Global evidence for joint effects of multiple natural and anthropogenic drivers on soil nitrogen cycling.

Global soil nitrogen (N) cycling remains poorly understood due to its complex driving mechanisms. Here, we present a comprehensive analysis of global soil δ15N, a stable isotopic signature indicative of the N input-output balance, using a machine-learning approach on 10,676 observations from 2670 sites. Our findings reveal prevalent joint effects of climatic conditions, plant N-use strategies, soil properties, and other natural and anthropogenic forcings on global soil δ15N. The joint effects of multiple drivers govern the latitudinal distribution of soil δ15N, with more rapid N cycling at lower latitudes than at higher latitudes. In contrast to previous climate-focused models, our data-driven model more accurately simulates spatial changes in global soil δ15N, highlighting the need to consider the joint effects of multiple drivers to estimate the Earth's N budget. These insights contribute to the reconciliation of discordances among empirical, theoretical, and modeling studies on soil N cycling, as well as sustainable N management.

A predictive model using MRI and clinicopathologic features for breast cancer recurrence in young women treated with upfront surgery.

OBJECTIVES: To identify preoperative breast MR imaging and clinicopathological variables related to recurrence and develop a risk prediction model for recurrence in young women with breast cancer treated with upfront surgery. METHODS: This retrospective study analyzed 438 consecutive women with breast cancer aged 35 years or younger between January 2007 and December 2016. Breast MR images before surgery were independently reviewed by breast radiologists blinded to patient outcomes. The clinicopathological data including patient demographics, clinical features, and tumor characteristics were reviewed. Univariate and multivariate logistic regression analyses were used to identify the independent factors associated with recurrence. The risk prediction model for recurrence was developed, and the discrimination and calibration abilities were assessed. RESULTS: Of 438 patients, 95 (21.7%) developed recurrence after a median follow-up of 65 months. Tumor size at MR imaging (HR = 1.158, p = 0.006), multifocal or multicentric disease (HR = 1.676, p = 0.017), and peritumoral edema on T2WI (HR = 2.166, p = 0.001) were identified as independent predictors of recurrence, while adjuvant endocrine therapy (HR = 0.624, p = 0.035) was inversely associated with recurrence. The prediction model showed good discrimination ability in predicting 5-year recurrence (C index, 0.707 in the development cohort; 0.686 in the validation cohort) and overall recurrence (C index, 0.699 in the development cohort; 0.678 in the validation cohort). The calibration plot demonstrated an excellent correlation (concordance correlation coefficient, 0.903). CONCLUSION: A prediction model based on breast MR imaging and clinicopathological features showed good discrimination to predict recurrence in young women with breast cancer treated with upfront surgery, which could contribute to individualized risk stratification. CLINICAL RELEVANCE STATEMENT: Our prediction model, incorporating preoperative breast MR imaging and clinicopathological features, predicts recurrence in young women with breast cancer undergoing upfront surgery, facilitating personalized risk stratification and informing tailored management strategies. KEY POINTS: Younger women with breast cancer have worse outcomes than those diagnosed at more typical ages. The described prediction model showed good discrimination performance in predicting 5-year and overall recurrence. Incorporating better risk stratification tools in this population may help improve outcomes.

Use of a commercial artificial intelligence-based mammography analysis software for improving breast ultrasound interpretations.

OBJECTIVES: To evaluate the use of a commercial artificial intelligence (AI)-based mammography analysis software for improving the interpretations of breast ultrasound (US)-detected lesions. METHODS: A retrospective analysis was performed on 1109 breasts that underwent both mammography and US-guided breast biopsy. The AI software processed mammograms and provided an AI score ranging from 0 to 100 for each breast, indicating the likelihood of malignancy. The performance of the AI score in differentiating mammograms with benign outcomes from those revealing cancers following US-guided breast biopsy was evaluated. In addition, prediction models for benign outcomes were constructed based on clinical and imaging characteristics with and without AI scores, using logistic regression analysis. RESULTS: The AI software had an area under the receiver operating characteristics curve (AUROC) of 0.79 (95% CI, 0.79-0.82) in differentiating between benign and cancer cases. The prediction models that did not include AI scores (non-AI model), only used AI scores (AI-only model), and included AI scores (integrated model) had AUROCs of 0.79 (95% CI, 0.75-0.83), 0.78 (95% CI, 0.74-0.82), and 0.85 (95% CI, 0.81-0.88) in the development cohort, and 0.75 (95% CI, 0.68-0.81), 0.82 (95% CI, 0.76-0.88), and 0.84 (95% CI, 0.79-0.90) in the validation cohort, respectively. The integrated model outperformed the non-AI model in the development and validation cohorts (p < 0.001 for both). CONCLUSION: The commercial AI-based mammography analysis software could be a valuable adjunct to clinical decision-making for managing US-detected breast lesions. CLINICAL RELEVANCE STATEMENT: The commercial AI-based mammography analysis software could potentially reduce unnecessary biopsies and improve patient outcomes. KEY POINTS: • Breast US has high rates of false-positive interpretations. • A commercial AI-based mammography analysis software could distinguish mammograms having benign outcomes from those revealing cancers after US-guided breast biopsy. • A commercial AI-based mammography analysis software may improve interpretations for breast US-detected lesions.

