A novel assessment of whole-mount Gleason grading in prostate cancer to identify candidates for radical prostatectomy: a machine learning-based multiomics study.

Purpose: This study aims to assess whole-mount Gleason grading (GG) in prostate cancer (PCa) accurately using a multiomics machine learning (ML) model and to compare its performance with biopsy-proven GG (bxGG) assessment. Materials and Methods: A total of 146 patients with PCa recruited in a pilot study of a prospective clinical trial (NCT02659527) were retrospectively included in the side study, all of whom underwent 68Ga-PSMA-11 integrated positron emission tomography (PET) / magnetic resonance (MR) before radical prostatectomy (RP) between May 2014 and April 2020. To establish a multiomics ML model, we quantified PET radiomics features, pathway-level genomics features from whole exome sequencing, and pathomics features derived from immunohistochemical staining of 11 biomarkers. Based on the multiomics dataset, five ML models were established and validated using 100-fold Monte Carlo cross-validation. Results: Among five ML models, the random forest (RF) model performed best in terms of the area under the curve (AUC). Compared to bxGG assessment alone, the RF model was superior in terms of AUC (0.87 vs 0.75), specificity (0.72 vs 0.61), positive predictive value (0.79 vs 0.75), and accuracy (0.78 vs 0.77) and showed slightly decreased sensitivity (0.83 vs 0.89) and negative predictive value (0.80 vs 0.81). Among the feature categories, bxGG was identified as the most important feature, followed by pathomics, clinical, radiomics and genomics features. The three important individual features were bxGG, PSA staining and one intensity-related radiomics feature. Conclusion: The findings demonstrate a superior assessment of the developed multiomics-based ML model in whole-mount GG compared to the current clinical baseline of bxGG. This enables personalized patient management by identifying high-risk PCa patients for RP.

A model combining BI-RADS® descriptors from pre-treatment B-mode breast ultrasound with clinicopathological tumor features shows promise in the prediction of residual disease after neoadjuvant chemotherapy.

PURPOSE: To create a simple model using standard BI-RADS® descriptors from pre-treatment B-mode ultrasound (US) combined with clinicopathological tumor features, and to assess the potential of the model to predict the presence of residual tumor after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients. METHOD: 245 female BC patients receiving NAC between January 2017 and December 2019 were included in this retrospective study. Two breast imaging fellows independently evaluated representative B-mode tumor images from baseline US. Additional clinicopathological tumor features were retrieved. The dataset was split into 170 training and 83 validation cases. Logistic regression was used in the training set to identify independent predictors of residual disease post NAC and to create a model, whose performance was evaluated by ROC curve analysis in the validation set. The reference standard was postoperative histology to determine the absence (pathological complete response, pCR) or presence (non-pCR) of residual invasive tumor in the breast or axillary lymph nodes. RESULTS: 100 patients (40.8%) achieved pCR. Logistic regression demonstrated that tumor size, microlobulated margin, spiculated margin, the presence of calcifications, the presence of edema, HER2-positive molecular subtype, and triple-negative molecular subtype were independent predictors of residual disease. A model using these parameters demonstrated an area under the ROC curve of 0.873 in the training and 0.720 in the validation set for the prediction of residual tumor post NAC. CONCLUSIONS: A simple model combining standard BI-RADS® descriptors from pre-treatment B-mode breast US with clinicopathological tumor features predicts the presence of residual disease after NAC.

Characterization of a Syngeneic Orthotopic Model of Cholangiocarcinoma by [18F]FDG-PET/MRI.

