Diagnostic value of synthetic diffusion-weighted imaging on breast magnetic resonance imaging assessment: comparison with conventional diffusion-weighted imaging.

PURPOSE: To compare images generated by synthetic diffusion-weighted imaging (sDWI) with those from conventional DWI in terms of their diagnostic performance in detecting breast lesions when performing breast magnetic resonance imaging (MRI). METHODS: A total of 128 consecutive patients with 135 enhanced lesions who underwent dynamic MRI between 2018 and 2021 were included. The sDWI and DWI signals were compared by three radiologists with at least 10 years of experience in breast radiology. RESULTS: Of the 82 malignant lesions, 91.5% were hyperintense on sDWI and 73.2% were hyperintense on DWI. Of the 53 benign lesions, 71.7% were isointense on sDWI and 37.7% were isointense on DWI. sDWI provides accurate signal intensity data with statistical significance compared with DWI (P < 0.05). The diagnostic performance of DWI and sDWI to differentiate malignant breast masses from benign masses was as follows: sensitivity 73.1% [95% confidence interval (CI): 62-82], specificity 37.7% (95% CI: 24-52); sensitivity 91.5% (95% CI: 83-96), specificity 71.7% (95% CI: 57-83), respectively. The diagnostic accuracy of DWI and sDWI was 59.2% and 83.7%, respectively. However, when the DWI images were evaluated with apparent diffusion coefficient mapping and compared with the sDWI images, the sensitivity was 92.68% (95% CI: 84-97) and the specificity was 79.25% (95% CI: 65-89) with no statistically significant difference. The inter-reader agreement was almost perfect (P < 0.001). CONCLUSION: Synthetic DWI is superior to DWI for lesion visibility with no additional acquisition time and should be taken into consideration when conducting breast MRI scans. The evaluation of sDWI in routine MRI reporting will increase diagnostic accuracy.

Diagnostic performance of two versions of an artificial intelligence system in interval breast cancer detection.

BACKGROUND: Various versions of artificial intelligence (AI) have been used as a diagnostic tool aid in the diagnosis of breast cancer. One of the most important problems in breast screening progmrams is interval breast cancer (IBC). PURPOSE: To compare the diagnostic performance of Transpara v1.6 and v1.7 in the detection of IBC. MATERIAL AND METHODS: Reports of screening mammograms of a total 2,248,665 of women were evaluated retrospectively. Of 2,129,486 mammograms reported as Breast Imaging Reporting and Data System (BIRADS) 1 and 2, the IBC group consisted of 323 cases who were diagnosed as having cancer on mammography and were correlated with pathology in second mammogram taken >30 days after first mammogram. Four hundred and forty-one were defined as the control group because they did not change over 2 years. Cancer risk scores of both groups were determined from 1 to 10 with Tranpara v1.6 and v1.7. Diagnostic performances of both versions were evaluated by the receiver operating characteristic curve. RESULTS: Cancer risk scores 1 and 10 in v1.7 increased compared to v1.6 (P < 0.001). In all cases, sensitivity for v1.6 was 56.6%, specificity was 90%, and, for v1.7, sensitivity was 65.9% and specificity was 90%, respectively. In all cases, area under the curve values were 0.812 for v1.6 and 0.856 for v1.7, which was higher in v1.7 (P < 0.001). Diagnostic performance of v1.7 was higher than v1.6 at the 7-12-month period (P < 0.001). CONCLUSION: The present study showed that Tranpara v1.7 has a higher specificity, sensitivity and diagnostic performance in IBC determination than v1.6. AI systems can be used in breast screening as a secondary or third reader in screening programs.

Outcomes of high-risk breast lesions diagnosed using image-guided core needle biopsy: results from a multicenter retrospective study.