Mammographic density assessment: comparison of radiologists, automated volumetric measurement, and artificial intelligence-based computer-assisted diagnosis.

BACKGROUND: Artificial intelligence-based computer-assisted diagnosis (AI-CAD) is increasingly used for mammographic exams, and its role in mammographic density assessment should be evaluated. PURPOSE: To assess the inter-modality agreement between radiologists, automated volumetric density measurement program (Volpara), and AI-CAD system in breast density categorization using the Breast Imaging-Reporting and Data System (BI-RADS) density categories. MATERIAL AND METHODS: A retrospective review was conducted on 1015 screening digital mammograms that were performed in Asian female patients (mean age = 56 years ± 10 years) in our health examination center between December 2022 and January 2023. Four radiologists with two different levels of experience (expert and general radiologists) performed density assessments. Agreement between the radiologists, Volpara, and AI-CAD (Lunit INSIGHT MMG) was evaluated using weighted kappa statistics and matched rates. RESULTS: Inter-reader agreement between expert and general radiologists was substantial (k = 0.65) with a matched rate of 72.8%. The agreement was substantial between expert or general radiologists and Volpara (k = 0.64-0.67) with a matched rate of 72.0% but moderate between expert or general radiologists and AI-CAD (k = 0.45-0.58) with matched rates of 56.7%-67.0%. The agreement between Volpara and AI-CAD was moderate (k = 0.53) with a matched rate of 60.8%. CONCLUSION: The agreement in breast density categorization between radiologists and automated volumetric density measurement program (Volpara) was higher than the agreement between radiologists and AI-CAD (Lunit INSIGHT MMG).

Effects of Preoperative Breast MRI on Breast Cancer Survival Outcomes in Women Aged 35 Years and Younger.

Background The impact of preoperative breast MRI on the long-term outcomes in patients with breast cancer who are 35 years and younger has not been established. Purpose To evaluate the impact of preoperative breast MRI on recurrence-free survival (RFS) and overall survival (OS) in women with breast cancer who are 35 years and younger by using propensity score matching. Materials and Methods A total of 708 women who were 35 years and younger (mean age, 32 years ± 3 [SD]) and diagnosed with breast cancer from 2007 to 2016 were retrospectively identified. Patients who underwent preoperative MRI (MRI group) were matched with those who did not (no MRI group) according to 23 patient and tumor characteristics. RFS and OS were compared using the Kaplan-Meier method. Cox proportional hazards regression analysis was used to estimate the hazard ratios (HRs). Results Of 708 women, 125 patient pairs were matched. In the MRI group versus the no MRI group, the mean follow-up time was 82 months ± 32 versus 106 months ± 42, and the rates of total recurrence and death were 22% (104 of 478 patients) versus 29% (66 of 230 patients) and 5% (25 of 478 patients) versus 12% (28 of 230 patients), respectively. The time to recurrence was 44 months ± 33 in the MRI group and 56 months ± 42 in the no MRI group. After propensity score matching, the MRI and no MRI groups did not show significant differences in total recurrence (HR, 1.0; P = .99), local-regional recurrence (HR, 1.3; P = .42), contralateral breast recurrence (HR, 0.7; P = .39), or distant recurrence (HR, 0.9; P = .79). The MRI group showed a tendency toward better OS, but this was not statistically significant (HR, 0.47; P = .07). In the entire unmatched cohort, MRI was not an independent significant factor for predicting RFS or OS. Conclusion Preoperative breast MRI was not a significant prognostic factor for recurrence-free survival in women 35 years and younger with breast cancer. A tendency toward better overall survival was observed in the MRI group, but this was not significant. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kim and Moy in this issue.

Improving mammography interpretation for both novice and experienced readers: a comparative study of two commercial artificial intelligence software.

