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Breast cancer remains the most prevalent cancer among women worldwide, necessitating advancements in diagnostic methods. The integration of artificial intelligence (AI) into mammography has shown promise in enhancing diagnostic accuracy. However, understanding patient perspectives, particularly considering the psychological impact of breast cancer diagnoses, is crucial. This narrative review synthesizes literature from 2000 to 2023 to examine breast cancer patients' attitudes towards AI in breast imaging, focusing on trust, acceptance, and demographic influences on these views. Methodologically, we employed a systematic literature search across databases such as PubMed, Embase, Medline, and Scopus, selecting studies that provided insights into patients' perceptions of AI in diagnostics. Our review included a sample of seven key studies after rigorous screening, reflecting varied patient trust and acceptance levels towards AI. Overall, we found a clear preference among patients for AI to augment rather than replace the diagnostic process, emphasizing the necessity of radiologists' expertise in conjunction with AI to enhance decision-making accuracy. This paper highlights the importance of aligning AI implementation in clinical settings with patient needs and expectations, emphasizing the need for human interaction in healthcare. Our findings advocate for a model where AI augments the diagnostic process, underlining the necessity for educational efforts to mitigate concerns and enhance patient trust in AI-enhanced diagnostics. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper delves into the persistent issue of unequal access to medical imaging, with a particular focus on breast cancer screening and its impact on marginalized communities and racial/ethnic minorities. Central to our discussion is the role of scientific mobility among radiologists in fostering healthcare policy changes that promote diversity and cultural competence. We propose various strategies to bridge this gap, including cultural education, sensitivity training, and diversifying the radiology workforce. These measures aim to improve communication with diverse patient groups and reduce healthcare disparities. Additionally, we explore the challenges and advantages of teleradiology as a means to extend medical imaging services to underserved areas. In the context of artificial intelligence, we emphasize the critical need to validate algorithms across diverse populations to ensure unbiased and equitable healthcare outcomes. Overall, this paper underscores the importance of international collaboration in addressing global access barriers, presenting it as a key to mitigating disparities in medical imaging access and contributing to the pursuit of equitable healthcare. Access to medical imaging is pivotal in healthcare, playing a crucial role in the prevention, diagnosis, and management of diseases. However, disparities persist in this scenario, disproportionately affecting marginalized communities, racial and ethnic minorities, and individuals facing linguistic or cultural barriers. This paper critically assesses methods to mitigate these disparities, with a focus on breast cancer screening. We underscore scientific mobility as a vital tool for radiologists to advocate for healthcare policy changes: it not only enhances diversity and cultural competence within the radiology community but also fosters international cooperation and knowledge exchange among healthcare institutions. Efforts to ensure cultural competency among radiologists are discussed, including ongoing cultural education, sensitivity training, and workforce diversification. These initiatives are key to improving patient communication and reducing healthcare disparities. This paper also highlights the crucial role of policy changes and legislation in promoting equal access to essential screening services like mammography. We explore the challenges and potential of teleradiology in improving access to medical imaging in remote and underserved areas. In the era of artificial intelligence, this paper emphasizes the necessity of validating its models across a spectrum of populations to prevent bias and achieve equitable healthcare outcomes. Finally, the importance of international collaboration is illustrated, showcasing its role in sharing insights and strategies to overcome global access barriers in medical imaging. Overall, this paper offers a comprehensive overview of the challenges related to disparities in medical imaging access and proposes actionable strategies to address these challenges, aiming for equitable healthcare delivery. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate the use of contrast-free magnetic resonance imaging (MRI) as an innovative screening method for detecting breast cancer in high-risk asymptomatic women. Specifically, the researchers evaluated the diagnostic performance of diffusion-weighted imaging (DWI) in this population. Methods: MR images from asymptomatic women, carriers of a germline mutation in either the BRCA1 or BRCA2 gene, collected in a single center from January 2019 to December 2021 were retrospectively evaluated. A radiologist with experience in breast imaging (R1) and a radiology resident (R2) independently evaluated DWI/ADC maps and, in case of doubts, T2-WI. The standard of reference was the pathological diagnosis through biopsy or surgery, or ≥1 year of clinical and radiological follow-up. Diagnostic performances were calculated for both readers with a 95% confidence interval (CI). The agreement was assessed using Cohen's kappa (κ) statistics. Results: Out of 313 women, 145 women were included (49.5 ± 12 years), totaling 344 breast MRIs with DWI/ADC maps. The per-exam cancer prevalence was 11/344 (3.2%). The sensitivity was 8/11 (73%; 95% CI: 46–99%) for R1 and 7/11 (64%; 95% CI: 35–92%) for R2. The specificity was 301/333 (90%; 95% CI: 87–94%) for both readers. The diagnostic accuracy was 90% for both readers. R1 recalled 40/344 exams (11.6%) and R2 recalled 39/344 exams (11.3%). Inter-reader reproducibility between readers was in moderate agreement (κ = 0.43). Conclusions: In female carriers of a BRCA1/2 mutation, breast DWI supplemented with T2-WI allowed breast cancer detection with high sensitivity and specificity by a radiologist with extensive experience in breast imaging, which is comparable to other screening tests. The findings suggest that DWI and T2-WI have the potential to serve as a stand-alone method for unenhanced breast MRI screening in a selected population, opening up new perspectives for prospective trials. [ABSTRACT FROM AUTHOR]

Recent technological advances in the field of artificial intelligence hold promise in addressing medical challenges in breast cancer care, such as early diagnosis, cancer subtype determination and molecular profiling, prediction of lymph node metastases, and prognostication of treatment response and probability of recurrence. Radiomics is a quantitative approach to medical imaging, which aims to enhance the existing data available to clinicians by means of advanced mathematical analysis using artificial intelligence. Various published studies from different fields in imaging have highlighted the potential of radiomics to enhance clinical decision making. In this review, we describe the evolution of AI in breast imaging and its frontiers, focusing on handcrafted and deep learning radiomics. We present a typical workflow of a radiomics analysis and a practical "how-to" guide. Finally, we summarize the methodology and implementation of radiomics in breast cancer, based on the most recent scientific literature to help researchers and clinicians gain fundamental knowledge of this emerging technology. Alongside this, we discuss the current limitations of radiomics and challenges of integration into clinical practice with conceptual consistency, data curation, technical reproducibility, adequate accuracy, and clinical translation. The incorporation of radiomics with clinical, histopathological, and genomic information will enable physicians to move forward to a higher level of personalized management of patients with breast cancer. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast cancer is the most frequent cancer among women: early diagnosis and management of breast lesions are crucial to achieve a better prognosis for patients with this diagnosis. Breast ultrasound (US) is one of the main techniques for the management of breast lesions and it is important in doubtful findings on mammography and in the evaluation of dense breasts. Unfortunately, US has a high rate of false positive and has high operator dependence. Ultrasound CAD (computer-aided diagnosis) and radiomics are newly developed tools that can help solve these issues: this study aims to create a radiomics score from breast US to predict malignancy of a breast lesion, and to also combine this score with CAD and sonographer performances. Finally, we would like to create a prediction tool of US radiomics features combined with CAD, clinical parameters, and Breast Imaging Reporting and Data System evaluation for the prediction of malignancy of breast lesions. The study aimed to evaluate the performance of radiomics features and one ultrasound CAD (computer-aided diagnosis) in the prediction of the malignancy of a breast lesion detected with ultrasound and to develop a nomogram incorporating radiomic score and available information on CAD performance, conventional Breast Imaging Reporting and Data System evaluation (BI-RADS), and clinical information. Data on 365 breast lesions referred for breast US with subsequent histologic analysis between January 2020 and March 2022 were retrospectively collected. Patients were randomly divided into a training group (n = 255) and a validation test group (n = 110). A radiomics score was generated from the US image. The CAD was performed in a subgroup of 209 cases. The radiomics score included seven radiomics features selected with the LASSO logistic regression model. The multivariable logistic model incorporating CAD performance, BI-RADS evaluation, clinical information, and radiomic score as covariates showed promising results in the prediction of the malignancy of breast lesions: Area under the receiver operating characteristic curve, [AUC]: 0.914; 95% Confidence Interval, [CI]: 0.876–0.951. A nomogram was developed based on these results for possible future applications in clinical practice. [ABSTRACT FROM AUTHOR]