PURPOSE: The clinical management of high-risk lesions using image-guided biopsy is challenging. This study aimed to evaluate the rates at which such lesions were upgraded to malignancy and identify possible predictive factors for upgrading high-risk lesions. METHODS: This retrospective multicenter analysis included 1.343 patients diagnosed with high-risk lesions using an image-guided core needle or vacuum-assisted biopsy (VAB). Only patients managed using an excisional biopsy or with at least one year of documented radiological follow-up were included. For each, the Breast Imaging Reporting and Data System (BI-RADS) category, number of samples, needle thickness, and lesion size were correlated with malignancy upgrade rates in different histologic subtypes. Pearson's chi-squared test, the Fisher-Freeman-Halton test, and Fisher's exact test were used for the statistical analyses. RESULTS: The overall upgrade rate was 20.6%, with the highest rates in the subtypes of intraductal papilloma (IP) with atypia (44.7%; 55/123), followed by atypical ductal hyperplasia (ADH) (38.4%; 144/375), lobular neoplasia (LN) (12.7%; 7/55), papilloma without atypia (9.4%; 58/611), flat epithelial atypia (FEA) (8.7%; 10/114), and radial scars (RSs) (4.6%; 3/65). There was a significant relationship between the upgrade rate and BI-RADS category, number of samples, and lesion size Lesion size was the most predictive factor for an upgrade in all subtypes. CONCLUSION: ADH and atypical IP showed considerable upgrade rates to malignancy, requiring surgical excision. The LN, IP without atypia, pure FEA, and RS subtypes showed lower malignancy rates when the BI-RADS category was lower and in smaller lesions that had been adequately sampled using VAB. After being discussed in a multidisciplinary meeting, these cases could be managed with follow-up instead of excision.

Microwave Breast Lesion Classification - Results from Clinical Investigation of the SAFE Microwave Breast Cancer System.

RATIONALE AND OBJECTIVES: Microwave breast cancer imaging (MWI) is an emerging non-invasive technology used to clinically assess the internal breast tissue inhomogeneity. MWI utilizes the variance in dielectric properties of healthy and cancerous tissue to identify anomalies inside the breast and make further clinical predictions. In this study, we evaluate our SAFE MWI system in a clinical setting. Capability of SAFE to provide breast pathology is assessed. MATERIALS AND METHODS: Patients with BI-RADS category 4 or 5 who were scheduled for biopsy were included in the study. Machine learning approach, more specifically the Adaptive Boosting (AdaBoost) model, was implemented to determine if the level of difference between backscattered signals of breasts with the benign and malignant pathological outcome is significant enough for quantitative breast health classification via SAFE. RESULTS: A dataset of 113 (70 benign and 43 malignant) breast samples was used in the study. The proposed classification model achieved the sensitivity, specificity, and accuracy of 79%, 77%, and 78%, respectively. CONCLUSION: The non-ionizing and non-invasive nature gives SAFE an opportunity to impact breast cancer screening and early detection positively. Device classified both benign and malignant lesions at a similar rate. Further clinical studies are planned to validate the findings of this study.

Validation of bioelectrical impedance analysis in the evaluation of body composition in patients with breast cancer.

BACKGROUND: The evaluation of body composition is an essential parameter for preventing obesity and sarcopenic obesity, which are prognostic factors in breast cancer. This study aims to validate the bioelectrical impedance analysis (BIA) of women who are breast cancer survivors by using the dual-energy x-ray absorptiometry (DXA) measurement method. METHODS: This validation study included 104 women without metastasis between 32 and 72 years old (mean 47.03 ± 8.59) whose treatment was completed 6 months prior. Body composition analysis was performed sequentially using both measurements and when participants were hungry. RESULTS: Meaningful differences were found in fat-free mass (FFM) (BIA: 46.57 ± 5.54 kg; DXA: 41.06 ± 5.11 kg), body fat percentage (%BF) (BIA: 34.28% ± 6.24%; DXA: 43.91% ± 5.58%), body fat mass (FM) (BIA: 25.37 ± 8.84 kg; DXA: 31.24 ± 9.09 kg), and lean soft tissue mass (LSTM) (BIA: 4.42 ± 5.66 kg; DXA: 38.75 ± 4.98 kg) (P < 0.001). Powerful associations for body FM and strong associations for other parameters were seen. A constant and/or proportional error was found between the two devices within the direction of strong and solid components. Compared with DXA, the BIA measurement gives a lower estimate of %BF and FM and a higher estimate of LSTM and FFM. CONCLUSIONS: By the mathematical relationship between the two measurement methods, it seems possible to adapt the body composition parameters obtained from BIA of patients with breast cancer to DXA results. In the future, there will be a need to evaluate these two devices with more extensive studies.

