Health-related quality of life and fear of progression in individuals with Li-Fraumeni syndrome.

Li-Fraumeni syndrome (LFS) is a rare autosomal dominant cancer predisposition syndrome associated with a highly elevated lifetime cancer risk. This and the recommended intense surveillance program represent a large psychological burden on families. In order to develop targeted psychosocial interventions, we conducted a needs assessment. Adults (≥18 years) with LFS were included via regular hospital visits and online support groups and newsletters. Individuals filled out a questionnaire addressing among others: fear of progression (FoP-questionnaire, short-form), health-related quality of life (HRQoL, Short-Form Health Survey-12), distress (National Comprehensive Cancer Network distress thermometer), perceived cancer risk, and aspects of surveillance adherence. Collecting data over a 14-month period (March 2020 - June 2021), 70 adults were recruited (female = 58, 82.9%; mean age = 41.53 years). With mean mental component scores (MCS) of 42.28 (SD = 10.79), and physical component scores (PCS) of 48.83 (SD = 10.46), HRQoL was low in 34.8% (physical) and 59.4% (mental) of individuals when applying a mean cut-off of 45.4 (PCS) and 47.5 (MCS) to indicate poor HRQoL. High levels of FoP and distress were present in 68.6% and 69.1% of the participants, respectively. Performing a multiple linear regression on MCS and PCS, no sociodemographic variable was shown to be significant. FoP (ß = -0.33, p < 0.05) and distress (ß = -0.34, p < 0.05) were significantly associated with MCS. Individuals in our sample were burdened more than expected, with the majority reporting low levels of (mental) HRQoL, high distress, and FoP. Psychosocial support is necessary to help individuals with LFS (survivors as well as "previvors") increase their HRQoL, as it is crucial to survival.

Can multi-modal radiomics using pretreatment ultrasound and tomosynthesis predict response to neoadjuvant systemic treatment in breast cancer?

OBJECTIVES: Response assessment to neoadjuvant systemic treatment (NAST) to guide individualized treatment in breast cancer is a clinical research priority. We aimed to develop an intelligent algorithm using multi-modal pretreatment ultrasound and tomosynthesis radiomics features in addition to clinical variables to predict pathologic complete response (pCR) prior to the initiation of therapy. METHODS: We used retrospective data on patients who underwent ultrasound and tomosynthesis before starting NAST. We developed a support vector machine algorithm using pretreatment ultrasound and tomosynthesis radiomics features in addition to patient and tumor variables to predict pCR status (ypT0 and ypN0). Findings were compared to the histopathologic evaluation of the surgical specimen. The main outcome measures were area under the curve (AUC) and false-negative rate (FNR). RESULTS: We included 720 patients, 504 in the development set and 216 in the validation set. Median age was 51.6 years and 33.6% (242 of 720) achieved pCR. The addition of radiomics features significantly improved the performance of the algorithm (AUC 0.72 to 0.81; p = 0.007). The FNR of the multi-modal radiomics and clinical algorithm was 6.7% (10 of 150 with missed residual cancer). Surface/volume ratio at tomosynthesis and peritumoral entropy characteristics at ultrasound were the most relevant radiomics. Hormonal receptors and HER-2 status were the most important clinical predictors. CONCLUSION: A multi-modal machine learning algorithm with pretreatment clinical, ultrasound, and tomosynthesis radiomics features may aid in predicting residual cancer after NAST. Pending prospective validation, this may facilitate individually tailored NAST regimens. CLINICAL RELEVANCE STATEMENT: Multi-modal radiomics using pretreatment ultrasound and tomosynthesis showed significant improvement in assessing response to NAST compared to an algorithm using clinical variables only. Further prospective validation of our findings seems warranted to enable individualized predictions of NAST outcomes. KEY POINTS: • We proposed a multi-modal machine learning algorithm with pretreatment clinical, ultrasound, and tomosynthesis radiomics features to predict response to neoadjuvant breast cancer treatment. • Compared with the clinical algorithm, the AUC of this integrative algorithm is significantly higher. • Used prior to the initiative of therapy, our algorithm can identify patients who will experience pathologic complete response following neoadjuvant therapy with a high negative predictive value.

Ultrasound Radiomics Features to Identify Patients With Triple-Negative Breast Cancer: A Retrospective, Single-Center Study.