OBJECTIVES: To evaluate the improvement of mammography interpretation for novice and experienced radiologists assisted by two commercial AI software. METHODS: We compared the performance of two AI software (AI-1 and AI-2) in two experienced and two novice readers for 200 mammographic examinations (80 cancer cases). Two reading sessions were conducted within 4 weeks. The readers rated the likelihood of malignancy (range, 1-7) and the percentage probability of malignancy (range, 0-100%), with and without AI assistance. Differences in AUROC, sensitivity, and specificity were analyzed. RESULTS: Mean AUROC increased in both novice (0.86 to 0.90 with AI-1 [p = 0.005]; 0.91 with AI-2 [p < 0.001]) and experienced readers (0.87 to 0.92 with AI-1 [p < 0.001]; 0.90 with AI-2 [p = 0.004]). Sensitivities increased from 81.3 to 88.8% with AI-1 (p = 0.027) and to 91.3% with AI-2 (p = 0.005) in novice readers, and from 81.9 to 90.6% with AI-1 (p = 0.001) and to 87.5% with AI-2 (p = 0.016) in experienced readers. Specificity did not decrease significantly in both novice (p > 0.999, both) and experienced readers (p > 0.999 with AI-1 and 0.282 with AI-2). There was no significant difference in the performance change depending on the type of AI software (p > 0.999). CONCLUSION: Commercial AI software improved the diagnostic performance of both novice and experienced readers. The type of AI software used did not significantly impact performance changes. Further validation with a larger number of cases and readers is needed. CLINICAL RELEVANCE STATEMENT: Commercial AI software effectively aided mammography interpretation irrespective of the experience level of human readers. KEY POINTS: • Mammography interpretation remains challenging and is subject to a wide range of interobserver variability. • In this multi-reader study, two commercial AI software improved the sensitivity of mammography interpretation by both novice and experienced readers. The type of AI software used did not significantly impact performance changes. • Commercial AI software may effectively support mammography interpretation irrespective of the experience level of human readers.

Assessment of sources variability of riverine particulate organic matter with land use and rainfall changes using a three-indicator (δ13C, δ15N, and C/N) Bayesian mixing model.

In intensive agricultural watersheds, riverine particulate organic matter (POM) may be transported from many sources such as rice paddies, crop uplands, forests, and livestock farming areas during rainy seasons. However, the impacts of land-use and rainfall changes on the POM sources are not well understood. In this study, changes in the sources of riverine POM were investigated in an agricultural area of Korea between 2014 and 2020/21. During this period, land-use and rainfall patterns changed dramatically. The δ13C, δ15N, and C/N of the POM sources as well as those of riverine POM were analyzed, and a stable isotope analysis in R (SIAR) model was utilized for source apportionment. There were differences in δ13C, δ15N, and C/N among the sources. For example, manure had higher δ13C (-22.6 ± 3.3‰) and δ15N (+10.6 ± 5.9‰) than soils (from -28.0 ± 0.8‰ to -25.1 ± 1.2‰ for δ13C and +3.6 ± 1.7‰ to +9.8 ± 1.4‰ for δ15N). For soils, the δ13C and δ15N were higher for upland soils, while C/N was greater for forest soils than for others. For riverine POM, the δ15N marginally changed; however, the δ13C and C/N increased from -26.1 ± 0.9‰ to -20.8 ± 5.3‰ and from +7.7 ± 1.7 to +18.8 ± 8.3 between 2014 and 2020/21, respectively. The SIAR model showed that the contributions of paddy (from 41.0% to 14.9%) and upland fields (from 48.1% to 23.7%) to riverine POM decreased between the periods due to decreased paddy area and the implementation of best management practice on upland fields, respectively. However, the contribution of forests (from 3.5% to 28.0%) and manure (from 7.4% to 33.5%) increased probably due to improper management of forest clear-cutting sites and livestock manure storage sites. The contributions of agricultural soils to riverine POM decreased in drier years. Our study suggests that land management rather than land-use area is critical in riverine POM management, particularly in wetter years.

Tablet-based cognitive behavioral intervention to improve arthritis associated fatigue: A pilot study.

This pilot study evaluated the effect of the tablet-based cognitive behavioral intervention ("Tab-CBI") on daily steps, fatigue, and self-efficacy. Tab-CBI combined simple walking and a cognitive behavioral approach. An experimental pretest-posttest repeated measures design was used with 24 older adults. RM-ANOVA results showed a significant group difference (Tab-CBI vs. Comparison), F (1, 22) = 2.25, p =0.048 and time difference (baseline vs. week 4 vs. week 6), F (2, 44) =5.04, p =0.01 in daily steps. There was no significant group difference, F (1, 22) = 2.99, p =0.09, but significant time difference existed, F (2, 44) =2.65, p =0.04 in the PROMIS Fatigue scores. In the PROMIS Self-efficacy scores, no significant group difference, F (1, 22) = 0.02, p =0.90) was found, but significant time difference existed, F (2, 44) =3.27, p = 0.04. The findings provide preliminary evidence for the positive impact of Tab-CBI, but should be interpreted cautiously.

Preoperative Breast MRI in Women 35 Years of Age and Younger with Breast Cancer: Benefits in Surgical Outcomes by Using Propensity Score Analysis.