Cholangiocarcinoma (CCA) is a type of primary liver cancer originating from the biliary tract epithelium, characterized by limited treatment options for advanced cases and low survival rates. This study aimed to establish an orthotopic mouse model for CCA and monitor tumor growth using PET/MR imaging. Murine CCA cells were implanted into the liver lobe of male C57BL/6J mice. The imaging groups included contrast-enhanced (CE) MR, CE-MR with static [18F]FDG-PET, and dynamic [18F]FDG-PET. Tumor volume and FDG uptake were measured weekly over four weeks. Early tumor formation was visible in CE-MR images, with a gradual increase in volume over time. Dynamic FDG-PET revealed an increase in the metabolic glucose rate (MRGlu) over time. Blood analysis showed pathological changes in liver-related parameters. Lung metastases were observed in nearly all animals after four weeks. The study concludes that PET-MR imaging effectively monitors tumor progression in the CCA mouse model, providing insights into CCA development and potential treatment strategies.

Influence of Gadolinium-based Contrast Media and Inter-reader Variation on the Estimation of Intravoxel Incoherent Motion (IVIM) Parameters in Breast MR Imaging.

PURPOSE: Gadolinium-based contrast media (GBCM) may affect apparent diffusion coefficient measurements on diffusion-weighted imaging. We aimed at investigating the effect of GBCM and inter-reader variation on intravoxel incoherent motion (IVIM) parameters in breast lesions. METHODS: A total of 89 patients referred to 3T breast MRI with at least one histologically verified lesion were included. IVIM data were acquired using a single-shot echo planar imaging sequence before and after GBCM administration. D (true diffusion coefficient), D* (pseudo-diffusion coefficient) and f (perfusion fraction) were calculated and measured by two readers (R1, R2). Inter-reader and intra-reader agreements were assessed by intraclass correlation coefficients (ICCs) and Bland-Altman plots. RESULTS: D was comparable before and after GBCM administration and between readers. D* and f decreased after GBCM administration and showed a lower agreement between readers. Intra-reader agreement before and after GBCM administration was almost perfect for D for both R1 and R2 (ICC 0.955 and 0.887). The intra-reader agreement was substantial to moderate for D* (ICC R1 0.708, R2 0.583) and moderate for f (ICC R1 0.529 and R2 0.425). Inter-reader agreement before GBCM administration was almost perfect for D (ICC 0.905), substantial for D* (ICC 0.733), and moderate for f (ICC 0.404); after contrast media administration, it was almost perfect for D (ICC 0.876) and substantial for D* (ICC 0.654) and f (ICC 0.606). Bland-Altman plots revealed no significant bias. CONCLUSION: Administration of GBCM seems to have a stronger effect on D* and f values than on D values. This should be considered when applying IVIM in clinical practice.

Evaluation of Hepatic Glucose and Palmitic Acid Metabolism in Rodents on High-Fat Diet Using Deuterium Metabolic Imaging.

BACKGROUND: One of the main features of several metabolic disorders is dysregulation of hepatic glucose and lipid metabolism. Deuterium metabolic imaging (DMI) allows for assessing the uptake and breakdown of 2H-labeled substrates, giving specific insight into nutrient processing in healthy and diseased organs. Thus, DMI could be a useful approach for analyzing the differences in liver metabolism of healthy and diseased subjects to gain a deeper understanding of the alterations related to metabolic disorders. PURPOSE: Evaluating the feasibility of DMI as a tool for the assessment of metabolic differences in rodents with healthy and fatty livers (FLs). STUDY TYPE: Animal Model. POPULATION: 18 male Sprague Dawley rats on standard (SD, n = 9, healthy) and high-fat diet (HFD, n = 9, FL disease). FIELD STRENGTH/SEQUENCE: Phase-encoded 1D pulse-acquire sequence and anatomy co-registered phase-encoded 3D pulse-acquire chemical shift imaging for 2H at 9.4T. ASSESSMENT: Localized and nonlocalized liver spectroscopy was applied at eight time points over 104 minutes post injection. The obtained spectra were preprocessed and quantified using jMRUI (v7.0) and the resulting amplitudes translated to absolute concentration (mM) according to the 2H natural abundance water peak. STATISTICAL TESTS: Two-way repeated measures ANOVA were employed to assess between-group differences, with statistical significance at P < 0.05. RESULTS: DMI measurements demonstrated no significant difference (P = 0.98) in the uptake of [6,6'-2H2]glucose between healthy and impaired animals (AUCSD = 1966.0 ± 151.5 mM - minutes vs. AUCHFD = 2027.0 ± 167.6 mM·minutes). In the diseased group, the intrahepatic uptake of palmitic acid d-31 was higher (AUCHFD = 57.4 ± 17.0 mM·minutes, AUCSD = 33.3 ± 10.5 mM·minutes), but without statistical significance owing to substantial in-group variation (P = 0.73). DATA CONCLUSION: DMI revealed higher concentrations of palmitic acid in rats with FL disease and no difference in hepatic glucose concentration between healthy and impaired animals. Thus, DMI appears to be a useful tool for evaluating metabolism in rodents with FL disease. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Pilot study: A simple CAD-based tool to detect breast cancer on MRI of the breast.