OBJECTIVES: Patients with triple-negative breast cancer (TNBC) exhibit a fast tumor growth rate and poor survival outcomes. In this study, we aimed to develop and compare intelligent algorithms using ultrasound radiomics features in addition to clinical variables to identify patients with TNBC prior to histopathologic diagnosis. METHODS: We used single-center, retrospective data of patients who underwent ultrasound before histopathologic verification and subsequent neoadjuvant systemic treatment (NAST). We developed a logistic regression with an elastic net penalty algorithm using pretreatment ultrasound radiomics features in addition to patient and tumor variables to identify patients with TNBC. Findings were compared to the histopathologic evaluation of the biopsy specimen. The main outcome measure was the area under the curve (AUC). RESULTS: We included 1161 patients, 813 in the development set and 348 in the validation set. Median age was 50.1 years and 24.4% (283 of 1161) had TNBC. The integrative model using radiomics and clinical information showed significantly better performance in identifying TNBC compared to the radiomics model (AUC: 0.71, 95% confidence interval [CI]: 0.65-0.76 versus 0.64, 95% CI: 0.57-0.71, P = .004). The five most important variables were cN status, shape surface volume ratio (SA:V), gray level co-occurrence matrix (GLCM) correlation, gray level dependence matrix (GLDM) dependence nonuniformity normalized, and age. Patients with TNBC were more often categorized as BI-RADS 4 than BI-RADS 5 compared to non-TNBC patients (P = .002). CONCLUSION: A machine learning algorithm showed promising potential to identify patients with TNBC using ultrasound radiomics features and clinical information prior to histopathologic evaluation.

Medical students' knowledge on cancer predisposition syndromes and attitude toward eHealth.

PURPOSE: Individuals with cancer predisposition syndromes (CPS) inherit elevated cancer risks. Medical supply gaps for people at risk of CPS cause insufficient outreach and miss potential benefits of individualized care strategies. Increased awareness of CPS and progress in the eHealth sector are untapped sources of health care improvement for affected individuals. METHODS AND RESULTS: This study addressed German-speaking medical students with an online questionnaire in respect to their knowledge of CPS, their medical education, and perspectives. The study population (n = 404) reported interest in and knowledge of CPS, supported by a satisfactory and sustainable education for their prospective patient care. The next generation of doctors would implement eHealth to improve medical services. Skepticism about digitization was claimed by students. They were especially concerned about deterioration in the physician-patient relationship, data abuse, dependence on technology, and incorrect diagnoses. CONCLUSION: Due to increasing diagnosing of CPS and deeper knowledge, this topic is essential for the curriculum in medical schools. In particular, care providers need know-how on identifying patients at risk for a CPS, certain diagnostic and therapeutic steps, surveillance and prophylactic strategies to improve patients' outcomes. Education in medical school as well as implemented eHealth seems to have potential to meet this demand in an upcoming era of personalized medicine. What does this study add to the clinical work. Medical teaching on cancer predisposition syndromes should be expanded to improve knowledge and individualized and personalized healthcare.

Intra- and Interobserver Reliability of Shear Wave Elastography in Breast Cancer Diagnosis.

OBJECTIVES: Shear wave elastography (SWE) is increasingly used in breast cancer diagnostics. However, large, prospective, multicenter data evaluating the reliability of SWE is missing. We evaluated the intra- and interobserver reliability of SWE in patients with breast lesions categorized as BIRADS 3 or 4. METHODS: We used data of 1288 women at 12 institutions in 7 countries with breast lesions categorized as BIRADS 3 to 4 who underwent conventional B-mode ultrasound and SWE. 1243 (96.5%) women had three repetitive conventional B-mode ultrasounds as well as SWE measurements performed by a board-certified senior physician. 375 of 1288 (29.1%) women received an additional ultrasound examination with B-mode and SWE by a second physician. Intraclass correlation coefficients (ICC) were calculated to examine intra- and interobserver reliability. RESULTS: ICC for intraobserver reliability showed an excellent correlation with ICC >0.9, while interobserver reliability was moderate with ICC of 0.7. There were no clinically significant differences in intraobserver reliability when SWE was performed in lesions categorized as BI-RADS 3 or 4 as well as in histopathologically benign or malignant lesions. CONCLUSION: Reliability of additional SWE was evaluated on a study cohort consisting of 1288 breast lesions categorized as BI-RADS 3 and 4. SWE shows an excellent intraobserver reliability and a moderate interobserver reliability in the evaluation of solid breast masses.

