Enhancing the Kaiser score for lesion characterization in unenhanced breast MRI.

PURPOSE: To adapt the methodology of the Kaiser score, a clinical decision rule for lesion characterization in breast MRI, for unenhanced protocols. METHOD: In this retrospective IRB-approved cross-sectional study, we included 93 consecutive patients who underwent breast MRI between 2021 and 2023 for further work-up of BI-RADS 0, 3-5 in conventional imaging or for staging purposes (BI-RADS 6). All patients underwent biopsy for histologic verification or were followed for a minimum of 12 months. MRI scans were conducted using 1.5 T or 3 T scanners using dedicated breast coils and a protocol in line with international recommendations including DWI and ADC. Lesion characterization relied solely on T2w and DWI/ADC-derived features (such as lesion type, margins, shape, internal signal, surrounding tissue findings, ADC value). Statistical analysis was done using decision tree analysis aiming to distinguish benign (histology/follow-up) from malignant outcomes. RESULTS: We analyzed a total of 161 lesions (81 of them non-mass) with a malignancy rate of 40%. Lesion margins (spiculated, irregular, or circumscribed) were identified as the most important criterion within the decision tree, followed by the ADC value as second most important criterion. The resulting score demonstrated a strong diagnostic performance with an AUC of 0.840, providing both rule-in and rule-out criteria. In an independent test set of 65 lesions the diagnostic performance was verified by two readers (AUC 0.77 and 0.87, kappa: 0.62). CONCLUSIONS: We developed a clinical decision rule for unenhanced breast MRI including lesion margins and ADC value as the most important criteria, achieving high diagnostic accuracy.

Using the Kaiser Score as a clinical decision rule for breast lesion classification: Does computer-assisted curve type analysis improve diagnosis?

PURPOSE: We aimed to investigate the effect of using visual or automatic enhancement curve type assessment on the diagnostic performance of the Kaiser Score (KS), a clinical decision rule for breast MRI. METHOD: This IRB-approved retrospective study analyzed consecutive conventional BI-RADS 0, 4 or 5 patients who underwent biopsy after 1.5T breast MRI according to EUSOBI recommendations between 2013 and 2015. The KS includes five criteria (spiculations; signal intensity (SI)-time curve type; margins of the lesion; internal enhancement; and presence of edema) resulting in scores from 1 (=lowest) to 11 (=highest risk of breast cancer). Enhancement curve types (Persistent, Plateau or Wash-out) were assessed by two radiologists independently visually and using a pixel-wise color-coded computed parametric map of curve types. KS diagnostic performance differences between readings were compared by ROC analysis. RESULTS: In total 220 lesions (147 benign, 73 malignant) including mass (n = 148) and non-mass lesions (n = 72) were analyzed. KS reading performance in distinguishing benign from malignant lesions did not differ between visual analysis and parametric map (P = 0.119; visual: AUC 0.875, sensitivity 95 %, specificity 63 %; and map: AUC 0.901, sensitivity 97 %, specificity 65 %). Additionally, analyzing mass and non-mass lesions separately, showed no difference between parametric map based and visual curve type-based KS analysis as well (P = 0.130 and P = 0.787). CONCLUSIONS: The performance of the Kaiser Score is largely independent of the curve type assessment methodology, confirming its robustness as a clinical decision rule for breast MRI in any type of breast lesion in clinical routine.

How much can abbreviated protocols for breast MRI increase patient throughput? a multi-centric evaluation.