PURPOSE: This pilot-study aims to assess, whether quantitatively assessed enhancing breast tissue as a percentage of the entire breast volume can serve as an indicator of breast cancer at breast MRI and whether the contrast-agent employed affects diagnostic efficacy. MATERIALS: This retrospective IRB-approved study, included 39 consecutive patients, that underwent two subsequent breast MRI exams for suspicious findings at conventional imaging with 0.1 mmol/kg gadobenic and gadoteric acid. Two independent readers, blinded to the histopathological outcome, assessed unenhanced and early post-contrast images using computer-assisted software (Brevis, Siemens Healthcare). Diagnostic performance was statistically determined for percentage of ipsilateral voxel volume enhancement and for percentage of contralateral enhancing voxel volume subtracted from ipsilateral enhancing voxel volume after crosstabulation with the dichotomized histological outcome (benign/malignant). RESULTS: Ipsilateral enhancing voxel volume versus histopathological outcome resulted in an AUC of 0.707 and 0.687 for gadobenic acid, reader 1 and 2, respectively and in an AUC of 0.778 and 0.773 for gadoteric acid, reader 1 and 2, respectively. Accounting for background parenchymal enhancement by subtracting contralateral enhancing volume from ipsilateral enhancing voxel volume versus histolopathological outcome resulted in an AUC of 0.793 and 0.843 for gadobenic acid, reader 1 and 2, respectively and in an AUC of 0.692 and 0.662 for gadoteric acid, reader 1 and 2, respectively. Pairwise testing yielded no statistically significant difference both between readers and between contrast agents employed (p > 0.05). CONCLUSION: Our proposed CAD algorithm, which quantitatively assesses enhancing breast tissue as a percentage of the entire breast volume, allows indicating the presence of breast cancer.

Superfluorinated, Highly Water-Soluble Polyphosphazenes as Potential 19F Magnetic Resonance Imaging (MRI) Contrast Agents.

"Hot spot" 19F magnetic resonance imaging (MRI) has garnered significant attention recently for its ability to image various disease markers quantitatively. Unlike conventional gadolinium-based MRI contrast agents, which rely on proton signal modulation, 19F-MRI's direct detection has a unique advantage in vivo, as the human body exhibits a negligible background 19F-signal. However, existing perfluorocarbon (PFC) or PFC-based contrast materials suffer from several limitations, including low longitudinal relaxation rates and relatively low imaging efficiency. Hence, we designed a macromolecular contrast agent featuring a high number of magnetically equivalent 19F-nuclei in a single macromolecule, adequate fluorine nucleus mobility, and excellent water solubility. This design utilizes superfluorinated polyphosphazene (PPz) polymers as the 19F-source; these are modified with sodium mercaptoethanesulfonate (MESNa) to achieve water solubility exceeding 360 mg/mL, which is a similar solubility to that of sodium chloride. We observed substantial signal enhancement in MRI with these novel macromolecular carriers compared to non-enhanced surroundings and aqueous trifluoroacetic acid (TFA) used as a positive control. In conclusion, these novel water-soluble macromolecular carriers represent a promising platform for future MRI contrast agents.