Liver stiffness in pregnant women with intrahepatic cholestasis of pregnancy: A case control study.

BACKGROUND: Intrahepatic cholestasis of pregnancy (ICP) is a rare but severe complication for both the mother and the unborn child. The diagnosis is primarily based on elevated serum levels of bile acids. In a large ICP cohort, we here study in detail liver stiffness (LS) using transient elastography (TE), now widely used to non-invasively screen for liver cirrhosis within minutes. AIM: To specifically explore LS in a large cohort of women with ICP compared to a control group with uncomplicated pregnancy. METHODS: LS and hepatic steatosis marker controlled attenuation parameter (CAP) were measured in 100 pregnant women with ICP using TE (Fibroscan, Echosens, Paris, France) between 2010 and 2020. In 17 cases, LS could be measured postpartum. 450 women before and 38 women after delivery with uncomplicated pregnancy served as control group. Routine laboratory, levels of bile acids and apoptosis marker caspase-cleaved cytokeratin 18 fragment (M30) were also measured. RESULTS: Women with ICP had significantly elevated transaminases but normal gamma-glutamyl transferase (GGT). Mean LS was significantly increased at 7.3 ± 3.0 kPa compared to the control group at 6.2 ± 2.3 kPa (P < 0.0001). Postpartum LS decreased significantly in both groups but was still higher in ICP (5.8 ± 1.7 kPa vs 4.2 ± 0.9 kPa, P < 0.0001), respectively. In ICP, LS was highly significantly correlated with levels of bile acids and M30 but not transaminases. No correlation was seen with GGT that even increased significantly after delivery in the ICP group. Bile acids were mostly correlated with the liver apoptosis marker M30, LS and levels of alanine aminotransferase, aspartate aminotransferase, and bilirubin. In multivariate analysis, LS remained the sole parameter that was independently associated with elevated bile acids. CONCLUSION: In conclusion, LS is significantly elevated in ICP which is most likely due to toxic bile acid accumulation and hepatocyte apoptosis. In association with conventional laboratory markers, LS provides additional non-invasive information to rapidly identify women at risk for ICP.

Conventional specimen radiography in breast-conserving therapy: a useful tool for intraoperative margin assessment after neoadjuvant therapy?

PURPOSE: A previous study in our breast unit showed that the diagnostic accuracy of intraoperative specimen radiography and its potential to reduce second surgeries in a cohort of patients treated with neoadjuvant chemotherapy were low, which questions the routine use of Conventional specimen radiography (CSR) in this patient group. This is a follow-up study in a larger cohort to further evaluate these findings. METHODS: This retrospective study included 376 cases receiving breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NACT) of primary breast cancer. CSR was performed to assess potential margin infiltration and recommend an intraoperative re-excision of any radiologically positive margin. The histological workup of the specimen served as gold standard for the evaluation of the accuracy of CSR and the potential reduction of second surgeries by CSR-guided re-excisions. RESULTS: 362 patients with 2172 margins were assessed. The prevalence of positive margins was 102/2172 (4.7%). CSR had a sensitivity of 37.3%, a specificity of 85.6%, a positive predictive value (PPV) of 11.3%, and a negative predictive value (NPV) of 96.5%. The rate of secondary procedures was reduced from 75 to 37 with a number needed to treat (NNT) of CSR-guided intraoperative re-excisions of 10. In the subgroup of patients with clinical complete response (cCR), the prevalence of positive margins was 38/1002 (3.8%), PPV was 6.5% and the NNT was 34. CONCLUSION: This study confirms our previous finding that the rate of secondary surgeries cannot be significantly reduced by CSR-guided intraoperative re-excisions in cases with cCR after NACT. The routine use CSR after NACT is questionable, and alternative tools of intraoperative margin assessment should be evaluated.

Potential of Lesion-to-Fat Elasticity Ratio Measured by Shear Wave Elastography to Reduce Benign Biopsies in BI-RADS 4 Breast Lesions.