A digital twin is a virtual model developed to accurately reflect a physical thing or a system. In radiology, a digital twin of a radiological device enables developers to test its characteristics, make alterations to the design or materials, and test the success or failure of the modifications in a virtual environment. Innovative technologies, such as AI and -omics sciences, may build virtual models for patients that are continuously adjustable based on live-tracked health/lifestyle parameters. Accordingly, healthcare could use digital twins to improve personalized medicine. Furthermore, the accumulation of digital twin models from real-world deployments will enable large cohorts of digital patients that may be used for virtual clinical trials and population studies. Through their further refinement, development, and application into clinical practice, digital twins could be crucial in the era of personalized medicine, revolutionizing how diseases are detected and managed. Although significant challenges remain in the development of digital twins, a structural modification to the current operating models is occurring, and radiologists can guide the introduction of such technology into healthcare. [ABSTRACT FROM AUTHOR]

• Breast screening needs a critical balance of early detection and risk of overtreatment. • AI integration elevates diagnostic precision in breast cancer screening. • Emphasis on personalized approaches in screening mitigate risks of overtreatment. • Emerging imaging technologies may significantly improve early cancer detection. • Ensuring equitable access to breast cancer screening is vital for diverse populations. Breast cancer remains a significant global health challenge, with projections indicating a troubling increase in incidence. Breast cancer screening programs have long been hailed as life-saving initiatives, yet their true impact on mortality rates is a subject of ongoing debate. Screening poses the risk of false positives and the detection of indolent tumors, potentially leading to overtreatment. Bias factors, including lead time, length time, and selection biases, further complicate the assessment of screening efficacy. Recent studies suggest that AI-driven image analysis may revolutionize breast cancer screening, maintaining diagnostic accuracy while reducing radiologists' workload. However, the generalizability of these findings to diverse populations is a critical consideration. Personalized screening approaches and equitable access to advanced technologies are essential to mitigate disparities. In conclusion, the breast cancer screening landscape is evolving, emphasizing the need for risk stratification, appropriate imaging modalities, and a personalized approach to reduce overdiagnosis and focus on cancers with the potential to impact lives while prioritizing patient-centered care. [ABSTRACT FROM AUTHOR]

Radiomics is an emerging translational field of medicine based on the extraction of highdimensional data from radiological images, with the purpose to reach reliable models to be applied into clinical practice for the purposes of diagnosis, prognosis and evaluation of disease response to treatment. We aim to provide the basic information on radiomics to radiologists and clinicians who are focused on breast cancer care, encouraging cooperation with scientists to mine data for a better application in clinical practice. We investigate the workflow and clinical application of radiomics in breast cancer care, as well as the outlook and challenges based on recent studies. Currently, radiomics has the potential ability to distinguish between benign and malignant breast lesions, to predict breast cancer's molecular subtypes, the response to neoadjuvant chemotherapy and the lymph node metastases. Even though radiomics has been used in tumor diagnosis and prognosis, it is still in the research phase and some challenges need to be faced to obtain a clinical translation. In this review, we discuss the current limitations and promises of radiomics for improvement in further research. [ABSTRACT FROM AUTHOR]

Numerous imaging modalities may be used for the staging of women with advanced breast cancer. Although bone scintigraphy and multiplanar-CT are the most frequently used tests, others including PET, MRI and hybrid scans are also utilised, with no specific recommendations of which test should be preferentially used. We review the evidence behind the imaging modalities that characterise metastases in breast cancer and to update the evidence on comparative imaging accuracy. [ABSTRACT FROM AUTHOR]

To determine the prevalence and predictive value of a series of commonly used MRI criteria for posterolateral extraprostatic extension (EPE) of prostate cancer (PCa). The presence of EPE in index lesions visible on prebiopsy mpMRI (T2w, DWI and DCE on a 3 Tesla-system) of biopsy-proven PCa patients was blindly assessed retrospectively by two radiologists with 8- and 17-years of experience on the basis of 8 commonly used staging criteria. Radical prostatectomy was used as standard of reference. The prevalences and positive predictive values (PPV) of all criteria were calculated for each reader separately and averaged for the two readers together. Cohen's K and percentage of agreement were used to assess the interobserver agreement. In 51 patients (mean age: 63 years; mean PSA: 17.2 ng/ml), tumor-capsule contact was the most prevalent sign (average 56,9%), but with the lowest PPV (average 51.9%), although increasing with broader capsular contact (56.5% if ≥10 mm; 87.5% if ≥20 mm; 100% if ≥25 mm). "Early signs" of EPE such as bulging, capsular disruption and unsharp prostatic margin showed a prevalence of 11.8%–18.6% on average, with 74.5%–86.3% of agreement; the average PPV range was 69.0%–75.0%. "Late signs" of EPE such as irregular prostatic contour, periprostatic fat infiltration, rectoprostatic angle obliteration and periprostatic mass showed a prevalence of 2.9%–8.8% on average, with 86.3%–94.1% of agreement; the average PPVs ranged between 85.7% and 100%. "Early" signs of EPE show high prevalences but low PPVs, while "late" signs show lower prevalences but higher PPVs. MRI-staging following this chronological concept can standardize morphologic staging and decrease the existing multi-reader variability. • Prostate cancer chronologically grows from intraprostatic to extraprostatic • MRI-criteria for extraprostatic extension (EPE) can be based on the evolutionary concept of prostate cancer growth • "Early" signs of EPE show high prevalences but low positive predictive values • "Late" signs of EPE show lower prevalences but higher positive predictive values • MRI-staging based on the evolutionary concept can decrease the multi-reader variability [ABSTRACT FROM AUTHOR]

