Chest computed tomography of suspected COVID-19 pneumonia in the Emergency Department: comparative analysis between patients with different vaccination status.

Purpose: To identify differences in chest computed tomography (CT) of the symptomatic coronavirus disease 2019 (COVID-19) population according to the patients' severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination status (non-vaccinated, vaccinated with incomplete or complete vaccination cycle). Material and methods: CT examinations performed in the Emergency Department (ED) in May-November 2021 for suspected COVID-19 pneumonia with a positive SARS-CoV-2 test were retrospectively included. Personal data were compared for vaccination status. One 13-year experienced radiologist and two 4th-year radiology residents independently evaluated chest CT scans according to CO-RADS and ACR COVID classifications. In possible COVID-19 pneumonia cases, defined as CO-RADS 3 to 5 (ACR indeterminate and typical) by each reader, high involvement CT score (≥ 25%) and CT patterns (presence of ground glass opacities, consolidations, crazy paving areas) were compared for vaccination status. Results: 184 patients with known vaccination status were included in the analysis: 111 non-vaccinated (60%) for SARS-CoV-2 infection, 21 (11%) with an incomplete vaccination cycle, and 52 (28%) with a complete vaccination cycle (6 different vaccine types). Multivariate logistic regression showed that the only factor predicting the absence of pneumonia (CO-RADS 1 and ACR negative cases) for the 3 readers was a complete vaccination cycle (OR = 12.8-13.1compared to non-vaccinated patients, p ≤ 0.032). Neither CT score nor CT patterns of possible COVID-19 pneumonia showed any statistically significant correlation with vaccination status for the 3 readers. Conclusions: Symptomatic SARS-CoV-2-infected patients with a complete vaccination cycle had much higher odds of showing a negative CT chest examination in ED compared to non-vaccinated patients. Neither CT involvement nor CT patterns of interstitial pneumonia showed differences across different vaccination status.

Biennial screening mammography: How many women ask for more? Estimate of the interval mammogram rate in an organised population-based screening programme.

OBJECTIVES: To estimate the interval mammogram rate, i.e. the undertaking of an additional mammography between scheduled screening rounds, and identify factors influencing this phenomenon. METHODS: Data from our screening programme for the year 2014, excluding prevalent rounds, were analysed. Information about the number of women who underwent  interval mammograms was obtained reviewing the questionnaires and searching the department database. Data on age, breast density, family history of breast cancer, number of screening rounds, previous recalls, general practitioner, and city of residence (used as a proxy of local socio-economic differences) were evaluated using chi-square test. RESULTS: Of 2780 screened women (incident rounds), 2566 had complete data (92%). The interval mammogram rate was 384/2566 (15%, 95% confidence interval 14-17%). Women classified with American College of Radiology c or d breast density categories showed a higher interval mammography probability than those with a and b density (p < 0.001); women in their second round showed a higher probability of interval mammogram compared to women in their fifth, sixth, or seventh round (p ≤ 0.004). No significant differences were found between women with and without an interval mammogram when considering previous recalls for a negative work-up (p = 0.241), positive breast cancer family history (p = 0.538), and city of residence (p = 0.177). CONCLUSIONS: The interval mammogram rate was relatively low (15%). Higher breast density and first of years of adherence to the programme were associated with higher interval mammogram rate.

Upgrade Rate of Percutaneously Diagnosed Pure Atypical Ductal Hyperplasia: Systematic Review and Meta-Analysis of 6458 Lesions.