PURPOSE: To assess the impact of abbreviated breast MRI protocols on patient throughput considering non-scanning time and differences between in- and out-of-hospital settings. MATERIALS & METHODS: A total of 143 breast MRI exams from four study sites (hospital, three radiology centers) were included in this retrospective study. Total exam time (TET), Table Time (TT), Scan Time (ST), Table Switch Time (TST) and Planning Time (PT) were determined from consecutive breast MRI examinations. Possible number of scans and exams per hour were calculated. Four scan protocols were compared: full diagnostic protocol (n = 34, hospital), split dynamic protocol (n = 109, all sites) and two abbreviated protocols (n = 109, calculated, all sites). Data were described as median and interquartile range (IQR) and compared by Mann-Whitney-U-Test. RESULTS: Non-scanning time increased from 50% to 74% of the TET with a TST of 46% and a PT of 28% in the shortest abbreviated protocol. Number of possible scans per hour increased from 4.7 to 18.8 while number of possible exams per hour only increased from 2.3 to 5.1. Absolute TST (4.7 vs. 5.7 min, p = 0.46) and TET (18 min each, p = 0.35) did not differ significantly between in- and out-of-hospital exams. Absolute (4.4 vs. 2.8 min, p < 0.001) and relative (23 vs. 13%, p < 0.001) PT and TT (13.3 vs. 11.5 min, p = 0.004) was longer and relative TST (27% vs. 34%, p = 0.047) was shorter in hospital. CONCLUSION: TST and PT significantly contribute to TET and challenge the effectiveness of abbreviated protocols for increasing patient throughput. These findings show only low setting-dependent differences.

Impact of PI-QUAL on PI-RADS and cancer yield in an MRI-TRUS fusion biopsy population.

PURPOSE: To test the inter-reader agreement of the Prostate Imaging Quality (PI-QUAL) score for multiparametric prostate MRI and its impact on diagnostic performance in an MRI-ultrasound fusion biopsy population. PATIENTS AND METHODS: Pre-biopsy multiparametric (T2-weighted, DWI, and DCE) prostate MRIs (mpMRI) of 50 patients undergoing transrectal ultrasound-guided MRI-fusion (MRI-TRUS) biopsy were included. Two radiologists independently assigned a PI-QUAL score to each patient and assessed the diagnostic quality of individual sequences. PI-RADS categories were assigned to six regions per prostate (left and right: base/mid-glandular/apex). Inter-reader agreement was calculated using Cohen's kappa and diagnostic performance was compared by the area under the receiver operating characteristics curve (AUC). RESULTS: In 274 diagnostic areas, the malignancy rate was 62.7% (22.5% clinically significant prostate cancer, ISUP ≥ 2). Inter-reader agreement for the diagnostic quality was poor for T2w (kappa 0.19), fair for DWI and DCE (kappa 0.23 and 0.29) and moderate for PI-QUAL (kappa 0.51). For PI-RADS category assignments, inter-reader agreement was very good (kappa 0.86). Overall diagnostic performance did not differ between studies with a PI-QUAL score > 3 compared to a score ≤ 3 (p = 0.552; AUC 0.805 and 0.839). However, the prevalence of prostate cancer was significantly lower when the PI-QUAL score was ≤ 3 (16.7% vs. 30.2%, p = 0.008). CONCLUSION: PI-QUAL has only a limited impact on PI-RADS diagnostic performance in patients scheduled for MRI-TRUS fusion biopsy. However, the lower cancer prevalence in the lower PI-QUAL categories points out a risk of false-positive referrals and unnecessary biopsies if prostate imaging quality is low.

AI-enhanced simultaneous multiparametric 18F-FDG PET/MRI for accurate breast cancer diagnosis.

PURPOSE: To assess whether a radiomics and machine learning (ML) model combining quantitative parameters and radiomics features extracted from simultaneous multiparametric 18F-FDG PET/MRI can discriminate between benign and malignant breast lesions. METHODS: A population of 102 patients with 120 breast lesions (101 malignant and 19 benign) detected on ultrasound and/or mammography was prospectively enrolled. All patients underwent hybrid 18F-FDG PET/MRI for diagnostic purposes. Quantitative parameters were extracted from DCE (MTT, VD, PF), DW (mean ADC of breast lesions and contralateral breast parenchyma), PET (SUVmax, SUVmean, and SUVminimum of breast lesions, as well as SUVmean of the contralateral breast parenchyma), and T2-weighted images. Radiomics features were extracted from DCE, T2-weighted, ADC, and PET images. Different diagnostic models were developed using a fine Gaussian support vector machine algorithm which explored different combinations of quantitative parameters and radiomics features to obtain the highest accuracy in discriminating between benign and malignant breast lesions using fivefold cross-validation. The performance of the best radiomics and ML model was compared with that of expert reader review using McNemar's test. RESULTS: Eight radiomics models were developed. The integrated model combining MTT and ADC with radiomics features extracted from PET and ADC images obtained the highest accuracy for breast cancer diagnosis (AUC 0.983), although its accuracy was not significantly higher than that of expert reader review (AUC 0.868) (p = 0.508). CONCLUSION: A radiomics and ML model combining quantitative parameters and radiomics features extracted from simultaneous multiparametric 18F-FDG PET/MRI images can accurately discriminate between benign and malignant breast lesions.