Gradient-Boosting Algorithm for Microwave Breast Lesion Classification-SAFE Clinical Investigation.

(1) Background: Microwave breast imaging (MBI) is a promising breast-imaging technology that uses harmless electromagnetic waves to radiate the breast and assess its internal structure. It utilizes the difference in dielectric properties of healthy and cancerous tissue, as well as the dielectric difference between different cancerous tissue types to identify anomalies inside the breast and make further clinical predictions. In this study, we evaluate the capability of our upgraded MBI device to provide breast tissue pathology. (2) Methods: Only patients who were due to undergo biopsy were included in the study. A machine learning (ML) approach, namely Gradient Boosting, was used to understand information from the frequency spectrum, collected via SAFE, and provide breast tissue pathology. (3) Results: A total of 54 patients were involved in the study: 29 of them had benign and 25 had malignant findings. SAFE acquired 20 true-positive, 24 true-negative, 4 false-positive and 4 false-negative findings, achieving the sensitivity, specificity and accuracy of 80%, 83% and 81%, respectively. (4) Conclusions: The use of harmless tissue radiation indicates that SAFE can be used to provide the breast pathology of women of any age without safety restrictions. Results indicate that SAFE is capable of providing breast pathology at a high rate, encouraging further clinical investigations.

The association of age at menarche and adult height with mammographic density in the International Consortium of Mammographic Density.

BACKGROUND: Early age at menarche and tall stature are associated with increased breast cancer risk. We examined whether these associations were also positively associated with mammographic density, a strong marker of breast cancer risk. METHODS: Participants were 10,681 breast-cancer-free women from 22 countries in the International Consortium of Mammographic Density, each with centrally assessed mammographic density and a common set of epidemiologic data. Study periods for the 27 studies ranged from 1987 to 2014. Multi-level linear regression models estimated changes in square-root per cent density (√PD) and dense area (√DA) associated with age at menarche and adult height in pooled analyses and population-specific meta-analyses. Models were adjusted for age at mammogram, body mass index, menopausal status, hormone therapy use, mammography view and type, mammographic density assessor, parity and height/age at menarche. RESULTS: In pooled analyses, later age at menarche was associated with higher per cent density (ß√PD = 0.023 SE = 0.008, P = 0.003) and larger dense area (ß√DA = 0.032 SE = 0.010, P = 0.002). Taller women had larger dense area (ß√DA = 0.069 SE = 0.028, P = 0.012) and higher per cent density (ß√PD = 0.044, SE = 0.023, P = 0.054), although the observed effect on per cent density depended upon the adjustment used for body size. Similar overall effect estimates were observed in meta-analyses across population groups. CONCLUSIONS: In one of the largest international studies to date, later age at menarche was positively associated with mammographic density. This is in contrast to its association with breast cancer risk, providing little evidence of mediation. Increased height was also positively associated with mammographic density, particularly dense area. These results suggest a complex relationship between growth and development, mammographic density and breast cancer risk. Future studies should evaluate the potential mediation of the breast cancer effects of taller stature through absolute breast density.

SAFE: A Novel Microwave Imaging System Design for Breast Cancer Screening and Early Detection-Clinical Evaluation.

