Природный и антропогенный факторы формирования и развития культурного ландшафта Форосского парка

Цель данной статьи: на примере небольшой территории Южного берега Крыма – парка в пгт. Форос и прилегающей к нему местности – показать роль и место культурного ландшафта в формировании человеком исторического геокультурного пространства

Optimization of Wire-guided Technique With Bracketing Reduces Resection Volumes in Breast-conserving Surgery for Early Breast Cancer

Background: Wire-guided localization (WGL) of early breast cancer can be facilitated using multiple wires, which is called bracketing wire-guided localization (BWL). The primary aim of this study is to compare BWL and conventional WGL regarding minimization of resection volumes without compromising margin status. Secondly, BWL is evaluated as an alternative method for intraoperative ultrasound (US) guidance in poorly definable breast tumors on US. Patients and Methods: In this retrospective cohort study, patients with preoperatively diagnosed breast cancer undergoing wide local excision between January 2016 and December 2018 were analyzed. Patients with multifocal disease or neoadjuvant treatment were excluded from this study. Optimal resection with minimal healthy breast tissue removal was assessed using the calculated resection ratio (CRR). Results: BWL was performed in 17 (9%) patients, WGL in 44 (22%), and US in 139 (70%). The rate of negative margins was comparable in all 3 groups. The CRR was significantly smaller for BWL (0.6) than WGL (1.3) in tumors larger than 1.5 cm. Additionally, BWL (0.8) led to smaller CRRs than US (1.7). This could be explained by the high number of small tumors (≤ 1.5 cm) in the US group for which greater CRRs are obtained than for large tumors (> 1.5 cm) (1.9 vs. 1.4; P = .005). Conclusion: For breast tumors larger than 1.5 cm, BWL achieves more optimal resection volumes without compromising margin status compared with WGL. Moreover, BWL seems a suitable alternative to US in patients with poorly ultrasound-visible breast tumors and patients with a small tumor in a (large) breast. Bracketing wire-guided localization (BWL) to demarcate tumor borders can be used to minimize resection volumes in patients with breast cancer. The sample consisted of 17 patients treated with BWL and 44 patients treated with single wire-guided localization. BWL achieved smaller resection volumes than wire-guided localization without compromising margin status for breast tumors larger than 1.5 cm, which could potentially improve cosmetic outcomes

Reducing False-Positive Screening MRI Rate in Women with Extremely Dense Breasts Using Prediction Models Based on Data from the DENSE Trial

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Reducing False-Positive Screening MRI Rate in Women with Extremely Dense Breasts Using Prediction Models Based on Data from the DENSE Trial

Background: High breast density increases breast cancer risk and lowers mammographic sensitivity. Supplemental MRI screening improves cancer detection but increases the number of false-positive screenings. Thus, methods to distinguish true-positive MRI screening results from false-positive ones are needed. Purpose: To build prediction models based on clinical characteristics and MRI findings to reduce the rate of false-positive screening MRI findings in women with extremely dense breasts. Materials and Methods: Clinical characteristics and MRI findings in Dutch breast cancer screening participants (age range, 50–75 years) with positive first-round MRI screening results (Breast Imaging Reporting and Data System 3, 4, or 5) after a normal screening mammography with extremely dense breasts (Volpara density category 4) were prospectively collected within the randomized controlled Dense Tissue and Early Breast Neoplasm Screening (DENSE) trial from December 2011 through November 2015. In this secondary analysis, prediction models were built using multivariable logistic regression analysis to distinguish true-positive MRI screening findings from false-positive ones. Results: Among 454 women (median age, 52 years; interquartile range, 50–57 years) with a positive MRI result in a first supplemental MRI screening round, 79 were diagnosed with breast cancer (true-positive findings), and 375 had false-positive MRI results. The full prediction model (area under the receiver operating characteristics curve [AUC], 0.88; 95% CI: 0.84, 0.92), based on all collected clinical characteristics and MRI findings, could have prevented 45.5% (95% CI: 39.6, 51.5) of false-positive recalls and 21.3% (95% CI: 15.7, 28.3) of benign biopsies without missing any cancers. The model solely based on readily available MRI findings and age had a comparable performance (AUC, 0.84; 95% CI: 0.79, 0.88; P = .15) and could have prevented 35.5% (95% CI: 30.4, 41.1) of false-positive MRI screening results and 13.0% (95% CI: 8.8, 18.6) of benign biopsies. Conclusion: Prediction models based on clinical characteristics and MRI findings may be useful to reduce the false-positive first-round screening MRI rate and benign biopsy rate in women with extremely dense breasts

Reducing False-Positive Screening MRI Rate in Women with Extremely Dense Breasts Using Prediction Models Based on Data from the DENSE Trial