Supervised machine learning enables non-invasive lesion characterization in primary prostate cancer with [68Ga]Ga-PSMA-11 PET/MRI.

PURPOSE: Risk classification of primary prostate cancer in clinical routine is mainly based on prostate-specific antigen (PSA) levels, Gleason scores from biopsy samples, and tumor-nodes-metastasis (TNM) staging. This study aimed to investigate the diagnostic performance of positron emission tomography/magnetic resonance imaging (PET/MRI) in vivo models for predicting low-vs-high lesion risk (LH) as well as biochemical recurrence (BCR) and overall patient risk (OPR) with machine learning. METHODS: Fifty-two patients who underwent multi-parametric dual-tracer [18F]FMC and [68Ga]Ga-PSMA-11 PET/MRI as well as radical prostatectomy between 2014 and 2015 were included as part of a single-center pilot to a randomized prospective trial (NCT02659527). Radiomics in combination with ensemble machine learning was applied including the [68Ga]Ga-PSMA-11 PET, the apparent diffusion coefficient, and the transverse relaxation time-weighted MRI scans of each patient to establish a low-vs-high risk lesion prediction model (MLH). Furthermore, MBCR and MOPR predictive model schemes were built by combining MLH, PSA, and clinical stage values of patients. Performance evaluation of the established models was performed with 1000-fold Monte Carlo (MC) cross-validation. Results were additionally compared to conventional [68Ga]Ga-PSMA-11 standardized uptake value (SUV) analyses. RESULTS: The area under the receiver operator characteristic curve (AUC) of the MLH model (0.86) was higher than the AUC of the [68Ga]Ga-PSMA-11 SUVmax analysis (0.80). MC cross-validation revealed 89% and 91% accuracies with 0.90 and 0.94 AUCs for the MBCR and MOPR models respectively, while standard routine analysis based on PSA, biopsy Gleason score, and TNM staging resulted in 69% and 70% accuracies to predict BCR and OPR respectively. CONCLUSION: Our results demonstrate the potential to enhance risk classification in primary prostate cancer patients built on PET/MRI radiomics and machine learning without biopsy sampling.

Impact of the Kaiser score on clinical decision-making in BI-RADS 4 mammographic calcifications examined with breast MRI.

OBJECTIVES: To investigate whether the application of the Kaiser score for breast magnetic resonance imaging (MRI) might downgrade breast lesions that present as mammographic calcifications and avoid unnecessary breast biopsies METHODS: This IRB-approved, retrospective, cross-sectional, single-center study included 167 consecutive patients with suspicious mammographic calcifications and histopathologically verified results. These patients underwent a pre-interventional breast MRI exam for further diagnostic assessment before vacuum-assisted stereotactic-guided biopsy (95 malignant and 72 benign lesions). Two breast radiologists with different levels of experience independently read all examinations using the Kaiser score, a machine learning-derived clinical decision-making tool that provides probabilities of malignancy by a formalized combination of diagnostic criteria. Diagnostic performance was assessed by receiver operating characteristics (ROC) analysis and inter-reader agreement by the calculation of Cohen's kappa coefficients. RESULTS: Application of the Kaiser score revealed a large area under the ROC curve (0.859-0.889). Rule-out criteria, with high sensitivity, were applied to mass and non-mass lesions alike. The rate of potentially avoidable breast biopsies ranged between 58.3 and 65.3%, with the lowest rate observed with the least experienced reader. CONCLUSIONS: Applying the Kaiser score to breast MRI allows stratifying the risk of breast cancer in lesions that present as suspicious calcifications on mammography and may thus avoid unnecessary breast biopsies. KEY POINTS: • The Kaiser score is a helpful clinical decision tool for distinguishing malignant from benign breast lesions that present as calcifications on mammography. • Application of the Kaiser score may obviate 58.3-65.3% of unnecessary stereotactic biopsies of suspicious calcifications. • High Kaiser scores predict breast cancer with high specificity, aiding clinical decision-making with regard to re-biopsy in case of negative results.