OBJECTIVES: We evaluated whether lesion-to-fat ratio measured by shear wave elastography in patients with Breast Imaging Reporting and Data System (BI-RADS) 3 or 4 lesions has the potential to further refine the assessment of B-mode ultrasound alone in breast cancer diagnostics. METHODS: This was a secondary analysis of an international diagnostic multicenter trial (NCT02638935). Data from 1288 women with breast lesions categorized as BI-RADS 3 and 4a-c by conventional B-mode ultrasound were analyzed, whereby the focus was placed on differentiating lesions categorized as BI-RADS 3 and BI-RADS 4a. All women underwent shear wave elastography and histopathologic evaluation functioning as reference standard. Reduction of benign biopsies as well as the number of missed malignancies after reclassification using lesion-to-fat ratio measured by shear wave elastography were evaluated. RESULTS: Breast cancer was diagnosed in 368 (28.6%) of 1288 lesions. The assessment with conventional B-mode ultrasound resulted in 53.8% (495 of 1288) pathologically benign lesions categorized as BI-RADS 4 and therefore false positives as well as in 1.39% (6 of 431) undetected malignancies categorized as BI-RADS 3. Additional lesion-to-fat ratio in BI-RADS 4a lesions with a cutoff value of 1.85 resulted in 30.11% biopsies of benign lesions which correspond to a reduction of 44.04% of false positives. CONCLUSIONS: Adding lesion-to-fat ratio measured by shear wave elastography to conventional B-mode ultrasound in BI-RADS 4a breast lesions could help reduce the number of benign biopsies by 44.04%. At the same time, however, 1.98% of malignancies were missed, which would still be in line with American College of Radiology BI-RADS 3 definition of <2% of undetected malignancies.

Imaging of lumpectomy surface with large field-of-view confocal laser scanning microscopy 'Histolog® scanner' for breast margin assessment in comparison with conventional specimen radiography.

PURPOSE: The Histolog® Scanner (SamanTree Medical SA, Lausanne, Switzerland) is a large field-of-view confocal laser scanning microscope designed to allow intraoperative margin assessment by the production of histological images ready for assessment in the operating room. We evaluated the feasibility and the performance of the Histolog® Scanner (HS) to correctly identify infiltrated margins in clinical practice of lumpectomy specimens. It was extrapolated if the utilization of the HS has the potential to reduce infiltrated margins and therefore reduce re-operation rates in patients undergoing breast conserving surgery (BCS) due to a primarily diagnosed breast cancer including ductal carcinoma in situ. METHODS: This is a single-center, prospective, non-interventional, diagnostic pilot study including 50 consecutive patients receiving BCS. The complete surface of the specimen was scanned using the HS intraoperatively. The surgery and the intraoperative margin assessment of the specimen was performed according to the clinical routine consisting of conventional specimen radiography as well as the clinical impression of the surgeon. Three surgeons and an experienced pathologist assessed the scans produced by the HS for cancer cells on the surface. The potential of the HS to correctly identify involved margins was compared to the results of the conventional specimen radiography alone as well as the clinical routine. The histopathological report served as the gold standard. RESULTS: 50 specimens corresponding to 300 surfaces were scanned by the HS. The mean sensitivity of the surgeons to identify involved margins with the HS was 37.5% ± 5.6%, the specificity was 75.2% ± 13.0%. The assessment of resection margins by the pathologist resulted in a sensitivity of 37.5% and a specificity of 81.0%, while the local clinical routine resulted in a sensitivity of 37.5% and a specificity of 78.2%. CONCLUSION: Acquisition of high-resolution histological images using the HS was feasible in clinical practice. Sensitivity and specificity were comparable to clinical routine. With more specific training and experience on image interpretation and acquisition, the HS may have the potential to enable more accuracy in the margin assessment of BCS specimens.

Intelligent multi-modal shear wave elastography to reduce unnecessary biopsies in breast cancer diagnosis (INSPiRED 002): a retrospective, international, multicentre analysis.