One of the ways in which modern radiology is manifesting itself in higher education and research is through the increasing importance of scientific mobility. This article seeks to provide an overview and a prospective of radiology fellows in their last year of training about the current trends and policy tools for promoting mobility among young radiologists, especially inside the European Union. Nowadays, the need to promote international cooperation is even greater to ensure that the best evidence-based medical practices become a common background of a next cross-border generation of radiologists. Organisations such as the European Society of Radiology (ESR) and the Radiological Society of North America (RSNA) are called upon to play as guarantors of the training of young radiologists building know-how and world-class excellence. Today, it is not just being certified radiologist that matters, the place where the training was done plays an important role in enhancing chances when applying for a high-level job or fellowship. The article argues that the mobility of radiology trainees is an indispensable prerequisite to face new challenges, including the application of artificial intelligence to medical imaging, which will require a large multicentre collaboration. [ABSTRACT FROM AUTHOR]

One of the ways in which modern radiology is manifesting itself in higher education and research is through the increasing importance of scientific mobility. This article seeks to provide an overview and a prospective of radiology fellows in their last year of training about the current trends and policy tools for promoting mobility among young radiologists, especially inside the European Union. Nowadays, the need to promote international cooperation is even greater to ensure that the best evidence-based medical practices become a common background of a next cross-border generation of radiologists. Organisations such as the European Society of Radiology (ESR) and the Radiological Society of North America (RSNA) are called upon to play as guarantors of the training of young radiologists building know-how and world-class excellence. Today, it is not just being certified radiologist that matters, the place where the training was done plays an important role in enhancing chances when applying for a high-level job or fellowship. The article argues that the mobility of radiology trainees is an indispensable prerequisite to face new challenges, including the application of artificial intelligence to medical imaging, which will require a large multicentre collaboration. [ABSTRACT FROM AUTHOR]

Abstract: Worldwide interest in artificial intelligence (AI) applications is growing rapidly. In medicine, devices based on machine/deep learning have proliferated, especially for image analysis, presaging new significant challenges for the utility of AI in healthcare. This inevitably raises numerous legal and ethical questions. In this paper we analyse the state of AI regulation in the context of medical device development, and strategies to make AI applications safe and useful in the future. We analyse the legal framework regulating medical devices and data protection in Europe and in the United States, assessing developments that are currently taking place. The European Union (EU) is reforming these fields with new legislation (General Data Protection Regulation [GDPR], Cybersecurity Directive, Medical Devices Regulation, In Vitro Diagnostic Medical Device Regulation). This reform is gradual, but it has now made its first impact, with the GDPR and the Cybersecurity Directive having taken effect in May, 2018. As regards the United States (U.S.), the regulatory scene is predominantly controlled by the Food and Drug Administration. This paper considers issues of accountability, both legal and ethical. The processes of medical device decision-making are largely unpredictable, therefore holding the creators accountable for it clearly raises concerns. There is a lot that can be done in order to regulate AI applications. If this is done properly and timely, the potentiality of AI based technology, in radiology as well as in other fields, will be invaluable.Teaching Points: • AI applications are medical devices supporting detection/diagnosis, work-flow, cost-effectiveness.• Regulations for safety, privacy protection, and ethical use of sensitive information are needed.• EU and U.S. have different approaches for approving and regulating new medical devices.• EU laws consider cyberattacks, incidents (notification and minimisation), and service continuity.• U.S. laws ask for opt-in data processing and use as well as for clear consumer consent. [ABSTRACT FROM AUTHOR]

Background Dual-phase cone beam computed tomography (DP-CBCT) and automatic vessel detection (AVD) software are helpful tools for detecting arteries before planned endovascular interventions. Purpose To evaluate the usefulness of DP-CBCT and AVD software in guiding the trans-arterial embolization (TAE) of challenging T2 lumbar endoleaks (T2-L-EL). Material and Methods Ten patients with T2-L-EL were included in this study. The accuracy of DP-CBCT and the AVD software was defined by the ability to detect the endoleak and arterial feeding vessel, respectively. Technical success was defined as the correct positioning of the microcatheter using AVD software and the successful embolization of the endoleak. Clinical success was defined as the absence of recurrent endoleaks during follow-up and the stability of the sac diameter for persistent endoleaks. The total volume of iodinated contrast medium, overall procedure time, mean procedural radiation dose, and mean fluoroscopy time were recorded. Results The EL was detected by DP-CBCT in all patients. The AVD software identified the feeding arterial branch in all cases. In one patient, the nidus of the endoleak was not reached due to the small caliber of the feeding artery, even though the software had clearly identified the vessel route. The mean contrast volume was 109 mL, the mean overall procedural time was 74.3 min. The mean procedural radiation dose was 140.97 Gy cm2, and the mean fluoroscopy time was 29.8 min. Conclusion The use of DP-CBCT and the AVD software is feasible and may facilitate successful embolization in challenging occult T2-L-EL with complex vasculature. [ABSTRACT FROM AUTHOR]

Objective: Although breast cancer screening can benefit from Artificial Intelligence (AI), it is still unknown whether, to which extent or under which conditions, the use of AI is going to be accepted by the general population. The aim of our study is to evaluate what the females who are eligible for breast cancer screening know about AI and how they perceive such innovation. Methods: We used a prospective survey consisting of a 11‐multiple‐choice questionnaire evaluating statistical associations with Chi‐Square‐test or Fisher‐exact‐test. Multinomial‐logistic‐regression was performed on items with more than two response categories. Odds ratio (OR) with 95% CI were computed to estimate the probability of a specific response according to patient's characteristics. Results: In the 800 analysed questionnaires, 51% of respondents confirmed to have knowledge of AI. Of these, 88% expressed a positive opinion about its use in medicine. Non‐Italian respondents were associated with the belief of having a deep awareness about AI more often than Italian respondents (OR = 1.91;95% CI[1.10–3.33]). Higher education level was associated with better opinions on the use of AI in medicine (OR = 4.69;95% CI[1.36–16.12]). According to 94% of respondents, the radiologists should always produce their own report on mammograms, whilst 77% agreed that AI should be used as a second reader. Most respondents (52%) considered that both the software developer and the radiologist should be held accountable for AI errors. Conclusions: Most of the females undergoing screening in our Institute approve the introduction of AI, although only as a support to radiologist, and not in substitution thereof. Yet, accountability in case of AI errors is still unsolved. advances in knowledge: This survey may be considered as a pilot‐study for the development of large‐scale studies to understand females's demands and concerns about AI applications in breast cancer screening. [ABSTRACT FROM AUTHOR]