Background The role of preoperative MRI in women 35 years of age or younger with breast cancer remains controversial. Purpose To determine the association between preoperative MRI and surgical outcomes in women aged 35 years or younger with breast cancer by using propensity score (PS) analysis to investigate the impact of preoperative MRI. Materials and Methods Women 35 years of age or younger diagnosed with breast cancer between 2007 and 2017 who had or had not undergone preoperative breast MRI were retrospectively identified. The MRI detection rate of additional suspicious lesions was analyzed, and changes in surgical management were recorded. Inverse probability weighting (IPW) and PS matching were used to adjust 19 variables and to create a balance between the two groups. Surgical outcomes were compared by using univariable logistic regression. Results Among 964 women (mean age ± standard deviation, 32 years ± 3), 665 (69%) had undergone preoperative MRI (MRI group; mean age, 32 years ± 3) and 299 (31%) had not (no-MRI group; mean age, 32 years ± 3). In the MRI group, additional suspicious lesions were found in 178 of the 665 women (27%), with 88 of those 178 women (49%) having malignant lesions. The surgical management was changed in 99 of the 665 women (15%) due to MRI findings, which was appropriate for 62 of those 99 women (63%). In the IPW analysis, the MRI group showed lower odds of repeat surgery (odds ratio [OR], 0.13; 95% CI: 0.07, 0.21; P < .001) and higher odds of initial mastectomy (OR, 1.62; 95% CI: 1.17, 2.25; P = .004). However, there was no difference in the overall mastectomy rate (OR, 1.24; 95% CI: 0.91, 1.68; P = .17) compared with the no-MRI group. These results were consistent when using the PS matching method. Conclusion Preoperative MRI in young women with breast cancer is useful for detecting additional malignancy and improving surgical outcomes by reducing the repeat surgery rate, with a similar likelihood of overall mastectomy. © RSNA, 2021 Online supplemental material is available for this article.

Calcifications with suspicious morphology at mammography: should they all be considered with the same clinical significance?

OBJECTIVES: To evaluate the positive predictive values (PPVs) of calcifications with suspicious morphology by incorporating distribution and clinical factors in two separate cohorts to provide more practical guidance for management. METHODS: This retrospective study included 1076 consecutive women from two cohorts (cohort A, 556; cohort B, 520), with calcifications of suspicious morphology seen on mammography that were pathologically confirmed or followed with mammography. Reader-averaged PPVs of the calcifications were analyzed and compared by logistic regression using the generalized estimating equation. Multivariate logistic regression analysis was performed to evaluate independent factors associated with the PPVs of suspicious calcifications. RESULTS: Overall reader-averaged PPVs of suspicious calcifications were 16.8% and 15.2% in cohort A and B, respectively. Reader-averaged PPVs according to morphology in cohort A and B were as follows: amorphous 9.1%, 6.4%; coarse heterogeneous 16.1%, 22.1%; fine pleomorphic 78.8%, 44.7%; and fine linear branching 78.6%, 85.1%, respectively (p < 0.001). PPVs for diffuse amorphous combinations were 2.6% and 2.6%, and for regional amorphous calcifications, 3.6% and 3.1%, respectively. Among diffuse amorphous calcifications, the PPVs for women ≥ 50 years and women without a personal history of breast cancer ranged from 0.0 to 1.9%. CONCLUSIONS: Amorphous calcifications have lower reader-averaged PPVs compared to calcifications with other suspicious morphology, falling into the BI-RADS 4a assessment (PPV 2-10%). Amorphous calcifications with diffuse distributions detected in women > 50 years old and without a personal history of breast cancer have reader-averaged PPVs < 2.0%. Further prospective studies are necessary to confirm if these patients can be managed with imaging follow-up. KEY POINTS: • In two cohorts, reader-averaged positive predictive values (PPVs) for suspicious calcifications showed lower rates for amorphous calcifications. • In two separate cohorts, reader-averaged PPVs showed lower rates for diffuse amorphous calcifications, falling into the BI-RADS 4a assessment category (PPV 2-10%). • Diffuse amorphous calcifications detected in women > 50 years old and without a personal history of breast cancer have reader-averaged PPVs < 2.0%.

Automated breast US as the primary screening test for breast cancer among East Asian women aged 40-49 years: a multicenter prospective study.

OBJECTIVES: To prospectively evaluate the diagnostic performance of screening ABUS as the primary screening test for breast cancer among Korean women aged 40-49 years. METHODS: This prospective, multicenter study included asymptomatic Korean women aged 40-49 years from three academic centers between February 2017 and October 2019. Each participant underwent ABUS without mammography, and the ABUS images were interpreted at each hospital with double-reading by two breast radiologists. Biopsy and at least 1 year of follow-up was considered the reference standard. Diagnostic performance of ABUS screening and subgroup analyses according to patient and tumor characteristics were evaluated. RESULTS: Reference standard data were available for 959 women. The recall rate was 9.8% (95% confidence interval [CI]: 7.9%, 11.7%; 94 of 959 women) and the cancer detection yield was 5.2 per 1000 women (95% CI: -0.6, 11.1; 5 of 959 women). There was only one interval cancer. The sensitivity was 83.3% (95% CI: 53.5%, 100%; 5 of 6 cancers) and the specificity was 90.7% (95% CI: 88.8%, 92.5%; 864 of 95. women). The positive predictive values of biopsies performed (PPV3) was 20.0% (95% CI: 4.3%, 35.7%; 5 of 25 women). Women with heterogeneous background echotexture had a higher recall rate (p = .009) and lower specificity (p = .036). Women with body mass index values < 25 kg/m2 had a higher mean recall rate (p = .046). CONCLUSION: In East Asia, screening automated breast US may be an alternative to screening mammography for detecting breast cancers in women aged 40-49 years. KEY POINTS: • Automated breast US screening for breast cancer in asymptomatic women aged 40-49 is effective with 5.2 per 1000 cancer detection yield. • Women with heterogeneous background echotexture had a higher recall rate and lower specificity. • Women with body mass index < 25 kg/m2 had a higher recall rate.