BACKGROUND: Breast ultrasound identifies additional carcinomas not detected in mammography but has a higher rate of false-positive findings. We evaluated whether use of intelligent multi-modal shear wave elastography (SWE) can reduce the number of unnecessary biopsies without impairing the breast cancer detection rate. METHODS: We trained, tested, and validated machine learning algorithms using SWE, clinical, and patient information to classify breast masses. We used data from 857 women who underwent B-mode breast ultrasound, SWE, and subsequent histopathologic evaluation at 12 study sites in seven countries from 2016 to 2019. Algorithms were trained and tested on data from 11 of the 12 sites and externally validated using the additional site's data. We compared findings to the histopathologic evaluation and compared the diagnostic performance between B-mode breast ultrasound, traditional SWE, and intelligent multi-modal SWE. RESULTS: In the external validation set (n = 285), intelligent multi-modal SWE showed a sensitivity of 100% (95% CI, 97.1-100%, 126 of 126), a specificity of 50.3% (95% CI, 42.3-58.3%, 80 of 159), and an area under the curve of 0.93 (95% CI, 0.90-0.96). Diagnostic performance was significantly higher compared to traditional SWE and B-mode breast ultrasound (P < 0.001). Unlike traditional SWE, positive-predictive values of intelligent multi-modal SWE were significantly higher compared to B-mode breast ultrasound. Unnecessary biopsies were reduced by 50.3% (79 versus 159, P < 0.001) without missing cancer compared to B-mode ultrasound. CONCLUSION: The majority of unnecessary breast biopsies might be safely avoided by using intelligent multi-modal SWE. These results may be helpful to reduce diagnostic burden for patients, providers, and healthcare systems.

Health Behavior and Cancer Prevention among Adults with Li-Fraumeni Syndrome and Relatives in Germany-A Cohort Description.

Li-Fraumeni-syndrome (LFS) is a rare, highly penetrant cancer predisposition syndrome (CPS) caused by pathogenic variants (PVs) in TP53. Physical activity (PA) and a Mediterranean diet lead to cancer reduction or survival benefits and increased quality of life (QoL), but this is yet unstudied among LFS. TP53 PV carriers (PVC) and their relatives were questioned on dietary patterns (Mediterranean Diet Adherence Screener), PA (Freiburg Questionnaire), QoL (Short-form-Health-Survey-12), smoking, alcohol consumption and perception of cancer risk in a German bi-centric study from March 2020-June 2021. The study enrolled 70 PVC and 43 relatives. Women compared to men (6.49 vs. 5.38, p = 0.005) and PVC to relatives (6.59 vs. 5.51; p = 0.006) showed a healthier diet, associated with participation in surveillance (p = 0.04) and education (diet p = 0.02 smoking p = 0.0003). Women smoked less (2.91 vs. 5.91 packyears; p = 0.03), psychological well-being was higher among men (SF-12: males 48.06 vs. females 41.94; p = 0.004). PVC rated their own cancer risk statistically higher than relatives (72% vs. 38%, p < 0.001) however, cancer risk of the general population was rated lower (38% vs. 70%, p < 0.001). A relative's cancer-related death increased the estimated personal cancer risk (p = 0.01). The possibilities of reducing cancer through self-determined health behavior among PVC and relatives has not yet been exhausted. Educating families with a CPS on cancer-preventive behavior requires further investigation with regard to acceptance and real-life implementation.

Genotype-phenotype associations within the Li-Fraumeni spectrum: a report from the German Registry.

Li-Fraumeni syndrome (LFS) is a cancer predisposition syndrome caused by pathogenic TP53 variants. The condition represents one of the most relevant genetic causes of cancer in children and adults due to its frequency and high cancer risk. The term Li-Fraumeni spectrum reflects the evolving phenotypic variability of the condition. Within this spectrum, patients who meet specific LFS criteria are diagnosed with LFS, while patients who do not meet these criteria are diagnosed with attenuated LFS. To explore genotype-phenotype correlations we analyzed 141 individuals from 94 families with pathogenic TP53 variants registered in the German Cancer Predisposition Syndrome Registry. Twenty-one (22%) families had attenuated LFS and 73 (78%) families met the criteria of LFS. NULL variants occurred in 32 (44%) families with LFS and in two (9.5%) families with attenuated LFS (P value < 0.01). Kato partially functional variants were present in 10 out of 53 (19%) families without childhood cancer except adrenocortical carcinoma (ACC) versus 0 out of 41 families with childhood cancer other than ACC alone (P value < 0.01). Our study suggests genotype-phenotype correlations encouraging further analyses.