Simple Summary: Screening mammography reduces mortality from breast malignancy. However, breast cancer screening is, unfortunately, hindered due to the poor sensitivity of mammography in dense breasts: up to 15–30% of all cancers may be missed. Given the rapid development of Contrast-Enhanced Mammography (CEM) and its potential for diagnostic use, even in an asymptomatic population, it seems very important to correctly assess the Average Glandular Dose (AGD) for a single CEM examination. Few studies have compared the AGD of CEM versus Digital Mammography (DM) and protocols, including Digital Breast Tomosynthesis (DBT) plus DM, in the same group of patients. The additional role of tomosynthesis versus digital mammography in asymptomatic patients with dense breasts in screening examinations has been well investigated with encouraging results. In this study, we intend to compare the AGD and the diagnostic performance of CEM versus DM, and of CEM versus DM + DBT, performed in the same group of patients over the same period of time in a screening setting. This study aims to evaluate the Average Glandular Dose (AGD) and diagnostic performance of CEM versus Digital Mammography (DM) as well as versus DM plus one-view Digital Breast Tomosynthesis (DBT), which were performed in the same patients at short intervals of time. A preventive screening examination in high-risk asymptomatic patients between 2020 and 2022 was performed with two-view Digital Mammography (DM) projections (Cranio Caudal and Medio Lateral) plus one Digital Breast Tomosynthesis (DBT) projection (mediolateral oblique, MLO) in a single session examination. For all patients in whom we found a suspicious lesion by using DM + DBT, we performed (within two weeks) a CEM examination. AGD and compression force were compared between the diagnostic methods. All lesions identified by DM + DBT were biopsied; then, we assessed whether lesions found by DBT were also highlighted by DM alone and/or by CEM. We enrolled 49 patients with 49 lesions in the study. The median AGD was lower for DM alone than for CEM (3.41 mGy vs. 4.24 mGy, p = 0.015). The AGD for CEM was significantly lower than for the DM plus one single projection DBT protocol (4.24 mGy vs. 5.55 mGy, p < 0.001). We did not find a statistically significant difference in the median compression force between the CEM and DM + DBT. DM + DBT allows the identification of one more invasive neoplasm one in situ lesion and two high-risk lesions, compared to DM alone. The CEM, compared to DM + DBT, failed to identify only one of the high-risk lesions. According to these results, CEM could be used in the screening of asymptomatic high-risk patients. [ABSTRACT FROM AUTHOR]

Background: Image-guided vacuum-assisted breast biopsy (VABB) of the tumour bed, performed after neoadjuvant therapy, is increasingly being used to assess residual cancer and to potentially identify to identify pathological complete response (pCR). In this study, the accuracy of preoperative VABB specimens was assessed and compared with surgical specimens in patients with triple-negative or human epidermal growth factor receptor 2 (HER2)-positive invasive ductal breast cancer after neoadjuvant therapy. As a secondary endpoint, the performance of contrast-enhanced MRI of the breast and PET-CT for response prediction was assessed. Methods: This single-institution prospective pilot study enrolled patients from April 2018 to April 2021 with a complete response on imaging (iCR) who subsequently underwent VABB before surgery. Those with a pCR at VABB were included in the primary analysis of the accuracy of VABB. The performance of imaging (MRI and PET-CT) was analysed for prediction of a pCR considering both patients with an iCR and those with residual disease at postneoadjuvant therapy imaging. Results: Twenty patients were included in the primary analysis. The median age was 44 (range 35-51) years. At surgery, 18 of 20 patients showed a complete response (accuracy 90 (95 per cent exact c.i. 68 to 99) per cent). Only two patients showed residual ductal intraepithelial neoplasia of grade 2 and 3 respectively. In the secondary analysis, accuracy was similar for MRI and PET-CT (77 versus 78 per cent; P=0.76). Conclusion: VABB in patients with an iCR might be a promising method to select patients for de-escalation of surgical treatment in triple-negative or HER2-positive breast cancer. The present results support such an approach and should inform the design of future trials on de-escalation of surgery. [ABSTRACT FROM AUTHOR]

Simple Summary: Artificial Intelligence (AI) has been increasingly used in radiology to improve diagnostic procedures over the past decades. The application of AI at the time of cancer diagnosis also creates challenges in the way doctors should communicate the use of AI to patients. The present systematic review deals with the patient's psycho-cognitive perspective on AI and the interpersonal skills between patients and physicians when AI is implemented in cancer diagnosis communication. Evidence from the retrieved studies pointed out that the use of AI in radiology is negatively associated with patient trust in AI and patient-centered communication in cancer disease. Background: In the past decade, interest in applying Artificial Intelligence (AI) in radiology to improve diagnostic procedures increased. AI has potential benefits spanning all steps of the imaging chain, from the prescription of diagnostic tests to the communication of test reports. The use of AI in the field of radiology also poses challenges in doctor–patient communication at the time of the diagnosis. This systematic review focuses on the patient role and the interpersonal skills between patients and physicians when AI is implemented in cancer diagnosis communication. Methods: A systematic search was conducted on PubMed, Embase, Medline, Scopus, and PsycNet from 1990 to 2021. The search terms were: ("artificial intelligence" or "intelligence machine") and "communication" "radiology" and "oncology diagnosis". The PRISMA guidelines were followed. Results: 517 records were identified, and 5 papers met the inclusion criteria and were analyzed. Most of the articles emphasized the success of the technological support of AI in radiology at the expense of patient trust in AI and patient-centered communication in cancer disease. Practical implications and future guidelines were discussed according to the results. Conclusions: AI has proven to be beneficial in helping clinicians with diagnosis. Future research may improve patients' trust through adequate information about the advantageous use of AI and an increase in medical compliance with adequate training on doctor–patient diagnosis communication. [ABSTRACT FROM AUTHOR]

Simple Summary: Nowadays, the only widely recognized method for evaluating the efficacy of neoadjuvant chemotherapy is the assessment of the pathological response through surgery. However, delivering chemotherapy to not-responders could expose them to unnecessary drug toxicity with delayed access to other potentially effective therapies. Radiomics could be useful in the early detection of resistance to chemotherapy, which is crucial for switching treatment strategy. We determined whether tumor radiomic features extracted from a highly homogeneous database of breast MRI can improve the prediction of response to chemotherapy in patients with breast cancer, in addiction to biological characteristics, potentially avoiding unnecessary treatment. Objectives: We aimed to determine whether radiomic features extracted from a highly homogeneous database of breast MRI could non-invasively predict pathological complete responses (pCR) to neoadjuvant chemotherapy (NACT) in patients with breast cancer. Methods: One hundred patients with breast cancer receiving NACT in a single center (01/2017–06/2019) and undergoing breast MRI were retrospectively evaluated. For each patient, radiomic features were extracted within the biopsy-proven tumor on T1-weighted (T1-w) contrast-enhanced MRI performed before NACT. The pCR to NACT was determined based on the final surgical specimen. The association of clinical/biological and radiomic features with response to NACT was evaluated by univariate and multivariable analysis by using random forest and logistic regression. The performances of all models were assessed using the areas under the receiver operating characteristic curves (AUC) with 95% confidence intervals (CI). Results: Eighty-three patients (mean (SD) age, 47.26 (8.6) years) were included. Patients with HER2+, basal-like molecular subtypes and Ki67 ≥ 20% presented a pCR to NACT more frequently; the clinical/biological model's AUC (95% CI) was 0.81 (0.71–0.90). Using 136 representative radiomics features selected through cluster analysis from the 1037 extracted features, a radiomic score was calculated to predict the response to NACT, with AUC (95% CI): 0.64 (0.51–0.75). After combining the clinical/biological and radiomics models, the AUC (95% CI) was 0.83 (0.73–0.92). Conclusions: MRI-based radiomic features slightly improved the pre-treatment prediction of pCR to NACT, in addiction to biological characteristics. If confirmed on larger cohorts, it could be helpful to identify such patients, to avoid unnecessary treatment. [ABSTRACT FROM AUTHOR]