Non-Contrast-Enhanced Multiparametric MRI of the Hypoxic Tumor Microenvironment Allows Molecular Subtyping of Breast Cancer: A Pilot Study.

Tumor neoangiogenesis is an important hallmark of cancer progression, triggered by alternating selective pressures from the hypoxic tumor microenvironment. Non-invasive, non-contrast-enhanced multiparametric MRI combining blood-oxygen-level-dependent (BOLD) MRI, which depicts blood oxygen saturation, and intravoxel-incoherent-motion (IVIM) MRI, which captures intravascular and extravascular diffusion, can provide insights into tumor oxygenation and neovascularization simultaneously. Our objective was to identify imaging markers that can predict hypoxia-induced angiogenesis and to validate our findings using multiplexed immunohistochemical analyses. We present an in vivo study involving 36 female athymic nude mice inoculated with luminal A, Her2+, and triple-negative breast cancer cells. We used a high-field 9.4-tesla MRI system for imaging and subsequently analyzed the tumors using multiplex immunohistochemistry for CD-31, PDGFR-ß, and Hif1-α. We found that the hyperoxic-BOLD-MRI-derived parameter ΔR2* discriminated luminal A from Her2+ and triple-negative breast cancers, while the IVIM-derived parameter fIVIM discriminated luminal A and Her2+ from triple-negative breast cancers. A comprehensive analysis using principal-component analysis of both multiparametric MRI- and mpIHC-derived data highlighted the differences between triple-negative and luminal A breast cancers. We conclude that multiparametric MRI combining hyperoxic BOLD MRI and IVIM MRI, without the need for contrast agents, offers promising non-invasive markers for evaluating hypoxia-induced angiogenesis.

Preoperative breast MRI positively impacts surgical outcomes of needle biopsy-diagnosed pure DCIS: a patient-matched analysis from the MIPA study.

OBJECTIVES: To investigate the influence of preoperative breast MRI on mastectomy and reoperation rates in patients with pure ductal carcinoma in situ (DCIS). METHODS: The MIPA observational study database (7245 patients) was searched for patients aged 18-80 years with pure unilateral DCIS diagnosed at core needle or vacuum-assisted biopsy (CNB/VAB) and planned for primary surgery. Patients who underwent preoperative MRI (MRI group) were matched (1:1) to those who did not receive MRI (noMRI group) according to 8 confounding covariates that drive referral to MRI (age; hormonal status; familial risk; posterior-to-nipple diameter; BI-RADS category; lesion diameter; lesion presentation; surgical planning at conventional imaging). Surgical outcomes were compared between the matched groups with nonparametric statistics after calculating odds ratios (ORs). RESULTS: Of 1005 women with pure unilateral DCIS at CNB/VAB (507 MRI group, 498 noMRI group), 309 remained in each group after matching. First-line mastectomy rate in the MRI group was 20.1% (62/309 patients, OR 2.03) compared to 11.0% in the noMRI group (34/309 patients, p = 0.003). The reoperation rate was 10.0% in the MRI group (31/309, OR for reoperation 0.40) and 22.0% in the noMRI group (68/309, p < 0.001), with a 2.53 OR of avoiding reoperation in the MRI group. The overall mastectomy rate was 23.3% in the MRI group (72/309, OR 1.40) and 17.8% in the noMRI group (55/309, p = 0.111). CONCLUSIONS: Compared to those going directly to surgery, patients with pure DCIS at CNB/VAB who underwent preoperative MRI had a higher OR for first-line mastectomy but a substantially lower OR for reoperation. CLINICAL RELEVANCE STATEMENT: When confounding factors behind MRI referral are accounted for in the comparison of patients with CNB/VAB-diagnosed pure unilateral DCIS, preoperative MRI yields a reduction of reoperations that is more than twice as high as the increase in overall mastectomies. KEY POINTS: • Confounding factors cause imbalance when investigating the influence of preoperative MRI on surgical outcomes of pure DCIS. • When patient matching is applied to women with pure unilateral DCIS, reoperation rates are significantly reduced in women who underwent preoperative MRI. • The reduction of reoperations brought about by preoperative MRI is more than double the increase in overall mastectomies.