Can the addition of clinical information improve the accuracy of PI-RADS version 2 for the diagnosis of clinically significant prostate cancer in positive MRI?

AIM: To report prostate cancer (PCa) prevalence in Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) categories and investigate the potential to avoid unnecessary, magnetic resonance imaging (MRI)-guided in-bore biopsies by adding clinical and biochemical patient characteristics. MATERIALS AND METHODS: The present institutional review board-approved, prospective study on 137 consecutive men with 178 suspicious lesions on 3 T MRI was performed. Routine data collected for each patient included patient characteristics (age, prostate volume), clinical background information (prostate-specific antigen [PSA] levels, PSA density), and PI-RADS v2 scores assigned in a double-reading approach. RESULTS: Histopathological evaluation revealed a total of 93/178 PCa (52.2%). The mean age was 66.3 years and PSA density was 0.24 ng/ml2 (range, 0.04-0.89 ng/ml). Clinically significant PCa (csPCa, Gleason score >6) was confirmed in 50/93 (53.8%) lesions and was significantly associated with higher PI-RADS v2 scores (p=0.0044). On logistic regression analyses, age, PSA density, and PI-RADS v2 scores contributed independently to the diagnosis of csPCa (p=7.9×10-7, p=0.097, and p=0.024, respectively). The resulting area under the receiver operating characteristic curve (AUC) to predict csPCa was 0.76 for PI-RADS v2, 0.59 for age, and 0.67 for PSA density. The combined regression model yielded an AUC of 0.84 for the diagnosis of csPCa and was significantly superior to each single parameter (p≤0.0009, respectively). Unnecessary biopsies could have been avoided in 50% (64/128) while only 4% (2/50) of csPCa lesions would have been missed. CONCLUSIONS: Adding age and PSA density to PI-RADS v2 scores improves the diagnostic accuracy for csPCa. A combination of these variables with PI-RADS v2 can help to avoid unnecessary in-bore biopsies while still detecting the majority of csPCa.

[Contrast agent-free breast MRI : Advantages and potential disadvantages]. / Kontrastmittelfreie Mamma-MRT : Vorteile und potenzielle Nachteile.

BACKGROUND: Contrast-enhanced breast magnetic resonance imaging (MRI) is the most sensitive method for detection of breast cancer. The further spread of breast MRI is limited by the complicated examination procedure and the need for intravenously administered contrast media. OBJECTIVES: Can diffusion-weighted imaging (DWI) replace contrast-enhanced sequences to achieve an unenhanced breast MRI examination? MATERIALS AND METHODS: Narrative review and meta-analytic assessment of previously published studies. RESULTS: DWI can visualize breast lesions and distinguish benign from malignant findings. It is thus a valid alternative to contrast-enhanced sequences. As an additional technique, the use of DWI can reduce the numbers of unnecessary breast biopsies. The lack of robustness leading to variable sensitivity that is currently lower than that of contrast-enhanced breast MRI is a disadvantage of DWI. CONCLUSIONS: Presently, DWI can be recommended as an integral part of clinical breast MRI protocols. The application as a stand-alone technique within unenhanced protocols is still under evaluation.