(1) Background: the study of dynamic contrast enhancement (DCE) has a limited role in the detection of prostate cancer (PCa), and there is a growing interest in performing unenhanced biparametric prostate-MRI (bpMRI) instead of the conventional multiparametric-MRI (mpMRI). In this study, we aimed to retrospectively compare the performance of the mpMRI, which includes DCE study, and the unenhanced bpMRI, composed of only T2-weighted imaging and diffusion-weighted imaging (DWI), in PCa detection in men with elevated prostate-specific-antigen (PSA) levels. (2) Methods: a 1.5 T MRI, with an endorectal-coil, was performed on 431 men (aged 61.5 ± 8.3 years) with a PSA ≥4.0 ng/mL. The bpMRI and mpMRI tests were independently assessed in separate sessions by two readers with 5 (R1) and 3 (R2) years of experience. The histopathology or ≥2 years follow-up served as a reference standard. The sensitivity and specificity were calculated with their 95% CI, and McNemar's and Cohen's κ statistics were used. (3) Results: in 195/431 (45%) of histopathologically proven PCa cases, 62/195 (32%) were high-grade PCa (GS ≥ 7b) and 133/195 (68%) were low-grade PCa (GS ≤ 7a). The PCa could be excluded by histopathology in 58/431 (14%) and by follow-up in 178/431 (41%) of patients. For bpMRI, the sensitivity was 164/195 (84%, 95% CI: 79–89%) for R1 and 156/195 (80%, 95% CI: 74–86%) for R2; while specificity was 182/236 (77%, 95% CI: 72–82%) for R1 and 175/236 (74%, 95% CI: 68–80%) for R2. For mpMRI, sensitivity was 168/195 (86%, 95% CI: 81–91%) for R1 and 160/195 (82%, 95% CI: 77–87%) for R2; while specificity was 184/236 (78%, 95% CI: 73–83%) for R1 and 177/236 (75%, 95% CI: 69–81%) for R2. Interobserver agreement was substantial for both bpMRI (κ = 0.802) and mpMRI (κ = 0.787). (4) Conclusions: the diagnostic performance of bpMRI and mpMRI were similar, and no high-grade PCa was missed with bpMRI. [ABSTRACT FROM AUTHOR]

Simple Summary: The role of magnetic resonance imaging (MRI) in breast cancer has expanded in the last decade, and studies have demonstrated good sensitivity and specificity of diffusion-weighted imaging (DWI), a functional imaging technique reflecting water diffusion properties in tissues. However, clear results about the reproducibility of DWI are still missing. To utilize DWI as a reliable stand-alone technique for breast cancer detection, the inter-reader agreement of the measurement must be assessed. Accordingly, in this study, we assess the inter-reader reproducibility to retrospectively evaluate the agreement of breast cancer detection using DWI as a stand-alone technique. As our results show a good agreement only in expert readers, the assumption that a breast MRI based only on qualitative analysis of DWI, with fewer variables, may be easier for a non-expert reader to learn seems disproved, and future prospective studies should assess the right time for appropriate training for radiologists to investigate the potential role of DWI as a stand-alone method for un-enhanced breast MRI. Purpose: In order to evaluate the use of un-enhanced magnetic resonance imaging (MRI) for detecting breast cancer, we evaluated the accuracy and the agreement of diffusion-weighted imaging (DWI) through the inter-reader reproducibility between expert and non-expert readers. Material and Methods: Consecutive breast MRI performed in a single centre were retrospectively evaluated by four radiologists with different levels of experience. The per-breast standard of reference was the histological diagnosis from needle biopsy or surgical excision, or at least one-year negative follow-up on imaging. The agreement across readers (by inter-reader reproducibility) was examined for each breast examined using Cohen's and Fleiss' kappa (κ) statistics. The Wald test was used to test the difference in inter-reader agreement between expert and non-expert readers. Results: Of 1131 examinations, according to our inclusion and exclusion criteria, 382 women were included (49.5 ± 12 years old), 40 of them with unilateral mastectomy, totaling 724 breasts. Overall inter-reader reproducibility was substantial (κ = 0.74) for expert readers and poor (κ = 0.37) for non- expert readers. Pairwise agreement between expert readers and non-expert readers was moderate (κ = 0.60) and showed a statistically superior agreement of the expert readers over the non-expert readers (p = 0.003). Conclusions: DWI showed substantial inter-reader reproducibility among expert-level readers. Pairwise comparison showed superior agreement of the expert readers over the non-expert readers, with the expert readers having higher inter-reader reproducibility than the non-expert readers. These findings open new perspectives for prospective studies investigating the actual role of DWI as a stand-alone method for un-enhanced breast MRI. [ABSTRACT FROM AUTHOR]

Italy has one of the highest COVID-19 clinical burdens in the world and Lombardy region accounts for more than half of the deaths of the country. Since COVID-19 is a novel disease, early impactful decisions are often based on experience of referral centres. We report the re-organisation which our institute (IEO, European Institute of Oncology), a cancer referral centre in Lombardy, went through to make our breast-imaging division pandemic-proof. Using personal-protective-equipment and innovative protocols, we provided essential breast-imaging procedures during COVID-19 pandemic without compromising cancer outcomes. The emergency management and infection-control-measures implemented in our division protected both the patients and the staff, making this experience useful for other radiology departments dealing with the pandemic. [ABSTRACT FROM AUTHOR]

Multiparametric ultrasound (MPUS), combining conventional techniques (greyscale and colour Doppler ultrasound), ultrasound strain elastography, and contrast-enhanced ultrasound (CEUS), has been successfully used in the assessment of adult scrotal pathology. Contrast-enhanced ultrasound can confidently establish testicular tissue vascularity even in the small-volume paediatric testis. Elastography provides further assessment of tissue stiffness, potentially adding useful diagnostic information. In children, ultrasonography is particularly advantageous, being safe, radiation-free and negating the need for sedation or general anaesthesia during the imaging evaluation. In this review article, we aim to familiarise readers with the MPUS scanning protocol used for paediatric scrotal examination and provide an overview of scrotal MPUS features, with particular focus to clinical indications where MPUS may be advantageous over conventional ultrasonography. [ABSTRACT FROM AUTHOR]