Simultaneous 18F-FDG PET/MRI Radiomics and Machine Learning Analysis of the Primary Breast Tumor for the Preoperative Prediction of Axillary Lymph Node Status in Breast Cancer.

In this prospective study, 117 female patients (mean age = 53 years) with 127 histologically proven breast cancer lesions (lymph node (LN) positive = 85, LN negative = 42) underwent simultaneous 18F-FDG PET/MRI of the breast. Quantitative parameters were calculated from dynamic contrast-enhanced (DCE) imaging (tumor Mean Transit Time, Volume Distribution, Plasma Flow), diffusion-weighted imaging (DWI) (tumor ADCmean), and PET (tumor SUVmax, mean and minimum, SUVmean of ipsilateral breast parenchyma). Manual whole-lesion segmentation was also performed on DCE, T2-weighted, DWI, and PET images, and radiomic features were extracted. The dataset was divided into a training (70%) and a test set (30%). Multi-step feature selection was performed, and a support vector machine classifier was trained and tested for predicting axillary LN status. 13 radiomic features from DCE, DWI, T2-weighted, and PET images were selected for model building. The classifier obtained an accuracy of 79.8 (AUC = 0.798) in the training set and 78.6% (AUC = 0.839), with sensitivity and specificity of 67.9% and 100%, respectively, in the test set. A machine learning-based radiomics model comprising 18F-FDG PET/MRI radiomic features extracted from the primary breast cancer lesions allows high accuracy in non-invasive identification of axillary LN metastasis.

[Use of contrast-enhanced mammography for diagnosis of breast cancer]. / Einsatz der kontrastmittelverstärkten Mammographie in der Brustkrebsdiagnostik.

BACKGROUND: Contrast-enhanced mammography (CEM) is an imaging method that is able to improve visualization of intramammary tumors after peripheral venous administration of an iodine-containing contrast medium (ICM). OBJECTIVES AND METHODS: The current significance of CEM is discussed. RESULTS: Studies were able to show an advantage of CEM in the diagnosis of breast cancer compared to mammography, especially for women with dense breasts. Indications for CEM currently depend on the availability of magnetic resonance imaging (MRI). If MRI is available, CEM is indicated in those cases when MRI cannot be performed. Use of CEM for breast cancer screening is currently viewed critically. This view can change when results and updated assessments of large CEM studies in Europe and USA become available. Patients must be informed about the use of an ICM. As ICM administration for CEM is carried out in a similar manner to established imaging methods, the authors expect the use of ICM for CEM to be unproblematic as long as general contraindications are adhered to. CONCLUSIONS: In the future, CEM could have greater importance for the diagnosis of breast cancer, as this imaging method has diagnostic advantages compared to conventional mammography. A great advantage of CEM is its availability. For those who use breast MRI, CEM is helpful when MRI is not feasible due to contraindications or other reasons.

Hyperoxic BOLD-MRI-Based Characterization of Breast Cancer Molecular Subtypes Is Independent of the Supplied Amount of Oxygen: A Preclinical Study.