Background Management of percutaneously diagnosed pure atypical ductal hyperplasia (ADH) is an unresolved clinical issue. Purpose To calculate the pooled upgrade rate of percutaneously diagnosed pure ADH. Materials and Methods A search of MEDLINE and EMBASE databases was performed in October 2018. Preferred Reporting Items for Systematic Reviews and Meta-Analyses, or PRISMA, guidelines were followed. A fixed- or random-effects model was used, along with subgroup and meta-regression analyses. The Newcastle-Ottawa scale was used for study quality, and the Egger test was used for publication bias. Results Of 521 articles, 93 were analyzed, providing data for 6458 ADHs (5911 were managed with surgical excision and 547 with follow-up). Twenty-four studies used core-needle biopsy; 44, vacuum-assisted biopsy; 21, both core-needle and vacuum-assisted biopsy; and four, unspecified techniques. Biopsy was performed with stereotactic guidance in 29 studies; with US guidance in nine, with MRI guidance in nine, and with mixed guidance in eight. Overall heterogeneity was high (I2 = 80%). Subgroup analysis according to management yielded a pooled upgrade rate of 29% (95% confidence interval [CI]: 26%, 32%) for surgically excised lesions and 5% (95% CI: 4%, 8%) for lesions managed with follow-up (P < .001). Heterogeneity was entirely associated with surgically excised lesions (I2 = 78%) rather than those managed with follow-up (I2 = 0%). Most variability was explained by guidance and needle caliper (P = .15). At subgroup analysis of surgically excised lesions, the pooled upgrade rate was 42% (95% CI: 31%, 53%) for US guidance, 23% (95% CI: 19%, 27%) for stereotactic biopsy, and 32% (95% CI: 22%, 43%) for MRI guidance, with heterogeneity (52%, 63%, and 56%, respectively) still showing the effect of needle caliper. When the authors considered patients with apparent complete lesion removal after biopsy (subgroups in 14 studies), the pooled upgrade rate was 14% (95% CI: 8%, 23%). Study quality was low to medium; the risk of publication bias was low (P = .10). Conclusion Because of a pooled upgrade rate higher than 2% (independent of biopsy technique, needle size, imaging guidance, and apparent complete lesion removal), atypical ductal hyperplasia diagnosed with percutaneous needle biopsy should be managed with surgical excision. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Brem in this issue.

Correlation between voxel-wise enhancement parameters on DCE-MRI and pathological prognostic factors in invasive breast cancers.

PURPOSE: To investigate the correlation between enhancement parameters on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and pathologic prognostic factors in invasive breast cancers (BCs). MATERIALS AND METHODS: A total of 25 invasive BCs were included: 22 invasive ductal, 2 invasive lobular and 1 invasive mucinous. The tumor volume was segmented using a semi-automatic software (Olea Sphere). The following voxel-wise enhancement parameters were extracted: (1) time to peak enhancement; (2) signal intensity at peak (SIP); (3) peak enhancement percentage (PEP); (4) post-initial enhancement percentage (PIEP). The following pathological prognostic factors were considered for potential correlation: tumor (pT) and nodal (pN) stage, grading, perivascular/perineural invasion, estrogen/progesterone receptor status, Ki-67 proliferation, and HER2 expression. Spearman and Pearson correlation coefficients were calculated according with type of variable and data distribution. RESULTS: Tumor volume was 2.8 ± 2.0 cm3 (mean ± standard deviation [SD]). Mean SIP correlated with pT (ρ = 0.424, p = 0.035); mean PEP correlated with HER2 overexpression (ϕ = 0.471, p = 0.017) and pT (ρ = 0.449, p = 0.024). The percentage of voxels with fast PEP directly correlated with pT (ρ = 0.482, p = 0.015) and pN (ρ = 0.446, p = 0.026), while the percentage of voxels with slow PEP inversely correlated with pT (ρ = -0.421, p = 0.039) and pN (ρ = -0.481, p = 0.015). Segmentation time was 14.6 ± 1.3 min (mean ± SD). CONCLUSION: In invasive BCs, DCE-MRI voxel-wise enhancement parameters correlated with HER2, pT, and pN.

Breast arterial calcifications on mammography: intra- and inter-observer reproducibility of a semi-automatic quantification tool.

PURPOSE: A strong association between breast arterial calcifications (BAC) and cardiovascular disease has been demonstrated. However, BAC quantification tools are lacking. We evaluated the intra- and inter-observer reproducibility of a semi-automatic tool for BAC quantification on digital mammograms. MATERIALS AND METHODS: A multivendor image dataset of 212 mammographic views, 106 cranio-caudal (CC) and 106 medio-lateral oblique (MLO), were retrospectively selected from 53 subjects if BAC were seen in at least one view. Images were segmented twice by two intensively trained residents in Radiodiagnostics with > 6-month experience in mammography using a semi-automatic software. The two observers (O1, O2) independently positioned rectangular ROIs where they recognized BAC on both CC and MLO views, separately. The adaptive thresholding algorithm automatically provided the BAC amount in mm2. Number, size, and position of the ROIs were observer-dependent. Total BAC amount was calculated for each patient. Bland-Altman analysis was used. RESULTS: Total BAC amount was 56.6 (IQR 18.1-91.1) and 41.0 (IQR 18.8-90.9) for O1 and O2, respectively. Intra-observer Bland-Altman analysis showed a bias of 11.9 mm2, a coefficient of repeatability of 32.7 mm2, an average measurement of 72.8 mm2, for a 55% reproducibility; the same data were - 7.0, 61.4, 63.4 mm2, and only 3%, respectively, for the inter-observer analysis. CONCLUSION: Our semi-automatic tool for BAC quantification showed a poor reproducibility. These results pointed out that the human identification of BAC represents the main source of variability. Further research is needed to translate BAC quantification into clinical practice.