Association of mammography and ultrasound features with MammaPrint in patients with estrogen receptor-positive, HER2-negative, node-positive invasive breast cancer.

BACKGROUND: MammaPrint is a 70-gene signature microarray assay that predicts the likelihood of recurrence of breast cancer and chemotherapeutic benefits. PURPOSE: To investigate the association between mammography and ultrasound (US) features and MammaPrint results in patients with estrogen receptor (ER)-positive, HER2-negative, node-positive invasive breast cancer, and to identify the predictive factors for high risk of recurrence. MATERIAL AND METHODS: This retrospective study included 251 patients with ER-positive, HER2-negative, 1-3 node-positive invasive breast cancer. Mammography and US findings were reviewed according to the BI-RADS criteria. The association between MammaPrint results and the clinicopathological and imaging features was evaluated. Logistic regression analysis was performed to identify independent predictors for high risk of recurrence. RESULTS: Of the patients, 143 (57.0%) and 108 (43.0%) had low and high risks for recurrence on MammaPrint, respectively. Young age (odds ratio [OR] 1.08; 95% confidence interval (CI) 1.04-1.12; P<0.001), posterior enhancement on US (OR 2.45; 95% CI 1.16-5.20; P = 0.019), absence of posterior shadowing on US (OR 3.19; 95% CI 1.17-8.62; P = 0.023), high histologic grade (OR 113.36; 95% CI 6.79-1893.53; P = 0.001), and high Ki-67 level (OR 4.90; 95% CI 2.62-9.17; P<0.001) were independently associated with high risk of recurrence on multivariate logistic regression analysis. CONCLUSION: Posterior features in US may predict a high risk of recurrence in patients with ER-positive, HER2-negative, node-positive invasive breast cancer, which may be useful in enhancing the diagnostic value of MammaPrint and aid in the decision-making process regarding treatment.

Analysis of false-negative findings of breast cancer on previous magnetic resonance imaging.

BACKGROUND: Despite the excellent contribution of contrast-enhanced breast magnetic resonance imaging (MRI), there are variable false-negative cases on MRI. PURPOSE: To evaluate the false-negative findings of breast cancer on previous MRI. MATERIAL AND METHODS: Between 2012 and 2016, we collected 132 patients who underwent surgery for a second primary cancer and had both current and previous MRI at an interval of <3 years. We included 45 patients; we excluded 38 patients who could not find a second cancer in the previous MRI and 49 patients who had a second cancer near to the original cancer and within within the same quadrant. Compared with current MRI, we retrospectively assessed the second primary cancer on previous MRI according to BI-RADS and analyzed the reasons of misinterpretation. RESULTS: Analysis of previous MRI revealed 26 (57.8%) masses (mean size 7.7 ± 2.25 mm), 12 (26.7%) non-mass enhancements (mean size 14.7 ± 4.76 mm), and 7 (15.5%) foci. At first reading, 24 (53.3%) were missed, 17 (37.8%) were assessed as BI-RADS category 2 or 3, and 4 (8.9%) were assessed as category 4. On current MRI, 39 (86.7%) lesions showed an increase in size and 22 (48.9%) showed a change in kinetics to wash-out pattern. CONCLUSION: On previous MRI, missed or misinterpreted cancers show variable findings of mass and non-mass enhancements with any types of kinetics. Careful application of BI-RADS is necessary as well as an appropriate biopsy. Any lesion that increases in size and changes in kinetics should not be underestimated.

Added Value of the Vascular Index on Superb Microvascular Imaging for the Evaluation of Breast Masses: Comparison With Grayscale Ultrasound.