Impact of androgen deprivation therapy on apparent diffusion coefficient and T2w MRI for histogram and texture analysis with respect to focal radiotherapy of prostate cancer.

PURPOSE: Accurate prostate cancer (PCa) detection is essential for planning focal external beam radiotherapy (EBRT). While biparametric MRI (bpMRI) including T2-weighted (T2w) and diffusion-weighted images (DWI) is an accurate tool to localize PCa, its value is less clear in the case of additional androgen deprivation therapy (ADT). The aim of this study was to investigate the value of a textural feature (TF) approach on bpMRI analysis in prostate cancer patients with and without neoadjuvant ADT with respect to future dose-painting applications. METHODS: 28 PCa patients (54-80 years) with (n = 14) and without (n = 14) ADT who underwent bpMRI with T2w and DWI were analyzed retrospectively. Lesions, central gland (CG), and peripheral zone (PZ) were delineated by an experienced urogenital radiologist based on localized pre-therapeutic histopathology. Histogram parameters and 20 Haralick TF were calculated. Regional differences (i. e., tumor vs. PZ, tumor vs. CG) were analyzed for all imaging parameters. Receiver-operating characteristic (ROC) analysis was performed to measure diagnostic performance to distinguish PCa from benign prostate tissue and to identify the features with best discriminative power in both patient groups. RESULTS: The obtained sensitivities were equivalent or superior when utilizing the TF in the no-ADT group, while specificity was higher for the histogram parameters. However, in the ADT group, TF outperformed the conventional histogram parameters in both specificity and sensitivity. Rule-in and rule-out criteria for ADT patients could exclusively be defined with the aid of TF. CONCLUSIONS: The TF approach has the potential for quantitative image-assisted boost volume delineation in PCa patients even if they are undergoing neoadjuvant ADT.

Imaging and the completion of the omics paradigm in breast cancer.

Within the field of oncology, "omics" strategies-genomics, transcriptomics, proteomics, metabolomics-have many potential applications and may significantly improve our understanding of the underlying processes of cancer development and progression. Omics strategies aim to develop meaningful imaging biomarkers for breast cancer (BC) by rapid assessment of large datasets with different biological information. In BC the paradigm of omics technologies has always favored the integration of multiple layers of omics data to achieve a complete portrait of BC. Advances in medical imaging technologies, image analysis, and the development of high-throughput methods that can extract and correlate multiple imaging parameters with "omics" data have ushered in a new direction in medical research. Radiogenomics is a novel omics strategy that aims to correlate imaging characteristics (i. e., the imaging phenotype) with underlying gene expression patterns, gene mutations, and other genome-related characteristics. Radiogenomics not only represents the evolution in the radiology-pathology correlation from the anatomical-histological level to the molecular level, but it is also a pivotal step in the omics paradigm in BC in order to fully characterize BC. Armed with modern analytical software tools, radiogenomics leads to new discoveries of quantitative and qualitative imaging biomarkers that offer hitherto unprecedented insights into the complex tumor biology and facilitate a deeper understanding of cancer development and progression. The field of radiogenomics in breast cancer is rapidly evolving, and results from previous studies are encouraging. It can be expected that radiogenomics will play an important role in the future and has the potential to revolutionize the diagnosis, treatment, and prognosis of BC patients. This article aims to give an overview of breast radiogenomics, its current role, future applications, and challenges.

Clinical role of breast MRI now and going forward.

Magnetic resonance imaging (MRI) is a well-established method in breast imaging, with manifold clinical applications, including the non-invasive differentiation between benign and malignant breast lesions, preoperative staging, detection of scar versus recurrence, implant assessment, and the evaluation of high-risk patients. At present, dynamic contrast-enhanced MRI is the most sensitive imaging technique for breast cancer diagnosis, and provides excellent morphological and to some extent also functional information. To compensate for the limited functional information, and to increase the specificity of MRI while preserving its sensitivity, additional functional parameters such as diffusion-weighted imaging and apparent diffusion coefficient mapping, and MR spectroscopic imaging have been investigated and implemented into the clinical routine. Several additional MRI parameters to capture breast cancer biology are still under investigation. MRI at high and ultra-high field strength and advances in hard- and software may also further improve this imaging technique. This article will review the current clinical role of breast MRI, including multiparametric MRI and abbreviated protocols, and provide an outlook on the future of this technique. In addition, the predictive and prognostic value of MRI as well as the evolving field of radiogenomics will be discussed.