Diagnostic Performance of MRI Versus Galactography in Women With Pathologic Nipple Discharge: A Systematic Review and Meta-Analysis.

OBJECTIVE: The objective of our study was to perform a systematic review of the literature of the diagnostic accuracy of MRI compared with galactography in women with pathologic nipple discharge. MATERIALS AND METHODS: A systematic literature search was performed (MEDLINE, Embase, Web of Science) for articles evaluating the diagnostic performance of MRI and galactography in patients with pathologic nipple discharge and with histologic verification or clinical follow-up. Distinction between any abnormality and cancer was made. Two independent readers selected eligible articles published until December 2015. The quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Data analyses were performed using the bivariate model. RESULTS: Ten articles were analyzed for a total of 921 patients. The study quality was high, with a low risk of bias and low concerns regarding applicability. The pooled sensitivity for any abnormality was significantly higher for MRI, with 92% (95% CI, 85-96%), than for galactography, with 69% (95% CI, 59-78%) (p < 0.001). The pooled specificity was 76% (95% CI, 49-92%) for MRI versus 39% (95% CI, 16-69%) for galactography (p < 0.001). The pooled sensitivity and specificity for cancer detection were calculated for MRI only and were 92% (95% CI, 74-98%) and 97% (95% CI, 80-100%), respectively. CONCLUSION: This meta-analysis shows a higher diagnostic performance of MRI compared with that of galactography in the detection of any kind of lesion in patients with pathologic nipple discharge. Moreover, high sensitivity and very high specificity for cancer by MRI could be confirmed in this clinical setting. If mammography and ultrasound are negative, MRI should be preferred over galactography for further evaluation.

MR Imaging for Selection of Patients for Partial Breast Irradiation: A Systematic Review and Meta-Analysis.

PURPOSE: To systematically review articles that estimated the ineligibility for partial breast irradiation (PBI) after magnetic resonance (MR) imaging. MATERIALS AND METHODS: No ethics committee approval was needed. A systematic search was performed by using MEDLINE and EMBASE. The rate of patients eligible at standard assessment (ie, clinical examination, mammography, and/or ultrasonography) but ineligible after MR imaging was a study outcome. Odds ratios (ORs) were calculated to identify predictors. Quality was appraised by using the Strengthening Reporting of Observational Studies in Epidemiology checklist. RESULTS: Of 93 retrieved articles, six were included (total, 3136 patients). For PBI eligibility, all studies applied National Surgical Adjuvant Breast and Bowel Project B-39 criteria. Ineligibility at standard assessment varied from 21% to 80%; MR imaging prompted ineligibility for PBI in 6%-25% of patients who were initially deemed eligible or in 2%-20% if calculated on the overall number of patients initially screened. Meta-regression showed a negative correlation between ineligibility at standard assessment and ineligibility after MR imaging (P < .001). The pooled percentage of patients eligible at standard assessment but ineligible after MR imaging was 11% (95% confidence interval [CI]: 6%, 19%). Predictors for ineligibility after MR imaging were cancers stage pT2 or greater versus less than stage pT2 (OR, 8.8 [95% CI: 4.7, 16.7]; P < .001), invasive lobular histopathologic results versus invasive ductal pathologic results (OR, 3.0 [95% CI: 1.6, 6.6]; P = .007), pre- versus postmenopausal status (OR, 1.9 [95% CI: 1.3, 2.6]; P < .001), invasive cancer versus ductal carcinoma in situ (OR, 1.6 [95% CI: 1.0, 2.4]; P = .031). Study quality ranged from 17 to 20 (maximum quality, 22). The risk of publication bias was moderate. CONCLUSION: One of nine women (11%), who on the sole basis of standard assessment were candidates to undergo PBI, was found to be ineligible after undergoing MR imaging. Breast MR imaging should be used to select patients for PBI.