Simple Summary: This retrospective study investigates histopathological outcomes, upgrade rates, and disease-free survival (DFS) in high-risk breast lesions, including atypical ductal hyperplasia (ADH or DIN1b) and lobular in situ neoplasms (LIN 1 and 2), following Vacuum-Assisted Breast Biopsy (VABB) and surgical excision. Focusing on 320 patients who underwent stereotactic VABB, with 246 individuals diagnosed with ADH (120) or LIN (126), the study addresses the challenge posed by these lesions due to their association with synchronous or adjacent Breast Cancer (BC) and increased future BC risk. The study underscores the importance of a multidisciplinary approach, acknowledging the evolving role of VABB, and emphasizes the need for careful follow-up, particularly for lobular lesions. It offers valuable insights for clinicians navigating the complex landscape of high-risk breast lesions, advocating for heightened awareness and vigilance in managing these lesions and contributing to the ongoing refinement of clinical strategies in BC care. This retrospective study investigates the histopathological outcomes, upgrade rates, and disease-free survival (DFS) of high-risk breast lesions, including atypical ductal hyperplasia (ADH or DIN1b) and lobular in situ neoplasms (LIN), following Vacuum-Assisted Breast Biopsy (VABB) and surgical excision. The study addresses the challenge posed by these lesions due to their association with synchronous or adjacent Breast Cancer (BC) and increased future BC risk. The research, comprising 320 patients who underwent stereotactic VABB, focuses on 246 individuals with a diagnosis of ADH (120) or LIN (126) observed at follow-up. Pathological assessments, categorized by the UK B-coding system, were conducted, and biopsy samples were compared with corresponding excision specimens to determine upgrade rates for in situ or invasive carcinoma. Surgical excision was consistently performed for diagnosed ADH or LIN. Finally, patient follow-ups were assessed and compared between LIN and ADH groups to identify recurrence signs, defined as histologically confirmed breast lesions on either the same or opposite side. The results reveal that 176 (71.5%) patients showed no upgrade post-surgery, with ADH exhibiting a higher upgrade rate to in situ pathology than LIN1 (Atypical Lobular Hyperplasia, ALH)/LIN2 (Low-Grade Lobular in situ Carcinoma, LCIS) (38% vs. 20%, respectively, p-value = 0.002). Considering only patients without upgrade, DFS at 10 years was 77%, 64%, and 72% for ADH, LIN1, and LIN2 patients, respectively (p-value = 0.92). The study underscores the importance of a multidisciplinary approach, recognizing the evolving role of VABB. It emphasizes the need for careful follow-up, particularly for lobular lesions, offering valuable insights for clinicians navigating the complex landscape of high-risk breast lesions. The findings advocate for heightened awareness and vigilance in managing these lesions, contributing to the ongoing refinement of clinical strategies in BC care. [ABSTRACT FROM AUTHOR]

Contrast-enhanced mammography (CEM) is a relatively recent diagnostic technique increasingly being utilized in clinical practice. Until recently, there was a lack of standardized reporting for CEM findings. However, this has changed with the publication of a supplement in the Breast Imaging Reporting and Data System (BI-RADS). A comprehensive understanding of CEM is essential for further enhancing its role in both screening and managing patients with breast malignancies. CEM can also be beneficial for problem-solving, improving the management of uncertain breast findings. Practitioners in this field should become more cognizant of how and when to employ this technique and interpret the various CEM findings. This paper aims to outline the key findings in the updated version of the BI-RADS specifically dedicated to CEM. Additionally, it will present some clinical cases commonly encountered in clinical practice. Critical relevance statement Standardized reporting and a thorough understanding of CEM findings are pivotal for advancing the role of CEM in screening and managing breast cancer patients. This standardization contributes significantly to integrating CEM as an essential component of daily clinical practice. Key points • A complete knowledge and understanding of the findings outlined in the new BI-RADS CEM are necessary for accurate reporting. • BI-RADS CEM supplement is intuitive and practical to use. • Standardization of the CEM findings enables more accurate patient management. [ABSTRACT FROM AUTHOR]

The primary aim of our study was to assess the main mammographic and ultrasonographic features of invasive male breast malignancies. The secondary aim was to evaluate whether a specific radiological presentation would be associated with a worse receptor profile. Radiological images (mammography and/or ultrasound) of all patients who underwent surgery for male invasive breast cancer in our institution between 2008 and 2023 were retrospectively analyzed by two breast radiologists in consensus. All significant features of radiological presentation known in the literature were re-evaluated. Fifty-six patients were selected. The mean age at surgery of patients was 69 years (range: 35–81); in 82% of cases (46 patients), the histologic outcome was invasive ductal carcinoma. A total of 28 out of 56 (50%) patients had preoperative mammography; in 9/28 cases (32%), we found a mass with microcalcifications on mammography. The mass presented high density in 25 out of 28 patients (89%); the mass showed irregular margins in 15/28 (54%) cases. A total of 46 out of 56 patients had preoperative ultrasounds. The lesion showed a solid mass in 41/46 (89%) cases. In 5/46 patients (11%), the lesion was a mass with a mixed (partly liquid–partly solid) structure. We did not find any statistically significant correlation between major types of radiological presentation and tumor receptor arrangement. Knowledge of the main radiologic presentation patterns of malignant male breast neoplasm can help better manage this type of disease, which is rare but whose incidence is increasing. [ABSTRACT FROM AUTHOR]

Simple Summary: This review provides a comprehensive overview of mammary Paget disease (MPD) from its historical origins to the current diagnostic and treatment strategies while also exploring promising avenues for future advancements in the field. With improved understanding and ongoing research efforts, we aim to enhance the prognosis and quality of life for individuals affected by this relatively uncommon condition. Mammary Paget disease (MPD) is a rare condition primarily affecting adult women, characterized by unilateral skin changes in the nipple–areolar complex (NAC) and frequently associated with underlying breast carcinoma. Histologically, MPD is identified by large intraepidermal epithelial cells (Paget cells) with distinct characteristics. Immunohistochemical profiles aid in distinguishing MPD from other skin conditions. Clinical evaluation and imaging techniques, including magnetic resonance imaging (MRI), are recommended if MPD is suspected, although definitive diagnosis always requires histological examination. This review delves into the historical context, epidemiology, pathogenesis, clinical manifestations, and diagnosis of MPD, emphasizing the need for early detection. The classification of MPD based on pathogenesis is explored, shedding light on its varied presentations. Treatment options, including mastectomy and breast-conserving surgery, are discussed with clear guidelines for different scenarios. Adjuvant therapies are considered, particularly in cases with underlying breast cancer. Prognostic factors are outlined, underlining the importance of early intervention. Looking to the future, emerging techniques, like liquid biopsy, new immunohistochemical and molecular markers, and artificial intelligence-based image analysis, hold the potential to transform MPD diagnosis and treatment. These innovations offer hope for early detection and improved patient care, though validation through large-scale clinical trials is needed. [ABSTRACT FROM AUTHOR]