Diaryliodonium salts as hydrosilylation initiators for the surface functionalization of silicon nanomaterials and their collaborative effect as ring opening polymerization initiators.

Diaryliodonium salts were found to initiate hydrosilylation reactions on the surface of silicon nanosheets as well as silicon nanocrystals of different sizes. A variety of different functional substrates can be used to stabilize the surface of the photoluminescent materials. Additionally, the combination of hydride terminated silicon nanomaterials with diaryliodonium salts was found to initiate cationic ring opening polymerization, demonstrating the potential of silicon based nanomaterials as coinitiators and enabling a mild, straightforward reaction method.

[Multiparametric and molecular imaging of breast tumors with MRI and PET/MRI]. / Multiparametrische und molekulare Bildgebung von Brusttumoren mit MRT und PET­MRT.

CLINICAL/METHODICAL ISSUE: Magnetic resonance imaging (MRI) of the breast is an indispensable tool in breast imaging for many indications. Several functional parameters with MRI and positron emission tomography (PET) have been assessed for imaging of breast tumors and their combined application is defined as multiparametric imaging. Available data suggest that multiparametric imaging using different functional MRI and PET parameters can provide detailed information about the hallmarks of cancer and may provide additional specificity. STANDARD RADIOLOGICAL METHODS: Multiparametric and molecular imaging of the breast comprises established MRI parameters, such as dynamic contrast-enhanced MRI, diffusion-weighted imaging (DWI), MR proton spectroscopy ((1)H-MRSI) as well as combinations of radiological and MRI techniques (e. g. PET/CT and PET/MRI) using radiotracers, such as fluorodeoxyglucose (FDG). METHODICAL INNOVATIONS: Multiparametric and molecular imaging of the breast can be performed at different field-strengths (range 1.5-7 T). Emerging parameters comprise novel promising techniques, such as sodium imaging ((23)Na MRI), phosphorus spectroscopy ((31)P-MRSI), chemical exchange saturation transfer (CEST) imaging, blood oxygen level-dependent (BOLD) and hyperpolarized MRI as well as various specific radiotracers. ACHIEVEMENTS: Multiparametric and molecular imaging has multiple applications in breast imaging. Multiparametric and molecular imaging of the breast is an evolving field that will enable improved detection, characterization, staging and monitoring for personalized medicine in breast cancer.

Inter- and intra-observer agreement of BI-RADS-based subjective visual estimation of amount of fibroglandular breast tissue with magnetic resonance imaging: comparison to automated quantitative assessment.

PURPOSE: To evaluate the inter-/intra-observer agreement of BI-RADS-based subjective visual estimation of the amount of fibroglandular tissue (FGT) with magnetic resonance imaging (MRI), and to investigate whether FGT assessment benefits from an automated, observer-independent, quantitative MRI measurement by comparing both approaches. MATERIALS AND METHODS: Eighty women with no imaging abnormalities (BI-RADS 1 and 2) were included in this institutional review board (IRB)-approved prospective study. All women underwent un-enhanced breast MRI. Four radiologists independently assessed FGT with MRI by subjective visual estimation according to BI-RADS. Automated observer-independent quantitative measurement of FGT with MRI was performed using a previously described measurement system. Inter-/intra-observer agreements of qualitative and quantitative FGT measurements were assessed using Cohen's kappa (k). RESULTS: Inexperienced readers achieved moderate inter-/intra-observer agreement and experienced readers a substantial inter- and perfect intra-observer agreement for subjective visual estimation of FGT. Practice and experience reduced observer-dependency. Automated observer-independent quantitative measurement of FGT was successfully performed and revealed only fair to moderate agreement (k = 0.209-0.497) with subjective visual estimations of FGT. CONCLUSION: Subjective visual estimation of FGT with MRI shows moderate intra-/inter-observer agreement, which can be improved by practice and experience. Automated observer-independent quantitative measurements of FGT are necessary to allow a standardized risk evaluation. KEY POINTS: • Subjective FGT estimation with MRI shows moderate intra-/inter-observer agreement in inexperienced readers. • Inter-observer agreement can be improved by practice and experience. • Automated observer-independent quantitative measurements can provide reliable and standardized assessment of FGT with MRI.