Hyperoxic BOLD-MRI targeting tumor hypoxia may provide imaging biomarkers that represent breast cancer molecular subtypes without the use of injected contrast agents. However, the diagnostic performance of hyperoxic BOLD-MRI using different levels of oxygen remains unclear. We hypothesized that molecular subtype characterization with hyperoxic BOLD-MRI is feasible independently of the amount of oxygen. Twenty-three nude mice that were inoculated into the flank with luminal A (n = 9), Her2+ (n = 5), and triple-negative (n = 9) human breast cancer cells were imaged using a 9.4 T Bruker BioSpin system. During BOLD-MRI, anesthesia was supplemented with four different levels of oxygen (normoxic: 21%; hyperoxic: 41%, 71%, 100%). The change in the spin-spin relaxation rate in relation to the normoxic state, ΔR2*, dependent on the amount of erythrocyte-bound oxygen, was calculated using in-house MATLAB code. ΔR2* was significantly different between luminal A and Her2+ as well as between luminal A and triple-negative breast cancer, reflective of the less aggressive luminal A breast cancer's ability to better deliver oxygen-rich hemoglobin to its tissue. Differences in ΔR2* between subtypes were independent of the amount of oxygen, with robust distinction already achieved with 41% oxygen. In conclusion, hyperoxic BOLD-MRI may be used as a biomarker for luminal A breast cancer identification without the use of exogenous contrast agents.

Novel approach using [18F]FTHA-PET and de novo synthesized VLDL for assessment of FFA metabolism in a rat model of diet induced NAFLD.

BACKGROUND AND AIMS: The worldwide prevalence of Non-alcoholic Fatty Liver Disease (NAFLD) raises concerns about associated risk factors, such as obesity and type 2 Diabetes Mellitus, for leading causes of disability and death. Besides Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS), functional imaging with Positron Emission Tomography (PET) could contribute to a deeper understanding of the pathophysiology of NAFLD. Here we describe a novel approach using the PET tracer [18F]FTHA, which is an analog of long-chain free fatty acids (FFA) and is taken up by tissues to enter mitochondria or to be incorporated into complex lipids for further export as very-low-density lipoprotein (VLDL). METHODS: Male Sprague Dawley rats, after 6 weeks on a high-fat diet (HFD), were used as a model of diet induced NAFLD, while a standard diet (SD) served as a control group. Liver fat was estimated by MR spectroscopy at a 9.4 T system for phenotyping. To measure hepatic FFA uptake, rats underwent 60 min dynamic [18F]FTHA-PET scans after unrestricted access to food (HFD: n = 6; SD: n = 6) or overnight (≤16h) fasting (HFD: n = 6; SD: n = 5). FFA removal was assessed from incorporated 18F-residual in de novo synthesized VLDL out of plasma. RESULTS: MRS of the liver confirmed the presence of NAFLD (>5.6% fat). Under non-fasting conditions, hepatic [18F]FTHA uptake was significantly increased in NAFLD: SUVmean (p = 0.03) within [0; 60] min interval, SUVmean (p = 0.01) and SUVmax (p = 0.03) within [30; 60] min interval. SUVs for hepatic uptake under fasting conditions were not significantly different between the groups. Analysis of FFA removal demonstrated elevated values of 18F-residue in the VLDL plasma fraction of the healthy group compared to the NAFLD (p = 0.0569). CONCLUSION: Our novel approach for assessing FFA metabolism using [18F]FTHA demonstrated differences in the hepatic FFA uptake and FFA incorporation into VLDL between healthy and NAFLD rats. [18F]FTHA-PET could be used to study metabolic disturbances involved in the progression of NAFLD.

European Society of Breast Imaging (EUSOBI) guidelines on the management of axillary lymphadenopathy after COVID-19 vaccination: 2023 revision.