OBJECTIVES: To evaluate the value of the vascular index (VI) on Superb Microvascular Imaging (SMI; Canon Medical Systems Corporation, Tokyo, Japan) in comparison with grayscale ultrasound (US) alone for assessing breast masses. METHODS: We evaluated a total of 70 breast masses (36 malignant and 34 benign lesions) in 70 consecutive patients using grayscale US and SMI. Two breast radiologists analyzed grayscale US alone and the combination of grayscale US and SMI. They also measured the VI based on SMI. The diagnostic performance of grayscale US alone and the combination of grayscale US and SMI was compared. The VI was compared between benign and malignant masses, and the optimal cutoff value was determined. In addition, the interobserver agreement in imaging analyses and the VI was assessed. RESULTS: The interobserver agreements in imaging analyses and the VI were almost perfect. The VI of malignant breast masses was significantly higher than that of benign lesions (P < .001). The optimal cutoff value of the VI for differentiating between malignant and benign breast masses was 2.95, with sensitivity of 86.1% and specificity of 91.2%. The diagnostic performance values of grayscale US alone and the combination of grayscale US and SMI were 0.824 and 0.912, respectively, for reader 1 (P = .028) and 0.795 and 0.853 for reader 2 (P = .101). CONCLUSIONS: The VI on SMI was significantly higher for malignant breast masses than for benign lesions, with high interobserver agreement. Our study suggests that the combination of grayscale US and SMI with the VI could improve the characterization of breast masses.

Surgical Outcomes for Ductal Carcinoma in Situ: Impact of Preoperative MRI.

Background The role of preoperative MRI for predicting surgical outcomes in patients diagnosed with ductal carcinoma in situ (DCIS) remains uncertain. Purpose To investigate the associations between preoperative MRI and surgical outcomes in DCIS confirmed by using US-guided core-needle biopsy (CNB) and to evaluate clinical-pathologic variables associated with a benefit from MRI. Materials and Methods Women with DCIS confirmed by using US-guided CNB between January 2012 and December 2016 were included in this retrospective study. Propensity score matching using 18 confounding covariates was used to create matched groups with MRI and without MRI, and surgical outcomes were compared. Clinical-pathologic variables were evaluated to determine women who benefited from MRI. Results A total of 541 women (mean age ± standard deviation, 50 years ± 10) were evaluated. Among 430 women who underwent MRI, 67 additional lesions (16%) were depicted, with 25 (37%) of the 67 additional lesions being malignant. Fifty-seven (13%) of the 430 women had a change in surgical plan because of their MRI findings; the change was appropriate for 31 (54%) women. In matched groups, the MRI group was associated with lower odds of positive resection margin (odds ratio [OR], 0.39; 95% confidence interval [CI]: 0.16, 0.93; P = .03) and repeat surgery (OR, 0.33; 95% CI: 0.12, 0.92; P = .03) compared with the non-MRI group. There was no difference in likelihood of initial mastectomy (OR, 1.2; 95% CI: 0.7, 2.0; P = .59) and overall mastectomy (OR, 0.93; 95% CI: 0.5, 1.6; P = .79). In the MRI group, low nuclear grade (90% [28 of 31] vs 69% [275 of 399]; P = .01), progesterone receptor positivity (81% [25 of 31] vs 61% [244 of 399]; P = .03), and human epidermal growth factor receptor 2 negativity (90% [28 of 31] vs 68% [270 of 399]; P = .01) were associated with a benefit from MRI versus no MRI. Conclusion Preoperative MRI depicted additional malignancy and reduced positive surgical margins and repeat surgery for ductal carcinoma in situ confirmed at US-guided biopsy without a higher mastectomy rate. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Pinker in this issue.

Male patients with unilateral breast symptoms: an optimal imaging approach.

OBJECTIVES: To evaluate the usefulness of bilateral mammography in male patients with unilateral breast symptoms, including investigation of the diagnostic performance of unilateral and bilateral reviews and the average glandular dose (AGD) per exposure. METHODS: Two hundred seventy-one consecutive male patients (mean age, 57 years) with unilateral breast symptoms underwent bilateral mammography. Image interpretation was performed in two ways, first with a unilateral review of the symptomatic breast and then with a bilateral review. A modified BI-RADS scale (from 1 to 5) was used. The diagnostic performance of unilateral and bilateral reviews was compared, and contralateral breast abnormalities and the AGD per exposure were recorded. We also analyzed ultrasound (US) results and compared them with mammography. RESULTS: Of 271 male patients, 29 were pathologically diagnosed with breast cancer. There was no bilateral breast cancer. The sensitivity, specificity, positive and negative predictive values, and accuracy were 96.6%, 96.7%, 77.8%, 99.6%, and 96.7%, respectively, for unilateral review, and 96.6%, 95.9%, 73.7%, 99.6%, and 95.9% for bilateral review. Receiver operator characteristic analysis showed excellent diagnostic performance for both methods: the area under the curve (AUC) was 0.966 for unilateral review and 0.962 for bilateral review (p = 0.415). The mean AGD per exposure was 1.10 ± 0.29 mGy for symptomatic breast and 1.04 ± 0.30 mGy for contralateral breast (p < 0.001). Diagnostic performance parameters of US were not significantly different from bilateral or unilateral review of mammography. CONCLUSION: The diagnostic performance of unilateral mammography is comparable with bilateral mammography in male patients with unilateral breast symptoms. Unilateral mammography also has the advantage of reducing radiation exposure. KEY POINTS: • There is limited knowledge about standardized guidelines or recommendations for imaging the male breast. • Unilateral mammography for male patients with unilateral breast symptoms showed comparable diagnostic performance with bilateral mammography. • Both unilateral and bilateral mammography showed excellent diagnostic performance in the assessment of male patients with unilateral breast symptoms.