Shear wave elastography as a supplemental tool in the assessment of unsuspicious axillary lymph nodes in patients undergoing breast ultrasound examination.

OBJECTIVES: To define reference values for shear wave elastography (SWE) in unsuspicious axillary lymph nodes in patients undergoing breast ultrasound examination. METHODS: In total, 177 clinically and sonographically unsuspicious axillary lymph nodes were prospectively evaluated with SWE using Virtual Touch Tissue Imaging Quantification (VTIQ) in 175 women. Mean values of tissue stiffness for axillary fatty tissue, lymph node cortex, and lymph node hilus were measured. Additionally, test-retest reliability of SWE in the assessment of axillary lymph node stiffness was evaluated by repeating each measurement three times. RESULTS: In 177 axillary lymph nodes, the mean stiffness of lymph node cortex, hilus, and surrounding fatty tissue as quantified by SWE was 1.90 m/s (SD: 0.34 m/s), 2.02 m/s (SD: 0.37 m/s), and 1.75 m/s (SD: 0.38 m/s), respectively. The mean stiffness of cortex and hilus was significantly higher compared to fatty tissue (p < 0.0001). SWE demonstrated good test-retest reliability in the assessment of stiffness of the lymph node hilus, cortex, and the surrounding fatty tissue with an intraclass correlation of 0.79 (95% CI: 0.75; 0.83), 0.75 (95% CI: 0.70; 0.79), and 0.78 (95% CI: 0.74; 0.82), respectively, (p < 0.0001). CONCLUSIONS: Reference values for SWE in unsuspicious axillary lymph nodes are determined. These results may help to better identify axillary lymph node metastasis for breast cancer patients when combined with other lymph node features. SWE is a reliable method for the objective quantification of tissue stiffness of axillary lymph nodes. ADVANCES IN KNOWLEDGE: This study presents physiological reference values for tissue stiffness by examining the axillary lymph nodes with SWE in 175 women with sonomorphologically unsuspicious lymph nodes.

How previous treatment changes the metabolomic profile in patients with metastatic breast cancer.

PURPOSE: Metabolites are in the spotlight of attention as promising novel breast cancer biomarkers. However, no study has been conducted concerning changes in the metabolomics profile of metastatic breast cancer patients according to previous therapy. METHODS: We performed a retrospective, single-center, nonrandomized, partially blinded, treatment-based study. Metastatic breast cancer (MBC) patients were enrolled between 03/2010 and 09/2016 at the beginning of a new systemic therapy. The endogenous metabolites in the plasma samples were analyzed using the AbsoluteIDQ® p180 Kit (Biocrates Life Sciences AG, Innsbruck) a targeted, quality and quantitative-controlled metabolomics approach. The statistical analysis was performed using R package, version 3.3.1. ANOVA was used to statistically assess age differences within groups. Furthermore, we analyzed the CTC status of the patients using the CellSearch™ assay. RESULTS: We included 178 patients in our study. Upon dividing the study population according to therapy before study inclusion, we found the following: 4 patients had received no therapy, 165 chemotherapy, and 135 anti-hormonal therapy, 30 with anti-Her2 therapy and 38 had received treatment with bevacizumab. Two metabolites were found to be significantly different, depending on the further therapy of the patients: methionine and serine. Whereas methionine levels were higher in the blood of patients who received an anti-Her2-therapy, serine was lower in patients with endocrine therapy only. CONCLUSION: We identified two metabolites for which concentrations differed significantly depending on previous therapies, which could help to choose the next therapy in patients who have already received numerous different treatments.

Potential of blood-based biomarker approaches in endometrium and breast cancer: a case-control comparison study.

PURPOSE: Endometrial carcinoma is the second most common gynecological malignancy. Until today lacking a screening tool. A blood-based biomarker could help address this need. METHODS: The expression levels of 30 acylcarnitines, 18 amino acids, 6 miRNAs, and 7 DNA methylation sites were measured in blood samples from 331 women (20 EC, 14 benign uterine lesions (benign), 140 breast cancers (BC), 157 controls). Areas under the ROC curves (AUC), sensitivity (sens.) and specificity (spec.) were computed to identify the variables best distinguishing. RESULTS: The best top ten markers for the four comparisons (cancer vs. cancer-free; EC vs. BC, EC vs. controls; EC vs. benign), were identified via AUC. Malonylcarnitine distinguished best patients with EC from controls (AUC: 0.827, sens. 80%, spec. 73.1%) or BC (AUC: 0.819, sens. 84.3%, spec. 80%) being most notable. Tryptophan best differentiated benign from EC (AUC: 0.846, sens. 70%, spec. 92.9%). CONCLUSIONS: The levels of the analyzed blood markers yielded promising results in the detection of EC and warrant further evaluation.