Axillary lymphadenopathy is a common side effect of COVID-19 vaccination, leading to increased imaging-detected asymptomatic and symptomatic unilateral axillary lymphadenopathy. This has threatened to negatively impact the workflow of breast imaging services, leading to the release of ten recommendations by the European Society of Breast Imaging (EUSOBI) in August 2021. Considering the rapidly changing scenario and data scarcity, these initial recommendations kept a highly conservative approach. As of 2023, according to newly acquired evidence, EUSOBI proposes the following updates, in order to reduce unnecessary examinations and avoid delaying necessary examinations. First, recommendation n. 3 has been revised to state that breast examinations should not be delayed or rescheduled because of COVID-19 vaccination, as evidence from the first pandemic waves highlights how delayed or missed screening tests have a negative effect on breast cancer morbidity and mortality, and that there is a near-zero risk of subsequent malignant findings in asymptomatic patients who have unilateral lymphadenopathy and no suspicious breast findings. Second, recommendation n. 7 has been revised to simplify follow-up strategies: in patients without breast cancer history and no imaging findings suspicious for cancer, symptomatic and asymptomatic imaging-detected unilateral lymphadenopathy on the same side of recent COVID-19 vaccination (within 12 weeks) should be classified as a benign finding (BI-RADS 2) and no further work-up should be pursued. All other recommendations issued by EUSOBI in 2021 remain valid.

Deep learning for predicting future lesion emergence in high-risk breast MRI screening: a feasibility study.

BACKGROUND: International societies have issued guidelines for high-risk breast cancer (BC) screening, recommending contrast-enhanced magnetic resonance imaging (CE-MRI) of the breast as a supplemental diagnostic tool. In our study, we tested the applicability of deep learning-based anomaly detection to identify anomalous changes in negative breast CE-MRI screens associated with future lesion emergence. METHODS: In this prospective study, we trained a generative adversarial network on dynamic CE-MRI of 33 high-risk women who participated in a screening program but did not develop BC. We defined an anomaly score as the deviation of an observed CE-MRI scan from the model of normal breast tissue variability. We evaluated the anomaly score's association with future lesion emergence on the level of local image patches (104,531 normal patches, 455 patches of future lesion location) and entire CE-MRI exams (21 normal, 20 with future lesion). Associations were analyzed by receiver operating characteristic (ROC) curves on the patch level and logistic regression on the examination level. RESULTS: The local anomaly score on image patches was a good predictor for future lesion emergence (area under the ROC curve 0.804). An exam-level summary score was significantly associated with the emergence of lesions at any location at a later time point (p = 0.045). CONCLUSIONS: Breast cancer lesions are associated with anomalous appearance changes in breast CE-MRI occurring before the lesion emerges in high-risk women. These early image signatures are detectable and may be a basis for adjusting individual BC risk and personalized screening. RELEVANCE STATEMENT: Anomalies in screening MRI preceding lesion emergence in women at high-risk of breast cancer may inform individualized screening and intervention strategies. KEY POINTS: • Breast lesions are associated with preceding anomalies in CE-MRI of high-risk women. • Deep learning-based anomaly detection can help to adjust risk assessment for future lesions. • An appearance anomaly score may be used for adjusting screening interval times.

Screening and diagnostic breast MRI: how do they impact surgical treatment? Insights from the MIPA study.

OBJECTIVES: To report mastectomy and reoperation rates in women who had breast MRI for screening (S-MRI subgroup) or diagnostic (D-MRI subgroup) purposes, using multivariable analysis for investigating the role of MRI referral/nonreferral and other covariates in driving surgical outcomes. METHODS: The MIPA observational study enrolled women aged 18-80 years with newly diagnosed breast cancer destined to have surgery as the primary treatment, in 27 centres worldwide. Mastectomy and reoperation rates were compared using non-parametric tests and multivariable analysis. RESULTS: A total of 5828 patients entered analysis, 2763 (47.4%) did not undergo MRI (noMRI subgroup) and 3065 underwent MRI (52.6%); of the latter, 2441/3065 (79.7%) underwent MRI with preoperative intent (P-MRI subgroup), 510/3065 (16.6%) D-MRI, and 114/3065 S-MRI (3.7%). The reoperation rate was 10.5% for S-MRI, 8.2% for D-MRI, and 8.5% for P-MRI, while it was 11.7% for noMRI (p ≤ 0.023 for comparisons with D-MRI and P-MRI). The overall mastectomy rate (first-line mastectomy plus conversions from conserving surgery to mastectomy) was 39.5% for S-MRI, 36.2% for P-MRI, 24.1% for D-MRI, and 18.0% for noMRI. At multivariable analysis, using noMRI as reference, the odds ratios for overall mastectomy were 2.4 (p < 0.001) for S-MRI, 1.0 (p = 0.957) for D-MRI, and 1.9 (p < 0.001) for P-MRI. CONCLUSIONS: Patients from the D-MRI subgroup had the lowest overall mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). This analysis offers an insight into how the initial indication for MRI affects the subsequent surgical treatment of breast cancer. KEY POINTS: • Of 3065 breast MRI examinations, 79.7% were performed with preoperative intent (P-MRI), 16.6% were diagnostic (D-MRI), and 3.7% were screening (S-MRI) examinations. • The D-MRI subgroup had the lowest mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). • The S-MRI subgroup had the highest mastectomy rate (39.5%) which aligns with higher-than-average risk in this subgroup, with a reoperation rate (10.5%) not significantly different to that of all other subgroups.