SAFE (Scan and Find Early) is a novel microwave imaging device intended for breast cancer screening and early detection. SAFE is based on the use of harmless electromagnetic waves and can provide relevant initial diagnostic information without resorting to X-rays. Because of SAFE's harmless effect on organic tissue, imaging can be performed repeatedly. In addition, the scanning process itself is not painful since breast compression is not required. Because of the absence of physical compression, SAFE can also detect tumors that are close to the thoracic wall. A total number of 115 patients underwent the SAFE scanning procedure, and the resultant images were compared with available magnetic resonance (MR), ultrasound, and mammography images in order to determine the correct detection rate. A sensitivity of 63% was achieved. Breast size influenced overall sensitivity, as sensitivity was lower in smaller breasts (51%) compared to larger ones (74%). Even though this is only a preliminary study, the results show promising concordance with clinical reports, thus encouraging further SAFE clinical studies.

Modified Glasgow Prognostic Score, Prognostic Nutritional Index and ECOG Performance Score Predicts Survival Better than Sarcopenia, Cachexia and Some Inflammatory Indices in Metastatic Gastric Cancer.

Background: Gastric carcinoma (GC) patients usually present with locally advanced or metastatic disease; therefore treatment aim is mainly palliation. In this study our purpose is to analyze the prognostic values of the sarcopenia index (SI), cachexia index (CIn) and other inflammatory indexes (advanced lung cancer inflammation index [ALI], modified Glasgow Prognostic Score [mGPS], prognostic index [PI], prognostic nutritional index [PNI] and neutrophil-to-lymphocyte ratio [NLR]) in metastatic GC patients.Methods: Data from the files of metastatic GC patients, who applied to Medical Oncology outpatient clinic in Marmara University Pendik Education and Research Hospital between January 2011 and June 2016, were retrospectively reviewed. Five hundred seventy patients with gastric cancer were detected. Exclusion criteria were the inability to reach the patient surveys for prognostic index calculations, the presence of additional comorbidities to affect the laboratory parameters, and the absence of metastatic disease. Finally, 87 of these patients were included in this study. For SI calculation L3 level muscle area was measured from patients' computed tomography (CT) by a radiologist. SI reference value was obtained from western-EGWSOP (The European Working Group on Sarcopenia in Older People) and eastern (Harada Y, et al.) sources separately, as Turkey doesn't have a reference value for SI. NLR cutoff value was accepted as the median value of patients' NLR measurements. Statistical analysis was conducted using SPSS. Kaplan-Meier and Cox regression models were used to assess independent prognostic factors. The area under the curve was used to compare the prognostic value of indexes.Results: The median length of follow-up of 87 patients was nine months (1-64 mo,/s), and 78 patients died during follow-up. Fifty-nine patients were male (63%), and the median age was 62 (range, 23-88). According to univariate analysis high mGPS and PI score, PNI level <45, NLR level ≥ 3.41, ALI level <18, CI level under 35, SI (Harada Y, et al) ≤44.5 for males and ≤36.5 for females, ECOG score ≥ 2, weight loss more than 10% during last 6 mo, BMI under 24 were poor prognostic factors. Age, gender, having multiple organ metastasis, history of gastric surgery, positivity C-erb-B2, SI (EGWSOP) ≤52.4 for males, and ≤38.4 for females did not have any impact on survival. According to multivariate analysis, high mGPS (score 2) (HR 2,494, 95% CI 1.25-4 .94, p = 0.02), PNI (score 1) (HR 4.2, 95% CI 1.73-10.1, p < 0.001) and ECOG score (≥2) (HR 1.541, 95% CI 1,089-4,214, p = 0.004) have been found to be independent prognostic factors which are determining the survival. mGPS was found to be more valuable than other indexes for predicting mortality by measuring the AUC with ROC analysis.Conclusions: In our study, mGPS, PNI and ECOG score were independent indicators for shorter survival in metastatic gastric cancer patients. mGPS and PNI, which can be done by using only serum CRP, albumin level and complete blood count, might be inexpensive, practical and beneficial to use in routine clinical practice to determine survival.