Breast Cancer: Computer-aided Detection with Digital Breast Tomosynthesis.

PURPOSE: To evaluate a commercial tomosynthesis computer-aided detection (CAD) system in an independent, multicenter dataset. MATERIALS AND METHODS: Diagnostic and screening tomosynthesis mammographic examinations (n = 175; cranial caudal and mediolateral oblique) were randomly selected from a previous institutional review board-approved trial. All subjects gave informed consent. Examinations were performed in three centers and included 123 patients, with 132 biopsy-proven screening-detected cancers, and 52 examinations with negative results at 1-year follow-up. One hundred eleven lesions were masses and/or microcalcifications (72 masses, 22 microcalcifications, 17 masses with microcalcifications) and 21 were architectural distortions. Lesions were annotated by radiologists who were aware of all available reports. CAD performance was assessed as per-lesion sensitivity and false-positive results per volume in patients with negative results. RESULTS: Use of the CAD system showed per-lesion sensitivity of 89% (99 of 111; 95% confidence interval: 81%, 94%), with 2.7 ± 1.8 false-positive rate per view, 62 of 72 lesions detected were masses, 20 of 22 were microcalcification clusters, and 17 of 17 were masses with microcalcifications. Overall, 37 of 39 microcalcification clusters (95% sensitivity, 95% confidence interval: 81%, 99%) and 79 of 89 masses (89% sensitivity, 95% confidence interval: 80%, 94%) were detected with the CAD system. On average, 0.5 false-positive rate per view were microcalcification clusters, 2.1 were masses, and 0.1 were masses and microcalcifications. CONCLUSION: A digital breast tomosynthesis CAD system can allow detection of a large percentage (89%, 99 of 111) of breast cancers manifesting as masses and microcalcification clusters, with an acceptable false-positive rate (2.7 per breast view). Further studies with larger datasets acquired with equipment from multiple vendors are needed to replicate the findings and to study the interaction of radiologists and CAD systems.

Focal Liver Lesions in Budd-Chiari Syndrome: Spectrum of Imaging Findings.

Budd-Chiari syndrome (BCS) is a rare clinical entity characterized by hepatic venous outflow obstruction, resulting in liver congestion and subsequent chronic parenchymal damage. This condition often leads to the development of focal liver lesions, including benign focal nodular hyperplasia-like regenerative nodules, hepatocellular carcinoma, and perfusion-related pseudo-lesions. Computed tomography, ultrasound, and magnetic resonance are the commonly employed imaging modalities for the follow-up of BCS patients and for the detection and characterization of new-onset lesions. The accurate differentiation between benign and malignant nodules is crucial for optimal patient management and treatment planning. However, it can be challenging due to the variable and overlapping characteristics observed. This review aims to provide a comprehensive overview of the imaging features and differential diagnosis of focal liver lesions in BCS, emphasizing the key findings and discussing the challenges associated with their interpretation, with the purpose of facilitating the subsequent clinical decision-making.

Impact of COVID-19 Pandemic on the Workload of Diagnostic Radiology: A 2-Year Observational Study in a Tertiary Referral Hospital.

RATIONALE AND OBJECTIVES: To evaluate the impact of COVID-19 pandemic on diagnostic imaging workload in a tertiary referral hospital. MATERIALS AND METHODS: Radiological examinations performed in pre-pandemic period (2015-2019) and in pandemic period (2020-2021) were retrospectively included. Based on epidemiological data and restriction measures, four pandemic waves were identified. For each of them, the relative change (RC) in workload was calculated and compared to the 5-year averaged workload in the corresponding pre-COVID-19 periods. Workload variations were also assessed according to technique (radiographs, CT, MRI, ultrasounds), body district (chest, abdomen, breast, musculoskeletal, head/neck, brain/spine, cardiovascular) and care setting (inpatient, outpatient, emergency imaging, pre-admission imaging). RESULTS: A total of 1384380 examinations were included. In 2020 imaging workload decreased (RC = -11%) compared to the average of the previous 5 years, while in 2021 only a minimal variation (RC = +1%) was observed. During first wave, workload was reduced for all modalities, body regions and types of care setting (RC from -86% to -10%), except for CT (RC = +3%). In subsequent waves, workload increased only for CT (mean RC = +18%) and, regarding body districts, for breast (mean RC = +23%) and cardiovascular imaging (mean RC = +23%). For all other categories, a workload comparable to pre-pandemic period was almost only restored in the fourth wave. In all pandemics periods workload decrease was mainly due to reduced outpatient activity (p < 0.001), while inpatient and emergency imaging was increased (p < 0.001). CONCLUSION: Evaluating imaging workload changes throughout COVID-19 pandemic helps to understand the response dynamics of radiological services and to improve institutional preparedness to face extreme contingency.