Prospective validation of 18F-Fluoroethylcholine as a tracer in PET/MRI for the evaluation of breast lesions and prediction of lymph node status.

PURPOSE: To assess 18F-Fluoroethylcholine (18F-FEC) as a PET/MRI tracer in the evaluation of breast lesions, breast cancer aggressiveness, and prediction of lymph node status. MATERIALS AND METHODS: This prospective, monocentric study was approved by the ethics committee and patients gave written, informed consent. This clinical trial was registered in the EudraCT database (Number 2017-003089-29). Women who presented with suspicious breast lesions were included. Histopathology was used as reference standard. Simultaneous 18F-FEC PET/MRI of the breast was performed in a prone position with a dedicated breast coil. MRI was performed using a standard protocol before and after contrast agent administration. A simultaneous read by nuclear medicine physicians and radiologists collected the imaging data of MRI-detected lesions, including the maximum standardized 18F-FEC-uptake value of breast lesions (SUVmaxT) and axillary lymph nodes (SUVmaxLN). Differences in SUVmax were evaluated with the Mann-Whitney U test. To calculate diagnostic performance, the area under the receiver operating characteristics curve (ROC) was used. RESULTS: There were 101 patients (mean age 52.3 years, standard deviation 12.0) with 117 breast lesions included (30 benign, 7 ductal carcinomas in situ, 80 invasive carcinomas). 18F-FEC was well tolerated by all patients. The ROC to distinguish benign from malignant breast lesions was 0.846. SUVmaxT was higher if lesions were malignant (p < 0.001), had a higher proliferation rate (p = 0.011), and were HER2-positive (p = 0.041). SUVmaxLN was higher in metastatic lymph nodes, with an ROC of 0.761 for SUVmaxT and of 0.793 for SUVmaxLN. CONCLUSION: Simultaneous 18F-FEC PET/MRI is safe and has the potential to be used for the evaluation of breast cancer aggressiveness, and prediction of lymph node status.

Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database.

OBJECTIVES: To develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria. METHODS: This was a multicentric, retrospective analysis of 11 independently conducted institutional review board-approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant. RESULTS: A total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10-3 mm2/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p < .001). The following ADC-B categories were identified: ADC-B0-ADC cannot be assessed; ADC-B1-no contrast-enhancing lesion; ADC-B2-ADC ≥ 1.9 (cumulative malignancy rate < 0.1%); ADC-B3-ADC 1.5 to < 1.9 (0.1-1.7%); ADC-B4-ADC 1.0 to < 1.5 (10-24.5%); and ADC-B5-ADC < 1.0 (> 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94-0.97) for invasive versus non-invasive breast carcinomas was reached. CONCLUSIONS: The breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI. CLINICAL RELEVANCE STATEMENT: The ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes. KEY POINTS: • The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI. • The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate. • The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making.