Diffusion-weighted imaging of breast tumours at 3 Tesla and 7 Tesla: a comparison.

OBJECTIVES: To compare bilateral diffusion-weighted MR imaging (DWI) at 3 T and 7 T in the same breast tumour patients. METHODS: Twenty-eight patients were included in this IRB-approved study (mean age 56 ± 16 years). Before contrast-enhanced imaging, bilateral DWI with b = 0 and 850 s/mm(2) was performed in 2:56 min (3 T) and 3:48 min (7 T), using readout-segmented echo planar imaging (rs-EPI) with a 1.4 × 1.4 mm(2) (3 T)/0.9 × 0.9 mm(2) (7 T) in-plane resolution. Apparent diffusion coefficients (ADC), signal-to-noise (SNR) and contrast-to-noise ratios (CNR) were assessed. RESULTS: Twenty-eight lesions were detected (18 malignant, 10 benign). CNR and SNR were comparable at both field strengths (p > 0.3). Mean ADC values at 7 T were 4-22% lower than at 3 T (p ≤ 0.03). An ADC threshold of 1.275 × 10(-3) mm(2)/s resulted in a diagnostic specificity of 90% at both field strengths. The sensitivity was 94% and 100% at 3 T and 7 T, respectively. CONCLUSION: 7-T DWI of the breast can be performed with 2.4-fold higher spatial resolution than 3 T, without significant differences in SNR if compared to 3 T. KEY POINTS: • 7 T provides a 2.4-fold higher resolution in breast DWI than 3 T • 7 T DWI has a high diagnostic accuracy comparable to that at 3 T • At 7 T malignant lesions had 22 % lower ADC than at 3 T (p < 0.001).

Clinical Practice Guideline for the prevention and early detection of breast and ovarian cancer in women from HBOC (hereditary breast and ovarian cancer) families.

An estimated 10% of breast cancer cases exhibit a higher familial incidence, and functional mutations in BRCA (breast cancer-gene) 1 or 2 are responsible for the development of malignant tumors in approximately half of these cases. Women with a germline mutation in either of the two genes have a lifetime risk of up to 85% to develop breast cancer, and of up to 60% risk to develop ovarian cancer. This clinical practice guideline defines the individual and familial tumor constellations that represent an indication for BRCA germline testing. It also describes the therapeutic options (early detection programme vs prophylactic surgery) that arise from the result of a BRCA mutational analysis. This guideline further includes recommendations regarding the use of multigene panels and therapeutic aspects that arise from the selective use of poly ADP ribose polymerase (PARP) inhibitors in patients with known BRCA1 or 2 mutations. It replaces the previous version of the "Clinical Practice Guideline for the Prevention and Early Detection of Breast- and Ovarian Cancer in women from HBOC (hereditary breast and ovarian cancer) families" which was published in 2012.

Technical Note: evaluation of the uncertainties in (choline + creatine)/citrate ratios measured by proton MR spectroscopic imaging in patients suspicious for prostate cancer.

The presented evaluation of the relative uncertainty (δ'CCC) of the (choline + creatine)/citrate (CC/C) ratios can provide objective information about the quality and diagnostic value of prostate MR spectroscopic imaging data. This information can be combined with the numeric values of CC/C ratios and provides metabolic-quality maps enabling accurate cancer detection and user-independent data evaluation. In addition, the prostate areas suffering most from the low precision of CC/C ratios (e. g., prostate base) were identified.