The role of MRI and clinicopathologic features in predicting the invasive component of biopsy-confirmed ductal carcinoma in situ.

BACKGROUND: The upgrade rate of biopsy-confirmed ductal carcinoma in situ (DCIS) to invasive carcinoma is up to 50% on final pathology. We investigated MRI and clinicopathologic predictors of the invasive components of DCIS diagnosed by preoperative biopsy and then compared MRI features between patients with DCIS, microinvasive ductal carcinoma (mIDC), and invasive ductal carcinoma (IDC) diagnosed on final pathology. METHODS: Two hundred and one patients with 206 biopsy-confirmed DCIS lesions were enrolled. MRI and clinicopathologic features were used to predict either mIDC or IDC via a cumulative logistic regression analysis. For the lesions detected on MRI, morphologic and kinetic analyses were performed using the Chi-square, Fisher's exact, and Kruskal-Wallis tests. RESULTS: Of all the lesions, 112 (54.4%) were diagnosed as DCIS, 50 (24.3%) were upgraded to mIDC, and 44 (21.4%) to IDC. The detection on MRI as mass (Odds ratio (OR) = 8.84, 95% confidence interval (CI) = 1.05-74.04, P = 0.045) or non-mass enhancement (NME; OR = 11.17, 95% CI = 1.35-92.36, P = 0.025), negative progesterone receptor (PR; OR = 2.40, 95% CI = 1.29-4.44, P = 0.006), and high Ki-67 level (OR = 2.42, 95% CI = 1.30-4.50, P = 0.005) were significant independent predictors of histologic upgrade. On MRI, 87 (42.2%) lesions appeared as mass and 107 (51.9%) as NME. Irregularly shaped, not-circumscribed, heterogeneous, or rim-enhancing masses with intratumoral high signal intensity or peritumoral edema, clumped or clustered ring-enhancing NMEs, and high peak enhancement were significantly associated with histologic upgrade (P < 0.001). CONCLUSION: MRI detection, negative PR, and high Ki-67 levels are associated with a histologic upgrade in patients with biopsy-confirmed DCIS. Suspicious MRI features are more frequent in such patients.

Diagnostic performance of standard breast MR imaging compared to dedicated axillary MR imaging in the evaluation of axillary lymph node.

BACKGROUND: Breast magnetic resonance (MR) imaging does not usually assess axillary lymph nodes -using dedicated axillary sequence. The additional utility of dedicated axillary sequence is poorly understood. We evaluated the diagnostic performance of dedicated axillary imaging sequence for evaluation of axillary lymph node. METHODS: In this retrospective study from January 2018 to March 2018, 750 consecutive women underwent breast MR imaging. 263 patients were excluded, due to neoadjuvant chemotherapy (n = 235), incomplete histopathological information (n = 14) and follow-up loss (n = 14), 487 women were included. Two radiologists scored lymph node on confidence level scale from 0 (definitely benign) to 4 (definitely malignant), -using standard MR and dedicated axillary imaging sequences. Diagnostic performance parameters were compared and calculated correlation coefficient of quantitative features (largest dimension, cortical thickness, and the ratio of cortical thickness to largest dimension of lymph node). RESULTS: 68 (14.0%) were node-positive and 419 (86.0%) were node-negative. The sensitivity, specificity, positive, negative predictive values and accuracy were respectively, 66.2, 93.3, 61.6, 94.4, and 89.5% for dedicated axillary sequence and 64.7, 94.0, 63.8, 94.3, 89.9% for standard MR sequence The dedicated axillary and standard sequences s did not exhibit significant differences in detection of positive lymph nodes (AUC, 0.794 for standard and 0.798 for dedicated axillary sequence, P = 0.825). The cortical thickness appeared to be the most discriminative quantitative measurement using both axillary (AUC, 0.846) and standard sequences (AUC, 0.823), with high correlation coefficient (0.947). CONCLUSION: Evaluation of axillary nodal status using standard breast MR imaging is comparable to dedicated axillary MR imaging.

Diagnostic accuracy and safety of 16α-[18F]fluoro-17ß-oestradiol PET-CT for the assessment of oestrogen receptor status in recurrent or metastatic lesions in patients with breast cancer: a prospective cohort study.

