUMO
OBJECTIVE: To compare digital breast tomosynthesis (DBT) and conventional full-field digital mammography (FFDM) in the detectability of breast cancers in patients with dense breast tissue, and to determine the influencing factors in the detection of breast cancers using the two techniques. MATERIALS AND METHODS: Three blinded radiologists independently graded cancer detectability of 300 breast cancers (288 women with dense breasts) on DBT and conventional FFDM images, retrospectively. Hormone status, histologic grade, T stage, and breast cancer subtype were recorded to identify factors affecting cancer detectability. The Wilcoxon signed-rank test was used to compare cancer detectability by DBT and conventional FFDM. Fisher's exact tests were used to determine differences in cancer characteristics between detectability groups. Kruskal-Wallis tests were used to determine whether the detectability score differed according to cancer characteristics. RESULTS: Forty breast cancers (13.3%) were detectable only with DBT; 191 (63.7%) breast cancers were detected with both FFDM and DBT, and 69 (23%) were not detected with either. Cancer detectability scores were significantly higher for DBT than for conventional FFDM (median score, 6; range, 0–6; p < 0.001). The DBT-only cancer group had more invasive lobular-type breast cancers (22.5%) than the other two groups (i.e., cancer detected on both types of image [both-detected group], 5.2%; cancer not detected on either type of image [both-non-detected group], 7.3%), and less detectability of ductal carcinoma in situ (5% vs. 16.8% [both-detected group] vs. 27.5% [both-non-detected group]). Low-grade cancers were more often detected in the DBT-only group than in the both-detected group (22.5% vs. 10%, p = 0.026). Human epidermal growth factor receptor-2 (HER-2)-negative cancers were more often detected in the DBT-only group than in the both-detected group (92.3% vs. 70.5%, p = 0.004). Cancers surrounded by mostly glandular tissue were detected less often in the DBT only group than in the both-non-detected group (10% vs. 31.9%, p = 0.016). DBT cancer detectability scores were significantly associated with cancer type (p = 0.012), histologic grade (p = 0.013), T and N stage (p = 0.001, p = 0.024), proportion of glandular tissue surrounding lesions (p = 0.013), and lesion type (p < 0.001). CONCLUSION: Invasive lobular, low-grade, or HER-2-negative cancer is more detectable with DBT than with conventional FFDM in patients with dense breasts, but cancers surrounded by mostly glandular tissue might be missed with both techniques.
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Feminino , Humanos , Neoplasias da Mama , Mama , Carcinoma Intraductal não Infiltrante , Fator de Crescimento Epidérmico , Mamografia , Estudos RetrospectivosRESUMO
PURPOSE@#This study was designed to verify the effectiveness of Mastocheck, a new diagnostic tool developed with proteomics techniques using plasma proteins. In addition, checked the current state of mammography used for breast cancer screening.@*METHODS@#A total of 305 cases were analyzed (normal 122, breast cancer 183) and used for validation after Mastocheck development. First, screening mammograms of normal patients and pre-diagnosis mammography of cancer patients were reviewed retrospectively. The results were compared with Mastocheck, a newly developed blood test. Imaging tests were blinded and analyzed by dividing the readings of breast specialists and non-breast specialists among radiologists. We confirmed how much better the results would be if only the mammography was used and if both tests were used together.@*RESULTS@#The sensitivity, specificity, and accuracy of mammography alone, reviewed by non-breast specialists among radiologists, were 63.0%, 85.7%, and 71.3%, respectively. In dense breasts, the values were 59.2%, 84.8% and 69.0%, which were too low to be considered interpretable. The sensitivity, specificity and accuracy of the test was 93.9%, 83.8%, and 90.2% when using mammography and Mastocheck together. From these results, an improvement in sensitivity of about 30% and an improvement in accuracy of about 15% or more in concomitant use than mammography alone can be seen.@*CONCLUSION@#Mastocheck can be widely used for screening breast cancer, especially in dense breasts, patients with low accuracy in mammography, and patients with mammography side effects. In addition, it has the advantage of increasing the diagnosis rate when used with mammography, the current screening method of choice.
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This article was initially published on the Journal of Breast Cancer with a misspelled the grant number.
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PURPOSE: The aim of our study was to investigate the characteristics of primary and recurrent breast cancers and the correlation between cancer subtypes and detection modes. METHODS: Between 2003 and 2013, 147 cases of recurrent breast cancer in 137 women (mean age, 45.30±10.78 years) were identified via an annual clinical examination using radiological studies among 6,169 patients with a breast cancer history (mean follow-up period, 13.26±1.78 years). Clinical, radiological, and pathological findings including immunohistochemistry findings of primary and recurrent cancers were reviewed. The size of the tumor in primary and recurrent cancers, disease-free survival, methods of surgery, and the recurrence detection modalities were analyzed with respect to the breast cancer subtype. RESULTS: Ipsilateral and contralateral in-breast recurrence occurred in 105, 21 had axillary lymph node recurrence, and 21 had chest wall recurrences. The subtypes of the primary cancers were hormone receptor (HR) positive and human epidermal growth factor receptor 2 (HER2) negative (HR+HER2−) in 57, HER2 positive (HER2+) in 39, and triple-negative type in 51, and the recurrent cancers in each subtype showed the same type as the primary cancer in 84.3% of cases. In the in-breast recurrent cancers, the HR+HER2− cancers were most frequently detected using ultrasonography (15/43) followed by mammography (MG) (11/43). The HER2+ recurrent cancers were most commonly detected using MG (14/31, 45.2%), whereas triple-negative type recurrent cancers most commonly presented as symptomatic masses (15/31) (p=0.028). CONCLUSION: Most recurrent breast cancers showed the same cancer subtype as the primary tumor, and recurrent breast cancer subtypes correlated with the detection modality. Imaging surveillance of survivors of breast cancer might be more beneficial in cases of HR+HER2− type breast cancer or HER2+ type breast cancer than in cases of triple-negative type breast cancer.