We aimed to investigate the association between the radiomic features of contrast-enhanced spectral mammography (CESM) images and a specific receptor pattern of breast neoplasms. In this single-center retrospective study, we selected patients with neoplastic breast lesions who underwent CESM before a biopsy and surgical assessment between January 2013 and February 2022. Radiomic analysis was performed on regions of interest selected from recombined CESM images. The association between the features and each evaluated endpoint (ER, PR, Ki-67, HER2+, triple negative, G2–G3 expressions) was investigated through univariate logistic regression. Among the significant and highly correlated radiomic features, we selected only the one most associated with the endpoint. From a group of 321 patients, we enrolled 205 malignant breast lesions. The median age at the exam was 50 years (interquartile range (IQR) 45–58). NGLDM_Contrast was the only feature that was positively associated with both ER and PR expression (p-values = 0.01). NGLDM_Coarseness was negatively associated with Ki-67 expression (p-value = 0.02). Five features SHAPE Volume(mL), SHAPE_Volume(vx), GLRLM_RLNU, NGLDM_Busyness and GLZLM_GLNU were all positively and significantly associated with HER2+; however, all of them were highly correlated. Radiomic features of CESM images could be helpful to predict particular molecular subtypes before a biopsy. [ABSTRACT FROM AUTHOR]

Simple Summary: Contrast-enhanced spectral mammography (CESM) represents a novel, reliable imaging adjunct for the early detection and management of breast lesions by coupling high sensitivity and specificity. Early diagnosis of breast tumors using this innovative diagnostic method could help in reducing the high number of unnecessary biopsies for breast lesions considered as suspicious by standard radiological examination (such as mammography, ultrasound, and magnetic resonance). Considering its relative recent introduction, there are still no standardized methods for assessing the diagnostic performance of CESM enhancement descriptors. Here, we aim to create a score that takes account four CESM enhancement descriptors able to efficiently predict the malignancy of a breast lesion prior to biopsy. Background: To create a predictive score of malignancy of a breast lesion based on the main contrast enhancement features ascertained by contrast-enhanced spectral mammography (CESM). Methods: In this single-centre prospective study, patients with suspicious breast lesions (BIRADS > 3) were enrolled between January 2013 and February 2022. All participants underwent CESM prior to breast biopsy, and eventually surgery. A radiologist with 20 years' experience in breast imaging evaluated the presence or absence of enhancement and the following enhancement descriptors: intensity, pattern, margin, and ground glass. A score of 0 or 1 was given for each descriptor, depending on whether the enhancement characteristic was predictive of benignity or malignancy (both in situ and invasive). Then, an overall enhancement score ranging from 0 to 4 was obtained. The histological results were considered the gold standard in the evaluation of the relationship between enhancement patterns and malignancy. Results: A total of 321 women (median age: 51 years; range: 22–83) with 377 suspicious breast lesions were evaluated. Two hundred forty-nine lesions (66%) have malignant histological results (217 invasive and 32 in situ). Considering an overall enhancement score ≥ 2 as predictive of malignancy, we obtain an overall sensitivity of 92.4%; specificity of 89.8%; positive predictive value of 94.7%; and negative predictive value of 85.8%. Conclusions: Our proposed predictive score on the enhancement descriptors of CESM to predict the malignancy of a breast lesion shows excellent results and can help in early breast cancer diagnosis and in avoiding unnecessary biopsies. [ABSTRACT FROM AUTHOR]

To evaluate if a computer-aided diagnosis (CAD) system on ultrasound (US) can improve the diagnostic performance of inexperienced radiologists. We collected ultrasound images of 256 breast lesions taken between March and May 2020. We asked two experienced and two inexperienced radiologists to retrospectively review the US features of each breast lesion according to the Breast Imaging Reporting and Data System (BI-RADS) categories. A CAD examination with S-Detect™ software (Samsung Healthcare, Seoul, South Korea) was conducted retrospectively by another uninvolved radiologist blinded to the BIRADS values previously attributed to the lesions. Diagnostic performances of experienced and inexperienced radiologists and CAD were compared and the inter-observer agreement among radiologists was calculated. The diagnostic performance of the experienced group in terms of sensitivity was significantly higher than CAD (p < 0.001). Conversely, the diagnostic performance of inexperienced group in terms of both sensitivity and specificity was significantly lower than CAD (p < 0.001). We obtained an excellent agreement in the evaluation of the lesions among the two expert radiologists (Kappa coefficient: 88.7%), and among the two non-expert radiologists (Kappa coefficient: 84.9%). The US CAD system is a useful additional tool to improve the diagnostic performance of the inexperienced radiologists, eventually reducing the number of unnecessary biopsies. Moreover, it is a valid second opinion in case of experienced radiologists. • Breast ultrasound (US) is an essential imaging tool for breast cancer detection in women with dense breast. • New generation ultrasound machines try to include software that can automatically evaluate the risk of malignancy. • Computer-aided diagnosis system on ultrasound can improve the diagnostic performance of inexperienced radiologists. [ABSTRACT FROM AUTHOR]

Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is a rare and newly recognized subtype of T cell Non-Hodgkin Lymphoma (NHLs) associated with breast implants. The mechanism involved in the development of this kind of lymphoma is still uncertain. BIA-ALCL is generally an indolent disease localized to the breast implant and its capsule and effectively treated with capsulectomy alone without chemotherapy. Clinically, BIA-ALCL may typically present a sudden-onset breast-swelling secondary to periimplant effusion. The minority of BIA-ALCL patients present a more aggressive mass-forming subtype, for which systemic therapy is mandatory. Despite the number of cases has recently increased, BIA-ALCL remains a rare disease described mainly in several case reports and small case series. Breast imaging, including mammography, ultrasound and breast MRI are routinely used in the screening of breast cancer; however, guidelines for the imaging and pathological diagnosis of this disease have only recently been proposed and included in the 2019 National Comprehensive Cancer Network (NCCN) consensus guidelines for BIA-ALCL. The main purpose of this pictorial is to illustrate the MRI signs of BIA-ALCL and correlate them with the corresponding pathology features in order to improve the knowledge of the principals MRI features of this type of lymphoma. [ABSTRACT FROM AUTHOR]

To assess a correlation between the shrinkage of the fibroid and the course of the symptoms. Fourteen patients with symptomatic uterine leiomyomas (mean fibroid volume: 111.45 cm3) underwent percutaneous microwave ablation. Contrast-enhanced MRI follow-up was performed before and after treatment to evaluate the volume shrinkage. Two scores obtained from the Uterine Fibroids Symptom and Quality of Life questionnaire were used to perform a clinical follow-up to evaluate the symptoms and the quality of life at baseline, and at 3, 6 and 12 months after treatment. All patients were treated, no complications occurred. During a mean MR follow-up of 8.1 months we observed shrinkage of the fibroids in all patients (mean 70.3 cm3). During 12 months clinical follow-up, we observed a significant improvement of symptoms and an excellent improvement of quality of life (p <.001). Uterine fibroids percutaneous microwave ablation is a safe tool to obtain a significant improvement in quality of life for all the patients of our cohort. [ABSTRACT FROM AUTHOR]