Washout of mass-like benign breast lesions at dynamic magnetic resonance imaging.

OBJECTIVE: This study aimed to estimate the frequency and timing of washout in a series of pathologically proven benign mass-like breast lesions at dynamic magnetic resonance imaging. METHODS: Institutional review board approval was obtained for this retrospective study. We evaluated enhancement kinetics of 33 pathologically confirmed benign breast lesions: fibroadenomas (n = 22), adenosis (n = 6), typical ductal hyperplasia (n = 2), fibroadenoma with ductal hyperplasia (n = 1), fibrosclerosis (n = 1), and inflammatory lesion (n = 1). Coronal 3-dimensional T1-weighted gradient-echo sequences were acquired before/after intravenous injection of 0.1 mmol/ kg gadoterate meglumine (time resolution, 111 seconds), 1 before and 5 after contrast injection. The time point at which the kinetic curve demonstrated a washout was recorded. Cumulative distribution of lesions showing washout was built. Paired comparisons of specificity for washout kinetics were performed using the McNemar test. RESULTS: Of 33 lesions, washout was never observed in 20 (61%), whereas 13 (39%) showed washout during the study. Of these 13 lesions, only 1 (inflammatory mass) exhibited washout within the first 3 minutes (specificity, 97%), 9 within 6 minutes (specificity, 73%), and 13 within 8 minutes (specificity, 61%). Specificity of washout kinetics within 3 minutes (97%) was significantly larger than that from the sixth minute (73%) and thereafter (P < 0.016). CONCLUSIONS: A prolonged observation for dynamic breast magnetic resonance imaging may result in false-positive washout, especially after 6 minutes. Late washout should not be considered a reliable marker of malignancy.

A Machine Learning Ensemble Based on Radiomics to Predict BI-RADS Category and Reduce the Biopsy Rate of Ultrasound-Detected Suspicious Breast Masses.

We developed a machine learning model based on radiomics to predict the BI-RADS category of ultrasound-detected suspicious breast lesions and support medical decision-making towards short-interval follow-up versus tissue sampling. From a retrospective 2015-2019 series of ultrasound-guided core needle biopsies performed by four board-certified breast radiologists using six ultrasound systems from three vendors, we collected 821 images of 834 suspicious breast masses from 819 patients, 404 malignant and 430 benign according to histopathology. A balanced image set of biopsy-proven benign (n = 299) and malignant (n = 299) lesions was used for training and cross-validation of ensembles of machine learning algorithms supervised during learning by histopathological diagnosis as a reference standard. Based on a majority vote (over 80% of the votes to have a valid prediction of benign lesion), an ensemble of support vector machines showed an ability to reduce the biopsy rate of benign lesions by 15% to 18%, always keeping a sensitivity over 94%, when externally tested on 236 images from two image sets: (1) 123 lesions (51 malignant and 72 benign) obtained from two ultrasound systems used for training and from a different one, resulting in a positive predictive value (PPV) of 45.9% (95% confidence interval 36.3-55.7%) versus a radiologists' PPV of 41.5% (p < 0.005), combined with a 98.0% sensitivity (89.6-99.9%); (2) 113 lesions (54 malignant and 59 benign) obtained from two ultrasound systems from vendors different from those used for training, resulting into a 50.5% PPV (40.4-60.6%) versus a radiologists' PPV of 47.8% (p < 0.005), combined with a 94.4% sensitivity (84.6-98.8%). Errors in BI-RADS 3 category (i.e., assigned by the model as BI-RADS 4) were 0.8% and 2.7% in the Testing set I and II, respectively. The board-certified breast radiologist accepted the BI-RADS classes assigned by the model in 114 masses (92.7%) and modified the BI-RADS classes of 9 breast masses (7.3%). In six of nine cases, the model performed better than the radiologist did, since it assigned a BI-RADS 3 classification to histopathology-confirmed benign masses that were classified as BI-RADS 4 by the radiologist.