BACKGROUND: A biopsy of first recurrence or metastatic disease is recommended to re-evaluate oestrogen receptor status in patients with breast cancer and to select appropriate treatment. However, retesting for oestrogen receptor status with rebiopsy is not always feasible, depending on lesion location and the risk associated with biopsy, and in these cases clinicians continue to treat patients according to the oestrogen receptor status of the primary tumour. Consequently suboptimal therapy might be offered to these patients. We assessed the diagnostic accuracy and safety of 16α-[18F]fluoro-17ß-oestradiol (18F-FES) PET-CT to assess oestrogen receptor status in patients with recurrent or metastatic breast cancer. METHODS: We did a prospective cohort study at the Asan Medical Center, Seoul, South Korea. Eligible patients had breast cancer, with first recurrence or metastatic disease at presentation, were 19 years or older, and had an Eastern Cooperative Oncology Group performance status of 0-2. The primary objective was to show the agreement between qualitative 18F-FES PET-CT interpretation and the results of oestrogen receptor expression by immunohistochemical assay, a non-reference standard test. Whole-body 18F-FES PET-CT imaging was done after intravenous injection of 111-222 MBq of 18F-FES, with dosing primarily determined by radiation dosimetry analysis. 18F-FES uptake above background intensity was interpreted as positive. Efficacy was assessed in all patients with histologically confirmed recurrent or metastatic breast cancer who received 18F-FES and had PET-CT images available (intention-to-diagnose analysis), and safety was assessed in all patients who received 18F-FES. This study is registered with ClinicalTrials.gov, number NCT01986569. FINDINGS: Between Nov 27, 2013, and Nov 10, 2016, 93 patients were enrolled. Of the 85 patients included in the efficacy analysis, 47 (55%) were oestrogen receptor-positive and 38 (45%) were oestrogen receptor-negative. Positive status percent agreement between the 18F-FES PET-CT results and oestrogen receptor status by immunohistochemical assay was 76·6% (95% CI 62·0-87·7) and the negative status percent agreement was 100·0% (90·8-100·0). Patients who were oestrogen receptor-positive and had a positive 18F-FES PET-CT result had a significantly higher progesterone receptor expression than those who were oestrogen receptor-positive and had a negative 18F-FES PET-CT result (23 [68%] of 34 patients vs 0 of 11 patients; p<0·0001). The most common adverse event was procedural pain in nine (10%) of 90 patients injected with 18F-FES. No adverse events were related to the study drug except injection site pain in one (1%) patient. No serious adverse events were recorded. INTERPRETATION: The high negative percent agreement between 18F-FES PET-CT and oestrogen receptor status by immunohistochemical assay in this cohort suggests that positive 18F-FES uptake by recurrent or metastatic oestrogen receptor-positive breast cancer lesions could be an alternative to oestrogen receptor assays in this setting. Staging assessment should include 18F-FES PET-CT when retesting oestrogen receptor status is not feasible. FUNDING: Asan Institute for Life Sciences, Ministry of Health and Welfare, South Korea.

Mammography, US, and MRI to Assess Outcomes of Invasive Breast Cancer with Extensive Intraductal Component: A Matched Cohort Study.

Background An extensive intraductal component (EIC) in breast cancer is an independent risk factor for local recurrence after surgery, especially in young, premenopausal women. Few studies have analyzed long-term outcomes or imaging features of EIC-positive breast cancer. Purpose To assess the prognostic value of EIC on recurrence-free and overall survival in breast cancer and evaluate imaging features of EIC-positive breast cancer by using mammography, US, and MRI. Materials and Methods A retrospective study of 6816 consecutive women with surgically diagnosed invasive breast cancer between January 2007 and December 2012 was performed. After individual matching, women were allocated into either an EIC-positive or an EIC-negative group. Imaging factors associated with prognosis were investigated. The recurrence-free and overall survival rates were compared. Univariable and multivariable analyses were performed to analyze the effect of EIC. Results Among 6136 included women (mean age, 48.9 years ± 9.8), 1800 EIC-positive and 4336 EIC-negative breast cancers were identified. After matching according to EIC presence was performed, 1551 women were allocated into each group. The mean follow-up period was 79.9 months. The local-regional recurrence rate in the EIC-positive group was higher than that in the EIC-negative group (39.4% [63 of 160] vs 25.5% [37 of 145]; P = .001). However, there were no significant differences in total recurrence rate (hazard ratio [HR]: 1.2; 95% confidence interval [CI]: 0.9, 1.4; P = .21) or death (HR: 1.1; 95% CI: 0.8, 1.5; P = .45). EIC was not a significant independent factor for recurrence-free survival (HR: 1.1; 95% CI: 0.9, 1.4; P = .45) or death (HR: 1.1; 95% CI: 0.8, 1.6; P = .44) in multivariable analyses. Calcification and non-mass lesions were more commonly seen at US and MRI in the EIC-positive group than in the EIC-negative group (P < .001). Conclusion The presence of an extensive intraductal component in women with invasive breast cancer did not affect overall survival or recurrence-free survival. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Eby in this issue.