Simple Summary: Surgical management is currently the main standard of care procedure used in order to treat ductal carcinoma in situ (DCIS) of the breast. Nevertheless, the survival benefit of surgical resection in patients with such lesions appears to be low, especially for low-grade DCIS. Low-grade DCIS typically exhibit a slow growth pattern and, in many cases, never fully develop into a clinically significant disease: discerning harmless lesions from potentially invasive ones could lead to avoid overtreatment in many patients. Nonetheless, up to 26% of patients with biopsy-proven DCIS can reveal a synchronous invasive carcinoma in surgical specimens. Here, we aimed to create a model of radiological and pathological criteria able to reduce the underestimation of vacuum assisted breast biopsy in DCIS, identifying patients at very low risk (e.g., <2%) of diagnostic underestimation. Background: We aimed to create a model of radiological and pathological criteria able to predict the upgrade rate of low-grade ductal carcinoma in situ (DCIS) to invasive carcinoma, in patients undergoing vacuum-assisted breast biopsy (VABB) and subsequent surgical excision. Methods: A total of 3100 VABBs were retrospectively reviewed, among which we reported 295 low-grade DCIS who subsequently underwent surgery. The association between patients' features and the upgrade rate to invasive breast cancer (IBC) was evaluated by univariate and multivariate analysis. Finally, we developed a nomogram for predicting the upstage at surgery, according to the multivariate logistic regression model. Results: The overall upgrade rate to invasive carcinoma was 10.8%. At univariate analysis, the risk of upgrade was significantly lower in patients with greater age (p = 0.018), without post-biopsy residual lesion (p < 0.001), with a smaller post-biopsy residual lesion size (p < 0.001), and in the presence of low-grade DCIS only in specimens with microcalcifications (p = 0.002). According to the final multivariable model, the predicted probability of upstage at surgery was lower than 2% in 58 patients; among these 58 patients, only one (1.7%) upstage was observed, showing a good calibration of the model. Conclusions: An easy-to-use nomogram for predicting the upstage at surgery based on radiological and pathological criteria is able to identify patients with low-grade carcinoma in situ with low risk of upstaging to infiltrating carcinomas. [ABSTRACT FROM AUTHOR]

Introduction: Necrobiosis lipoidica (NL) is a rare chronic granulomatous dermatitis that usually appears in the lower extremities. It affects about 0.3-1.2% of diabetic patients, the majority of whom have type 1 diabetes. The etiology and pathogenesis of this disorder are still unclear. NL is characterized by skin rash that usually affects the shins. The average onset is 30 years, with females being affected more commonly. There are very few reported cases of necrobiosis lipoidica in children. Case report: We report a case of a 16 year old girl affected by type 1 diabetes mellitus (15 years disease duration) who developed an erythematous nodular rash on the lower extremities and interscapular area. In the suspect of necrobiosis lipoidica, a skin biopsy was performed (lower extremities and interscapular area). The microscopic evaluation of the pre-tibial lesions was suggestive of necrobiosis lipoidica. The smaller lesions in the interscapular area showed signs of perivascular dermatitis which could be consistent with early stages of necrobiosis lipoidica. Local treatment with tacrolimus determined a progressive improvement of the lesions. Conclusion: In patients with T1DM, diagnosis of NL of the lower legs is usually unequivocal. However, diagnosis may be more challenging in the presence of lesions with recent onset and/or atypical clinical presentation and unusual site. In these cases, NL must always be taken in consideration in order to avoid misdiagnosis, wrong/late treatment decisions and progression to ulceration. [ABSTRACT FROM AUTHOR]

Simple Summary: Interventional radiology image-guided locoregional therapies for the treatment of HCC have demonstrated to be characterized by immunomodulatory effects on the tumoral microenvironment, and, possibly, systemic. Immunotherapy has gained an important role in the treatment of HCC over the last several years. Currently, there is great interest in combining locoregional therapies with immunotherapy, as this could open a new chapter in the history of HCC treatment. In this review, after describing the immune system changes caused by the tumor, we describe, for each locoregional therapy, technique and immunomodulatory effects. Then, we describe the current status of immunotherapy in HCC and report the ongoing clinical studies testing the combination treatment. Image-guided locoregional therapies (LRTs) are a crucial asset in the treatment of hepatocellular carcinoma (HCC), which has proven to be characterized by an impaired antitumor immune status. LRTs not only directly destroy tumor cells but also have an immunomodulating role, altering the tumor microenvironment with potential systemic effects. Nevertheless, the immune activation against HCC induced by LRTs is not strong enough on its own to generate a systemic significant antitumor response, and it is incapable of preventing tumor recurrence. Currently, there is great interest in the possibility of combining LRTs with immunotherapy for HCC, as this combination may result in a mutually beneficial and synergistic relationship. On the one hand, immunotherapy could amplify and prolong the antitumoral immune response of LRTs, reducing recurrence cases and improving outcome. On the other hand, LTRs counteract the typical immunosuppressive HCC microenvironment and status and could therefore enhance the efficacy of immunotherapy. Here, after reviewing the current therapeutic options for HCC, we focus on LRTs, describing for each of them the technique and data on its effect on the immune system. Then, we describe the current status of immunotherapy and finally report the recently published and ongoing clinical studies testing this combination. [ABSTRACT FROM AUTHOR]

Simple Summary: The purpose of this study is to determine whether the combination assessment of DWI and T2WI improves the diagnostic ability for differential diagnosis of lung cancer from benign pulmonary nodules and masses (BPNMs). As using the OCV (1.470 × 10−3 mm2/s) for ADC, the sensitivity was 83.9% (220/262), the specificity 63.4% (33/52), and the accuracy 80.6% (253/314). As using the OCV (2.45) for T2 CR, the sensitivity was 89.7% (235/262), the specificity 61.5% (32/52), and the accuracy 85.0% (267/314). In 212 PNMs which were judged to be malignant by both DWI and T2WI, 203 PNMs (95.8%) were lung cancers. In 33 PNMs which were judged to be benign by both DWI and T2WI, 23 PNMs (69.7%) were BPNMs. The combined assessment of DWI and T2WI could judge PNMs more precisely and would be acceptable for differential diagnosis of PNMs. The purpose of this study is to determine whether the combination assessment of DWI and T2-weighted imaging (T2WI) improves the diagnostic ability for differential diagnosis of lung cancer from benign pulmonary nodules and masses (BPNMs). The optimal cut-off value (OCV) for differential diagnosis was set at 1.470 × 10−3 mm2/s for apparent diffusion coefficient (ADC), and at 2.45 for T2 contrast ratio (T2 CR). The ADC (1.24 ± 0.29 × 10−3 mm2/s) of lung cancer was significantly lower than that (1.69 ± 0.58 × 10−3 mm2/s) of BPNM. The T2 CR (2.01 ± 0.52) of lung cancer was significantly lower than that (2.74 ± 1.02) of BPNM. As using the OCV for ADC, the sensitivity was 83.9% (220/262), the specificity 63.4% (33/52), and the accuracy 80.6% (253/314). As using the OCV for T2 CR, the sensitivity was 89.7% (235/262), the specificity 61.5% (32/52), and the accuracy 85.0% (267/314). In 212 PNMs which were judged to be malignant by both DWI and T2WI, 203 PNMs (95.8%) were lung cancers. In 33 PNMs which were judged to be benign by both DWI and T2WI, 23 PNMs (69.7%) were BPNMs. The combined assessment of DWI and T2WI could judge PNMs more precisely and would be acceptable for differential diagnosis of PNMs. [ABSTRACT FROM AUTHOR]