Diagnostic Performance in Differentiating COVID-19 from Other Viral Pneumonias on CT Imaging: Multi-Reader Analysis Compared with an Artificial Intelligence-Based Model.

Growing evidence suggests that artificial intelligence tools could help radiologists in differentiating COVID-19 pneumonia from other types of viral (non-COVID-19) pneumonia. To test this hypothesis, an R-AI classifier capable of discriminating between COVID-19 and non-COVID-19 pneumonia was developed using CT chest scans of 1031 patients with positive swab for SARS-CoV-2 (n = 647) and other respiratory viruses (n = 384). The model was trained with 811 CT scans, while 220 CT scans (n = 151 COVID-19; n = 69 non-COVID-19) were used for independent validation. Four readers were enrolled to blindly evaluate the validation dataset using the CO-RADS score. A pandemic-like high suspicion scenario (CO-RADS 3 considered as COVID-19) and a low suspicion scenario (CO-RADS 3 considered as non-COVID-19) were simulated. Inter-reader agreement and performance metrics were calculated for human readers and R-AI classifier. The readers showed good agreement in assigning CO-RADS score (Gwet's AC2 = 0.71, p < 0.001). Considering human performance, accuracy = 78% and accuracy = 74% were obtained in the high and low suspicion scenarios, respectively, while the AI classifier achieved accuracy = 79% in distinguishing COVID-19 from non-COVID-19 pneumonia on the independent validation dataset. The R-AI classifier performance was equivalent or superior to human readers in all comparisons. Therefore, a R-AI classifier may support human readers in the difficult task of distinguishing COVID-19 from other types of viral pneumonia on CT imaging.

Accuracy and inter-reader agreement of breast MRI for cancer staging using 0.08 mmol/kg of gadobutrol.

BACKGROUND: Evidence on gadolinium brain accumulation after contrast-enhanced MRI prompted research in dose reduction. PURPOSE: To estimate accuracy and inter-reader reproducibility of tumor size measurement in breast MRI using 0.08 mmol/kg of gadobutrol. METHODS: We retrospectively analyzed all women who underwent 1.5-T breast MRI for cancer staging at our department with 0.08 mmol/kg of gadobutrol. Two readers (R1 and R2, 12 and 3 years-experience) measured the largest lesion diameter. Accuracy was estimated both as correlation with pathology and rate of absolute (>5 mm) overestimation and underestimation, inter-reader reproducibility using the Bland-Altman method. Data are given as median and interquartile range. RESULTS: Thirty-six patients were analyzed (median age 56 years, 49-66) for a total of 38 lesions, 24 (63%) mass enhancement, 14 (37%) non-mass enhancement. Histopathological median size (mm) of all lesions was 15 (9-25): 13 (9-19) for mass lesions, 19 (11-39) for non-mass lesions. On MRI, R1 measured (mm) 14 (10-22) for all lesions, 13 (10-19) for mass lesions, 19 (11-49) for non-mass lesions. MRI-pathology correlation was very high for all lesion categories (ρ ≥ 0.766). On MRI, R1 overestimated lesion size in 6 cases (16%), and underestimated in 3 (8%); R2, overestimated 7 cases (18%) and underestimated 3 cases (8%). At inter-reader reproducibility analysis (mm): bias 0.9, coefficient of reproducibility 13 for all lesions; -0.1 and 6 for mass lesions; 2.5 and 20 for non-mass lesions. CONCLUSIONS: Breast MRI may be performed using 0.08 mmol/kg of gadobutrol with high accuracy and acceptable inter-reader agreement.

MRI versus Mammography plus Ultrasound in Women at Intermediate Breast Cancer Risk: Study Design and Protocol of the MRIB Multicenter, Randomized, Controlled Trial.