The importance of multi-modal imaging and clinical information for humans and AI-based algorithms to classify breast masses (INSPiRED 003): an international, multicenter analysis.

OBJECTIVES: AI-based algorithms for medical image analysis showed comparable performance to human image readers. However, in practice, diagnoses are made using multiple imaging modalities alongside other data sources. We determined the importance of this multi-modal information and compared the diagnostic performance of routine breast cancer diagnosis to breast ultrasound interpretations by humans or AI-based algorithms. METHODS: Patients were recruited as part of a multicenter trial (NCT02638935). The trial enrolled 1288 women undergoing routine breast cancer diagnosis (multi-modal imaging, demographic, and clinical information). Three physicians specialized in ultrasound diagnosis performed a second read of all ultrasound images. We used data from 11 of 12 study sites to develop two machine learning (ML) algorithms using unimodal information (ultrasound features generated by the ultrasound experts) to classify breast masses which were validated on the remaining study site. The same ML algorithms were subsequently developed and validated on multi-modal information (clinical and demographic information plus ultrasound features). We assessed performance using area under the curve (AUC). RESULTS: Of 1288 breast masses, 368 (28.6%) were histopathologically malignant. In the external validation set (n = 373), the performance of the two unimodal ultrasound ML algorithms (AUC 0.83 and 0.82) was commensurate with performance of the human ultrasound experts (AUC 0.82 to 0.84; p for all comparisons > 0.05). The multi-modal ultrasound ML algorithms performed significantly better (AUC 0.90 and 0.89) but were statistically inferior to routine breast cancer diagnosis (AUC 0.95, p for all comparisons ≤ 0.05). CONCLUSIONS: The performance of humans and AI-based algorithms improves with multi-modal information. KEY POINTS: • The performance of humans and AI-based algorithms improves with multi-modal information. • Multimodal AI-based algorithms do not necessarily outperform expert humans. • Unimodal AI-based algorithms do not represent optimal performance to classify breast masses.

A New Practical Decision Rule to Better Differentiate BI-RADS 3 or 4 Breast Masses on Breast Ultrasound.

OBJECTIVES: The BI-RADS classification provides a standardized way to describe ultrasound findings in breast cancer diagnostics. However, there is little information regarding which BI-RADS descriptors are most strongly associated with malignancy, to better distinguish BI-RADS 3 (follow-up imaging) and 4 (diagnostic biopsy) breast masses. METHODS: Patients were recruited as part of an international, multicenter trial (NCT02638935). The trial enrolled 1294 women (6 excluded) categorized as BI-RADS 3 or 4 upon routine B-mode ultrasound examination. Ultrasound images were evaluated by three expert physicians according to BI-RADS. All patients underwent histopathological confirmation (reference standard). We performed univariate and multivariate analyses (chi-square test, logistic regression, and Krippendorff's alpha). RESULTS: Histopathologic evaluation showed malignancy in 368 of 1288 masses (28.6%). Upon performing multivariate analysis, the following descriptors were significantly associated with malignancy (P < .05): age ≥50 years (OR 8.99), non-circumscribed indistinct (OR 4.05) and microlobulated margin (OR 2.95), nonparallel orientation (OR 2.69), and calcification (OR 2.64). A clinical decision rule informed by these results demonstrated a 97% sensitivity and missed fewer cancers compared to three physician experts (range of sensitivity 79-95%) and a previous decision rule (sensitivity 59%). Specificity was 44% versus 22-83%, respectively. The inter-reader reliability of the BI-RADS descriptors and of the final BI-RADS score was fair-moderate. CONCLUSIONS: A patient should undergo a diagnostic biopsy (BI-RADS 4) instead of follow-up imaging (BI-RADS 3) if the patient is 50 years or older or exhibits at least one of the following features: calcification, nonparallel orientation of mass, non-circumscribed margin, or posterior shadowing.