Silicone-based composite materials simulate breast tissue to be used as ultrasonography training phantoms.

A silicone-based composite breast phantom is fabricated to be used as an education model in ultrasonography training. A matrix of silicone formulations is tracked to mimic the ultrasonography and tactile response of human breast tissue. The performance of two different additives: (i) silicone oil and (ii) vinyl-terminated poly (dimethylsiloxane) (PDMS) are monitored by a home-made acoustic setup. Through the use of 75 wt% vinyl-terminated PDMS in two-component silicone elastomer mixture, a sound velocity of 1.29 ±â€¯0.09 × 103 m/s and an attenuation coefficient of 12.99 ±â€¯0.08 dB/cm-values those match closely to the human breast tissue-are measured with 5 MHz probe. This model can also be used for needle biopsy as well as for self-exam trainings. Herein, we highlight the fabrication of a realistic, durable, accessible, and cost-effective training platform that contains skin layer, inner breast tissue, and tumor masses.

Mammographic density and ageing: A collaborative pooled analysis of cross-sectional data from 22 countries worldwide.

BACKGROUND: Mammographic density (MD) is one of the strongest breast cancer risk factors. Its age-related characteristics have been studied in women in western countries, but whether these associations apply to women worldwide is not known. METHODS AND FINDINGS: We examined cross-sectional differences in MD by age and menopausal status in over 11,000 breast-cancer-free women aged 35-85 years, from 40 ethnicity- and location-specific population groups across 22 countries in the International Consortium on Mammographic Density (ICMD). MD was read centrally using a quantitative method (Cumulus) and its square-root metrics were analysed using meta-analysis of group-level estimates and linear regression models of pooled data, adjusted for body mass index, reproductive factors, mammogram view, image type, and reader. In all, 4,534 women were premenopausal, and 6,481 postmenopausal, at the time of mammography. A large age-adjusted difference in percent MD (PD) between post- and premenopausal women was apparent (-0.46 cm [95% CI: -0.53, -0.39]) and appeared greater in women with lower breast cancer risk profiles; variation across population groups due to heterogeneity (I2) was 16.5%. Among premenopausal women, the √PD difference per 10-year increase in age was -0.24 cm (95% CI: -0.34, -0.14; I2 = 30%), reflecting a compositional change (lower dense area and higher non-dense area, with no difference in breast area). In postmenopausal women, the corresponding difference in √PD (-0.38 cm [95% CI: -0.44, -0.33]; I2 = 30%) was additionally driven by increasing breast area. The study is limited by different mammography systems and its cross-sectional rather than longitudinal nature. CONCLUSIONS: Declines in MD with increasing age are present premenopausally, continue postmenopausally, and are most pronounced over the menopausal transition. These effects were highly consistent across diverse groups of women worldwide, suggesting that they result from an intrinsic biological, likely hormonal, mechanism common to women. If cumulative breast density is a key determinant of breast cancer risk, younger ages may be the more critical periods for lifestyle modifications aimed at breast density and breast cancer risk reduction.

Evaluation of sacroiliac joint MRI for pelvic venous congestion signs in women clinically suspected of sacroiliitis.