Background: High breast density increases breast cancer risk and lowers mammographic sensitivity. Supplemental MRI screening improves cancer detection but increases the number of false-positive screenings. Thus, methods to distinguish true-positive MRI screening results from false-positive ones are needed.Purpose: To build prediction models based on clinical characteristics and MRI findings to reduce the rate of false-positive screening MRI findings in women with extremely dense breasts.Materials and Methods: Clinical characteristics and MRI findings in Dutch breast cancer screening participants (age range, 50-75 years) with positive first-round MRI screening results (Breast Imaging Reporting and Data System 3, 4, or 5) after a normal screening mammography with extremely dense breasts (Volpara density category 4) were prospectively collected within the randomized controlled Dense Tissue and Early Breast Neoplasm Screening (DENSE) trial from December 2011 through November 2015. In this secondary analysis, prediction models were built using multivariable logistic regression analysis to distinguish true-positive MRI screening findings from false-positive ones.Results: Among 454 women (median age, 52 years; interquartile range, 50-57 years) with a positive MRI result in a first supplemental MRI screening round, 79 were diagnosed with breast cancer (true-positive findings), and 375 had false-positive MRI results. The full prediction model (area under the receiver operating characteristics curve [AUC], 0.88; 95% CI: 0.84, 0.92), based on all collected clinical characteristics and MRI findings, could have prevented 45.5% (95% CI: 39.6, 51.5) of false-positive recalls and 21.3% (95% CI: 15.7, 28.3) of benign biopsies without missing any cancers. The model solely based on readily available MRI findings and age had a comparable performance (AUC, 0.84; 95% CI: 0.79, 0.88; P =.15) and could have prevented 35.5% (95% CI: 30.4, 41.1) of false-positive MRI screening results and 13.0% (95% CI: 8.8, 18.6) of benign biopsies.Conclusion: Prediction models based on clinical characteristics and MRI findings may be useful to reduce the false-positive first-round screening MRI rate and benign biopsy rate in women with extremely dense breasts. (C) RSNA, 202

Predicting breast cancer types on and beyond molecular level in a multi-modal fashion

Accurately determining the molecular subtypes of breast cancer is important for the prognosis of breast cancer patients and can guide treatment selection. In this study, we develop a deep learning-based model for predicting the molecular subtypes of breast cancer directly from the diagnostic mammography and ultrasound images. Multi-modal deep learning with intra- and inter-modality attention modules (MDL-IIA) is proposed to extract important relations between mammography and ultrasound for this task. MDL-IIA leads to the best diagnostic performance compared to other cohort models in predicting 4-category molecular subtypes with Matthews correlation coefficient (MCC) of 0.837 (95% confidence interval [CI]: 0.803, 0.870). The MDL-IIA model can also discriminate between Luminal and Non-Luminal disease with an area under the receiver operating characteristic curve of 0.929 (95% CI: 0.903, 0.951). These results significantly outperform clinicians’ predictions based on radiographic imaging. Beyond molecular-level test, based on gene-level ground truth, our method can bypass the inherent uncertainty from immunohistochemistry test. This work thus provides a noninvasive method to predict the molecular subtypes of breast cancer, potentially guiding treatment selection for breast cancer patients and providing decision support for clinicians

Radiofrequency-assisted intact specimen biopsy of breast tumors: Critical evaluation according to the IDEAL recommendations

Radiofrequency-assisted intact specimen biopsy (RFIB) has been introduced for percutaneous biopsy or removal of breast tumors. Using radiofrequency cutting, the system enables the radiologist to obtain an intact sample of the target lesion. According to the IDEAL recommendations, we performed a critical evaluation of our initial experience with RFIB. Between June and November 2010, radiography-guided RFIB was performed in 19 female patients. All patients presented with suspicious microcalcifications (BI-RADS III-V) on mammography. Biopsy specimen integrity, thermal damage and histologic diagnosis were assessed by an expert breast pathologist. Data on technical success, diagnostic and therapeutic accuracy and periprocedural complications were collected and analyzed. The median age of the patients was 59 years. Median lesion diameter on mammography was 8mm (range 2-76 mm). The procedure was successful in 16/19 (84%) patients and unsuccessful in 3/19 (16%) patients (2 non-representative samples, 1 sample with extensive thermal damage). Histologic analysis of the RFIB specimen revealed 12/19 (63%) benign lesions and 7/19 (37%) malignancies (4 ductal carcinoma in situ (DCIS) lesions and 3 invasive ductal carcinomas). In 1 patient, a DCIS lesion was completely removed with RFIB. Overall, 3 periprocedural complications occurred (1 wound leakage, 1 arterial hemorrhage and 1 infection requiring oral antibiotics). Tissue sampling of suspicious breast lesions can be performed successfully with RFIB. In 1 patient DCIS was radically excised with RFIB, which illustrates its potential as a minimally invasive therapeutic procedure for removal of small breast tumors. This is an interesting focus for further research when larger probe sizes become available

Preoperative Partial Breast Irradiation in Patients with Low-Risk Breast Cancer: A Systematic Review of Literature