Does conventional specimen radiography after neoadjuvant chemotherapy of breast cancer help to reduce the rate of second surgeries?

PURPOSE: This is the first study to systematically evaluate the diagnostic accuracy of intraoperative specimen radiography on margin level and its potential to reduce second surgeries in patients treated with neoadjuvant chemotherapy. METHODS: This retrospective study included 174 cases receiving breast conserving surgery (BCS) after neoadjuvant chemotherapy (NACT) of primary breast cancer. Conventional specimen radiography (CSR) was performed to assess potential margin infiltration and recommend an intraoperative re-excision of any radiologically positive margin. The histological workup of the specimen served as gold standard for the evaluation of the accuracy of CSR and the potential reduction of second surgeries by CSR-guided re-excisions. RESULTS: 1044 margins were assessed. Of 47 (4.5%) histopathological positive margins, CSR identified 9 correctly (true positive). 38 infiltrated margins were missed (false negative). This resulted in a sensitivity of 19.2%, a specificity of 89.2%, a positive predictive value (PPV) of 7.7%, and a negative predictive value (NPV) of 95.9%. The rate of secondary procedures was reduced from 23 to 16 with a number needed to treat (NNT) of CSR-guided intraoperative re-excisions of 25. In the subgroup of patients with cCR, the prevalence of positive margins was 10/510 (2.0%), PPV was 1.9%, and the NNT was 85. CONCLUSION: Positive margins after NACT are rare and CSR has only a low sensitivity to detect them. Thus, the rate of secondary surgeries cannot be significantly reduced by recommending targeted re-excisions, especially in cases with cCR. In summary, CSR after NACT is inadequate for intraoperative margin assessment but remains useful to document removal of the biopsy site clip.

Evaluation of the FUSION-X-US-II prototype to combine automated breast ultrasound and tomosynthesis.

OBJECTIVE: The FUSION-X-US-II prototype was developed to combine 3D automated breast ultrasound (ABUS) and digital breast tomosynthesis in a single device. We evaluated the performance of ABUS and tomosynthesis in a single examination in a clinical setting. METHODS: In this prospective feasibility study, digital breast tomosynthesis and ABUS were performed using the FUSION-X-US-II prototype without any change of the breast position in patients referred for clarification of breast lesions with an indication for tomosynthesis. The tomosynthesis and ABUS images of the prototype were interpreted independently from the clinical standard by a breast diagnostics specialist. Any detected lesion was classified using BI-RADS® scores, and results of the standard clinical routine workup (gold standard) were compared to the result of the separate evaluation of the prototype images. Image quality was rated subjectively and coverage of the breast was measured. RESULTS: One hundred one patients received both ABUS and tomosynthesis using the prototype. The duration of the additional ABUS acquisition was 40 to 60 s. Breast coverage by ABUS was approximately 80.0%. ABUS image quality was rated as diagnostically useful in 86 of 101 cases (85.1%). Thirty-three of 34 malignant breast lesions (97.1%) were identified using the prototype. CONCLUSION: The FUSION-X-US-II prototype allows a fast ABUS scan in combination with digital breast tomosynthesis in a single device integrated in the clinical workflow. Malignant breast lesions can be localized accurately with direct correlation of ABUS and tomosynthesis images. The FUSION system shows the potential to improve breast cancer screening in the future after further technical improvements. KEY POINTS: • The FUSION-X-US-II prototype allows the combination of automated breast ultrasound and digital breast tomosynthesis in a single device without decompression of the breast. • Image quality and coverage of ABUS are sufficient to accurately detect malignant breast lesions. • If tomosynthesis and ABUS should become part of breast cancer screening, the combination of both techniques in one device could offer practical and logistic advantages. To evaluate a potential benefit of a combination of ABUS and tomosynthesis in screening-like settings, further studies are needed.

Intramural pregnancy: A case report.

A 24-year-old woman, who had undergone neither fertility treatment nor uterine surgery other than a cesarean section, presented with an intramural ectopic pregnancy. A laparotomy with uterine wedge resection including the embryonic tissue was performed. The postoperative course was uneventful, with falling ßHCG levels. Two months after surgery she presented again with an intrauterine pregnancy.