In women at high/intermediate lifetime risk of breast cancer (BC-LTR), contrast-enhanced magnetic resonance imaging (MRI) added to mammography ± ultrasound (MX ± US) increases sensitivity but decreases specificity. Screening with MRI alone is an alternative and potentially more cost-effective strategy. Here, we describe the study protocol and the characteristics of enrolled patients for MRIB feasibility, multicenter, randomized, controlled trial, which aims to compare MRI alone versus MX+US in women at intermediate breast cancer risk (aged 40-59, with a 15-30% BC-LTR and/or extremely dense breasts). Two screening rounds per woman were planned in ten centers experienced in MRI screening, the primary endpoint being the rate of cancers detected in the 2 arms after 5 years of follow-up. From July 2013 to November 2015, 1254 women (mean age 47 years) were enrolled: 624 were assigned to MX+US and 630 to MRI. Most of them were aged below 50 (72%) and premenopausal (45%), and 52% used oral contraceptives. Among postmenopausal women, 15% had used hormone replacement therapy. Breast and/or ovarian cancer in mothers and/or sisters were reported by 37% of enrolled women, 79% had extremely dense breasts, and 41% had a 15-30% BC-LTR. The distribution of the major determinants of breast cancer risk profiles (breast density and family history of breast and ovarian cancer) of enrolled women varied across centers.

Chest x-ray severity score in COVID-19 patients on emergency department admission: a two-centre study.

BACKGROUND: Integration of imaging and clinical parameters could improve the stratification of COVID-19 patients on emergency department (ED) admission. We aimed to assess the extent of COVID-19 pulmonary abnormalities on chest x-ray (CXR) using a semiquantitative severity score, correlating it with clinical data and testing its interobserver agreement. METHODS: From February 22 to April 8, 2020, 926 consecutive patients referring to ED of two institutions in Northern Italy for suspected SARS-CoV-2 infection were reviewed. Patients with reverse transcriptase-polymerase chain reaction positive for SARS-CoV-2 and CXR images on ED admission were included (295 patients, median age 69 years, 199 males). Five readers independently and blindly reviewed all CXRs, rating pulmonary parenchymal involvement using a 0-3 semiquantitative score in 1-point increments on 6 lung zones (range 0-18). Interobserver agreement was assessed with weighted Cohen's κ, correlations between median CXR score and clinical data with Spearman's ρ, and the Mann-Whitney U test. RESULTS: Median score showed negative correlation with SpO2 (ρ = -0.242, p < 0.001), positive correlation with white cell count (ρ = 0.277, p < 0.001), lactate dehydrogenase (ρ = 0.308, p < 0.001), and C-reactive protein (ρ = 0.367, p < 0.001), being significantly higher in subsequently dead patients (p = 0.003). Considering overall scores, readers' pairings yielded moderate (κ = 0.449, p < 0.001) to almost perfect interobserver agreement (κ = 0.872, p < 0.001), with better interobserver agreement between readers of centre 2 (up to κ = 0.872, p < 0.001) than centre 1 (κ = 0.764, p < 0.001). CONCLUSIONS: Proposed CXR pulmonary severity score in COVID-19 showed moderate to almost perfect interobserver agreement and significant but weak correlations with clinical parameters, potentially furthering CXR integration in patients' stratification.

Chest x-ray in the COVID-19 pandemic: Radiologists' real-world reader performance.

PURPOSE: To report real-world diagnostic performance of chest x-ray (CXR) readings during the COVID-19 pandemic. METHODS: In this retrospective observational study we enrolled all patients presenting to the emergency department of a Milan-based university hospital from February 24th to April 8th 2020 who underwent nasopharyngeal swab for reverse transcriptase-polymerase chain reaction (RT-PCR) and anteroposterior bedside CXR within 12 h. A composite reference standard combining RT-PCR results with phone-call-based anamnesis was obtained. Radiologists were grouped by CXR reading experience (Group-1, >10 years; Group-2, <10 years), diagnostic performance indexes were calculated for each radiologist and for the two groups. RESULTS: Group-1 read 435 CXRs (77.0 % disease prevalence): sensitivity was 89.0 %, specificity 66.0 %, accuracy 83.7 %. Group-2 read 100 CXRs (73.0 % prevalence): sensitivity was 89.0 %, specificity 40.7 %, accuracy 76.0 %. During the first half of the outbreak (195 CXRs, 66.7 % disease prevalence), overall sensitivity was 80.8 %, specificity 67.7 %, accuracy 76.4 %, Group-1 sensitivity being similar to Group-2 (80.6 % versus 81.5 %, respectively) but higher specificity (74.0 % versus 46.7 %) and accuracy (78.4 % versus 69.0 %). During the second half (340 CXRs, 81.8 % prevalence), overall sensitivity increased to 92.8 %, specificity dropped to 53.2 %, accuracy increased to 85.6 %, this pattern mirrored in both groups, with decreased specificity (Group-1, 58.0 %; Group-2, 33.3 %) but increased sensitivity (92.7 % and 93.5 %) and accuracy (86.5 % and 81.0 %, respectively). CONCLUSIONS: Real-world CXR diagnostic performance during the COVID-19 pandemic showed overall high sensitivity with higher specificity for more experienced radiologists. The increase in accuracy over time strengthens CXR role as a first line examination in suspected COVID-19 patients.