Background: Preoperative instead of standard postoperative partial breast irradiation (PBI) after breast-conserving surgery (BCS) has the advantage of reducing the irradiated breast volume, toxicity, and number of radiotherapy sessions and can allow tumor downstaging. In this review, we assessed tumor response and clinical outcomes after preoperative PBI. Patients and Methods: We conducted a systematic review of studies on preoperative PBI in patients with low-risk breast cancer using the databases Ovid Medline, Embase.com, Web of Science (Core Collection), and Scopus (PROSPERO registration CRD42022301435). References of eligible manuscripts were checked for other relevant manuscripts. The primary outcome measure was pathologic complete response (pCR). Results: A total of eight prospective and one retrospective cohort study were identified (n = 359). In up to 42% of the patients, pCR was obtained and this increased after a longer interval between radiotherapy and BCS (0.5–8 months). After a maximum median follow-up of 5.0 years, three studies on external beam radiotherapy reported low local recurrence rates (0–3%) and overall survival of 97–100%. Acute toxicity consisted mainly of grade 1 skin toxicity (0–34%) and seroma (0–31%). Late toxicity was predominantly fibrosis grade 1 (46–100%) and grade 2 (10–11%). Cosmetic outcome was good to excellent in 78–100% of the patients. Conclusions: Preoperative PBI showed a higher pCR rate after a longer interval between radiotherapy and BCS. Mild late toxicity and good oncological and cosmetic outcomes were reported. In the ongoing ABLATIVE-2 trial, BCS is performed at a longer interval of 12 months after preoperative PBI aiming to achieve a higher pCR rate

Preoperative Partial Breast Irradiation in Patients with Low-Risk Breast Cancer: A Systematic Review of Literature

Background: Preoperative instead of standard postoperative partial breast irradiation (PBI) after breast-conserving surgery (BCS) has the advantage of reducing the irradiated breast volume, toxicity, and number of radiotherapy sessions and can allow tumor downstaging. In this review, we assessed tumor response and clinical outcomes after preoperative PBI. Patients and Methods: We conducted a systematic review of studies on preoperative PBI in patients with low-risk breast cancer using the databases Ovid Medline, Embase.com, Web of Science (Core Collection), and Scopus (PROSPERO registration CRD42022301435). References of eligible manuscripts were checked for other relevant manuscripts. The primary outcome measure was pathologic complete response (pCR). Results: A total of eight prospective and one retrospective cohort study were identified (n = 359). In up to 42% of the patients, pCR was obtained and this increased after a longer interval between radiotherapy and BCS (0.5–8 months). After a maximum median follow-up of 5.0 years, three studies on external beam radiotherapy reported low local recurrence rates (0–3%) and overall survival of 97–100%. Acute toxicity consisted mainly of grade 1 skin toxicity (0–34%) and seroma (0–31%). Late toxicity was predominantly fibrosis grade 1 (46–100%) and grade 2 (10–11%). Cosmetic outcome was good to excellent in 78–100% of the patients. Conclusions: Preoperative PBI showed a higher pCR rate after a longer interval between radiotherapy and BCS. Mild late toxicity and good oncological and cosmetic outcomes were reported. In the ongoing ABLATIVE-2 trial, BCS is performed at a longer interval of 12 months after preoperative PBI aiming to achieve a higher pCR rate

The added diagnostic value of dynamic contrast-enhanced MRI at 3.0 T in nonpalpable breast lesions.

To investigate the added diagnostic value of 3.0 Tesla breast MRI over conventional breast imaging in the diagnosis of in situ and invasive breast cancer and to explore the role of routine versus expert reading.We evaluated MRI scans of patients with nonpalpable BI-RADS 3-5 lesions who underwent dynamic contrast-enhanced 3.0 Tesla breast MRI. Initially, MRI scans were read by radiologists in a routine clinical setting. All histologically confirmed index lesions were re-evaluated by two dedicated breast radiologists. Sensitivity and specificity for the three MRI readings were determined, and the diagnostic value of breast MRI in addition to conventional imaging was assessed. Interobserver reliability between the three readings was evaluated.MRI examinations of 207 patients were analyzed. Seventy-eight of 207 (37.7%) patients had a malignant lesion, of which 33 (42.3%) patients had pure DCIS and 45 (57.7%) invasive breast cancer. Sensitivity of breast MRI was 66.7% during routine, and 89.3% and 94.7% during expert reading. Specificity was 77.5% in the routine setting, and 61.0% and 33.3% during expert reading. In the routine setting, MRI provided additional diagnostic information over clinical information and conventional imaging, as the Area Under the ROC Curve increased from 0.76 to 0.81. Expert MRI reading was associated with a stronger improvement of the AUC to 0.87. Interobserver reliability between the three MRI readings was fair and moderate.3.0 T breast MRI of nonpalpable breast lesions is of added diagnostic value for the diagnosis of in situ and invasive breast cancer