Background Pelvic congestion syndrome (PCS) is a commonly overlooked condition which is a potential cause of chronic pelvic pain. Magnetic resonance imaging (MRI) of the sacroiliac joint (SIJ) may demonstrate unexpected conditions that can mimic sacroiliitis (SI). Awareness of MRI-defined pelvic venous congestion (PVC) may help in identifying PCS, where vascular abnormality may be the sole manifestation of SIJ pain. Purpose To detect incidental MRI-defined PVC in patients who underwent SIJ-MRI for presumed SI and define the variance of its incidence. Material and Methods A total of 870 women who underwent SIJ-MRI were retrospectively evaluated. Incidental findings of PVC and other genitourinary and musculoskeletal system disorders were documented. Results Of the 774 included patients, 37% demonstrated incidentally detected imaging findings related to the genitourinary system, musculoskeletal system, and PVC. The prevalence of MRI-defined PVC signs was higher in patients without SI than with SI. The prevalence of musculoskeletal disorders was higher in patients with SI whereas prevalence for genitourinary disorders was similar. Binary logistic regression analysis revealed a statistically significant correlation between SI-PVC and SI-genitourinary disorders but not between SI-musculoskeletal disorders pairs ( P = 0.001, 0.001, and 0.057 > 0.05). The probability of observing SI in SIJ-MRI is positively correlated with the absence of PVC or genitourinary disorders. Conclusion Patients who underwent MRI for presumed SI demonstrated incidental PVC as well as other genitourinary and musculoskeletal findings. An awareness of these imaging findings can help identify PVC and may draw clinicians' attention to the possibility of PCS.

Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems.

BACKGROUND: Inter-women and intra-women comparisons of mammographic density (MD) are needed in research, clinical and screening applications; however, MD measurements are influenced by mammography modality (screen film/digital) and digital image format (raw/processed). We aimed to examine differences in MD assessed on these image types. METHODS: We obtained 1294 pairs of images saved in both raw and processed formats from Hologic and General Electric (GE) direct digital systems and a Fuji computed radiography (CR) system, and 128 screen-film and processed CR-digital pairs from consecutive screening rounds. Four readers performed Cumulus-based MD measurements (n = 3441), with each image pair read by the same reader. Multi-level models of square-root percent MD were fitted, with a random intercept for woman, to estimate processed-raw MD differences. RESULTS: Breast area did not differ in processed images compared with that in raw images, but the percent MD was higher, due to a larger dense area (median 28.5 and 25.4 cm2 respectively, mean √dense area difference 0.44 cm (95% CI: 0.36, 0.52)). This difference in √dense area was significant for direct digital systems (Hologic 0.50 cm (95% CI: 0.39, 0.61), GE 0.56 cm (95% CI: 0.42, 0.69)) but not for Fuji CR (0.06 cm (95% CI: -0.10, 0.23)). Additionally, within each system, reader-specific differences varied in magnitude and direction (p < 0.001). Conversion equations revealed differences converged to zero with increasing dense area. MD differences between screen-film and processed digital on the subsequent screening round were consistent with expected time-related MD declines. CONCLUSIONS: MD was slightly higher when measured on processed than on raw direct digital mammograms. Comparisons of MD on these image formats should ideally control for this non-constant and reader-specific difference.

International Consortium on Mammographic Density: Methodology and population diversity captured across 22 countries.

Mammographic density (MD) is a quantitative trait, measurable in all women, and is among the strongest markers of breast cancer risk. The population-based epidemiology of MD has revealed genetic, lifestyle and societal/environmental determinants, but studies have largely been conducted in women with similar westernized lifestyles living in countries with high breast cancer incidence rates. To benefit from the heterogeneity in risk factors and their combinations worldwide, we created an International Consortium on Mammographic Density (ICMD) to pool individual-level epidemiological and MD data from general population studies worldwide. ICMD aims to characterize determinants of MD more precisely, and to evaluate whether they are consistent across populations worldwide. We included 11755 women, from 27 studies in 22 countries, on whom individual-level risk factor data were pooled and original mammographic images were re-read for ICMD to obtain standardized comparable MD data. In the present article, we present (i) the rationale for this consortium; (ii) characteristics of the studies and women included; and (iii) study methodology to obtain comparable MD data from original re-read films. We also highlight the risk factor heterogeneity captured by such an effort and, thus, the unique insight the pooled study promises to offer through wider exposure ranges, different confounding structures and enhanced power for sub-group analyses.