We summarise here the information to be provided to women and referring physicians about percutaneous breast biopsy and lesion localisation under imaging guidance. After explaining why a preoperative diagnosis with a percutaneous biopsy is preferred to surgical biopsy, we illustrate the criteria used by radiologists for choosing the most appropriate combination of device type for sampling and imaging technique for guidance. Then, we describe the commonly used devices, from fine-needle sampling to tissue biopsy with larger needles, namely core needle biopsy and vacuum-assisted biopsy, and how mammography, digital breast tomosynthesis, ultrasound, or magnetic resonance imaging work for targeting the lesion for sampling or localisation. The differences among the techniques available for localisation (carbon marking, metallic wire, radiotracer injection, radioactive seed, and magnetic seed localisation) are illustrated. Type and rate of possible complications are described and the issue of concomitant antiplatelet or anticoagulant therapy is also addressed. The importance of pathological-radiological correlation is highlighted: when evaluating the results of any needle sampling, the radiologist must check the concordance between the cytology/pathology report of the sample and the radiological appearance of the biopsied lesion. We recommend that special attention is paid to a proper and tactful approach when communicating to the woman the need for tissue sampling as well as the possibility of cancer diagnosis, repeat tissue sampling, and or even surgery when tissue sampling shows a lesion with uncertain malignant potential (also referred to as "high-risk" or B3 lesions). Finally, seven frequently asked questions are answered.

Chest x-ray (CXR) can play a role in diagnosing patients with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but only few small-scale studies are available. We assessed the diagnostic performance of CXR in consecutive patients presenting at the emergency room at the Policlinico San Donato, Milan, Italy from February 24 to April 8, 2020 for suspected SARS-CoV-2 infection. The results of CXR were classified as positive or negative according to the original prospective radiologic reports. To overcome the limitations of reverse transcriptase-polymerase chain reaction (RT-PCR) swab, especially oscillating sensitivity, we added the information obtained from phone calls to discharged patients with negative initial RT-PCR. Thus, we included 535 patients with concomitant CXR and RT-PCR on admission (aged 65±17 y; 340 males, 195 females), resulting in 408 RT-PCR positive and 127 negative patients at the composite reference standard. Original CXR reports showed an 89.0% sensitivity (95% confidence intervals [CI], 85.5%-91.8%), 60.6% specificity (95% CI, 51.6%-69.2%), 87.9% positive predictive value (95% CI, 84.4%-90.9%), and 63.1% negative predictive value (95% CI, 53.9%-71.7%). The adoption of CXR alongside RT-PCR to triage patients with suspected SARS-CoV-2 infection could foster a safe and efficient workflow, counteracting possible false negative RT-PCR results.

Background Lower muscle mass is a known predictor of unfavorable outcome, but its prognostic impact on COVID-19 patients is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in COVID-19 patients. Materials and Methods Clinical/laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed COVID-19, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. Extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation of paravertebral muscles were measured on axial CT images at T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation odds ratios (OR) with 95% confidence intervals (CIs), were used to build four models to predict ICU admission and death, tested and compared using receiver operating characteristic curve (ROC) analysis. Results A total 552 patients (364 men; median age 65 years, interquartile range 54–75) were included. In a CT-based model, lower-than-median T5 paravertebral muscle area showed the highest ORs for ICU admission (OR 4.8, 95% CI 2.7–8.5; P <.001) and death (OR 2.3, 95% CI 1.0–2.9; P =.027). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle area still showed the highest ORs both for ICU admission (OR 4.3; 95% CI 2.5–7.7; P <.001) and death (OR 2.3, 95% CI 1.3–3.7; P =.001). At ROC analysis, the CT-based model and the model including clinical variables showed the same area under the curve (AUC) for ICU admission prediction (AUC 0.83, P =.380) and were not different in predicting death (AUC 0.86 versus AUC 0.87, respectively, P =.282). Conclusion In hospitalized patients with COVID-19, lower muscle mass on CT was independently associated with ICU admission and hospital mortality.

ObjectivesWe tested artificial intelligence (AI) to support the diagnosis of COVID-19 using chest X-ray (CXR). Diagnostic performance was computed for a system trained on CXRs of Italian subjects from two hospitals in Lombardy, Italy. MethodsWe used for training and internal testing an ensemble of ten convolutional neural networks (CNNs) with mainly bedside CXRs of 250 COVID-19 and 250 non-COVID-19 subjects from two hospitals.We then tested such system on bedside CXRs of an independent group of 110 patients 36 non-COVID-19) from one of the two hospitals. A retrospective reading was performed by two radiologists in the absence of any clinical information, with the aim to differentiate COVID-19 from non-COVID-19 patients. Real-time polymerase chain reaction served as reference standard.Results At 10-fold cross-validation, our AI model classified COVID-19 and non COVID-19 patients with 0.78 sensitivity (95% confidence interval [CI] 0.74-0.81), 0.82 specificity (95% CI 0.78-0.85) and 0.89 area under the curve (AUC) (95% CI 0.86-0.91). For the independent dataset, AI showed 0.80 sensitivity (95% CI 0.72-0.86) (59/74), 0.81 specificity (29/36) (95% CI 0.73-0.87), and 0.81 AUC (95% CI 0.73-0.87). Radiologists' reading obtained 0.63 sensitivity (95% CI 0.52-0.74) and 0.78 specificity (95% CI 0.61-0.90) in one centre and 0.64 sensitivity (95% CI 0.52-0.74) and 0.86 specificity (95% CI 0.71-0.95) in the other.Conclusions This preliminary experience based on ten CNNs trained on a limited training dataset shows an interesting potential of AI for COVID-19 diagnosis. Such tool is in training with new CXRs to further increase its performance.

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 (I 2 = 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 (I 2 = 78%) rather than those managed with follow-up (I 2 = 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.