Technique, protocols and adverse reactions for contrast-enhanced spectral mammography (CESM): a systematic review.

We reviewed technical parameters, acquisition protocols and adverse reactions (ARs) for contrast-enhanced spectral mammography (CESM). A systematic search in databases, including MEDLINE/EMBASE, was performed to extract publication year, country of origin, study design; patients; mammography unit/vendor, radiation dose, low-/high-energy tube voltage; contrast molecule, concentration and dose; injection modality, ARs and acquisition delay; order of views; examination time. Of 120 retrieved articles, 84 were included from 22 countries (September 2003-January 2019), totalling 14012 patients. Design was prospective in 44/84 studies (52%); in 70/84 articles (83%), a General Electric unit with factory-set kVp was used. Per-view average glandular dose, reported in 12/84 studies (14%), ranged 0.43-2.65 mGy. Contrast type/concentration was reported in 79/84 studies (94%), with Iohexol 350 mgI/mL mostly used (25/79, 32%), dose and flow rate in 72/84 (86%), with 1.5 mL/kg dose at 3 mL/s in 62/72 studies (86%). Injection was described in 69/84 articles (82%), automated in 59/69 (85%), manual in 10/69 (15%) and flush in 35/84 (42%), with 10-30 mL dose in 19/35 (54%). An examination time < 10 min was reported in 65/84 studies (77%), 120 s acquisition delay in 65/84 (77%) and order of views in 42/84 (50%) studies, beginning with the craniocaudal view of the non-suspected breast in 7/42 (17%). Thirty ARs were reported by 14/84 (17%) studies (26 mild, 3 moderate, 1 severe non-fatal) with a pooled rate of 0.82% (fixed-effect model). Only half of CESM studies were prospective; factory-set kVp, contrast 1.5 mL/kg at 3 mL/s and 120 s acquisition delay were mostly used; only 1 severe AR was reported. CESM protocol standardisation is advisable.

Clinical Breast MR Using MRS or DWI: Who Is the Winner?

Magnetic resonance imaging (MRI) of the breast gained a role in clinical practice thanks to the optimal sensitivity of contrast-enhanced (CE) protocols. This approach, first proposed 30 years ago and further developed as bilateral highly spatially resolved dynamic study, is currently considered superior for cancer detection to any other technique. However, other directions than CE imaging have been explored. Apart from morphologic features on unenhanced T2-weighted images, two different non-contrast molecular approaches were mainly run in vivo: proton MR spectroscopy (1H-MRS) and diffusion-weighted imaging (DWI). Both approaches have shown aspects of breast cancer (BC) hidden to CE-MRI: 1H-MRS allowed for evaluating the total choline peak (tCho) as a biomarker of malignancy; DWI showed that restricted diffusivity is correlated with high cellularity and tumor aggressiveness. Secondary evidence on the two approaches is now available from systematic reviews and meta-analyses, mainly considered in this article: pooled sensitivity ranged 71-74% for 1H-MRS and 84-91% for DWI; specificity 78-88% and 75-84%, respectively. Interesting research perspectives are opened for both techniques, including multivoxel MRS and statistical strategies for classification of MR spectra as well as diffusion tensor imaging and intravoxel incoherent motion for DWI. However, when looking at a clinical perspective, while MRS remained a research tool with important limitations, such as relatively long acquisition times, frequent low quality spectra, difficult standardization, and quantification of tCho tissue concentration, DWI has been integrated in the standard clinical protocols of breast MRI and several studies showed its potential value as a stand-alone approach for BC detection.