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Lung cancer remains a global health challenge, leading to substantial morbidity and mortality. While prevention and early detection strategies have improved, the need for precise diagnosis, prognosis, and treatment remains crucial. In this comprehensive review article, we explore the role of artificial intelligence (AI) in reshaping the management of lung cancer. AI may have different potential applications in lung cancer characterization and outcome prediction. Manual segmentation is a time-consuming task, with high inter-observer variability, that can be replaced by AI-based approaches, including deep learning models such as U-Net, BCDU-Net, and others, to quantify lung nodules and cancers objectively and to extract radiomics features for the characterization of the tissue. AI models have also demonstrated their ability to predict treatment responses, such as immunotherapy and targeted therapy, by integrating radiomic features with clinical data. Additionally, AI-based prognostic models have been developed to identify patients at higher risk and personalize treatment strategies. In conclusion, this review article provides a comprehensive overview of the current state of AI applications in lung cancer management, spanning from segmentation and virtual biopsy to outcome prediction. The evolving role of AI in improving the precision and effectiveness of lung cancer diagnosis and treatment underscores its potential to significantly impact clinical practice and patient outcomes.

Introduction: Obstruction of the lacrimal drainage represents a common ophthalmologic issue. The blockage may interest any level of the lacrimal drainage pathway, and it is important to find the site of obstruction to plan the most appropriate treatment. In this study, findings from magnetic resonance (MR) dacryocystography were compared with findings from endoscopic and surgical procedures to evaluate the accuracy of MR dacryocystography in localizing the site of nasolacrimal duct obstruction., Methods: We enrolled twenty-one patients with clinical suspicion of nasolacrimal duct obstruction who underwent dacryoendoscopy and surgery. MR dacryocystography was performed with a heavily T2-weighted fast spin echo sequence in the coronal planes. Before the MRI was performed, a sterile 0.9% NaCl solution was administered into both conjunctival sacs. For each examination, two independent readers (with 8 and 10 years of experience in head and neck imaging) evaluated both heavily 3D space T2-weighted and STIR sequences., Results: Stenosis/obstruction of nasolacrimal duct or lacrimal sac was diagnosed in all 21 patients who underwent MRI dacryocystography. In particular, the site of the obstruction was classified as lacrimal sac in 12 (57%) patients, nasolacrimal duct in 6 (29%) patients, and canaliculi in 3 (14%) patients by both readers. By comparison with the evidence resulting from the endoscopy, there were differences between MRI dacryocystography and dacryoendoscopy in the evaluation of the obstruction's site in three patients, with an overall accuracy of 85.7%., Conclusion: MR dacryocystography allows a non-invasive evaluation of the lacrimal drainage pathway, valid for the planning of the most appropriate treatment.

The application of artificial intelligence (AI) is accelerating the paradigm shift towards patient-tailored brain tumor management, achieving optimal onco-functional balance for each individual. AI-based models can positively impact different stages of the diagnostic and therapeutic process. Although the histological investigation will remain difficult to replace, in the near future the radiomic approach will allow a complementary, repeatable and non-invasive characterization of the lesion, assisting oncologists and neurosurgeons in selecting the best therapeutic option and the correct molecular target in chemotherapy. AI-driven tools are already playing an important role in surgical planning, delimiting the extent of the lesion (segmentation) and its relationships with the brain structures, thus allowing precision brain surgery as radical as reasonably acceptable to preserve the quality of life. Finally, AI-assisted models allow the prediction of complications, recurrences and therapeutic response, suggesting the most appropriate follow-up. Looking to the future, AI-powered models promise to integrate biochemical and clinical data to stratify risk and direct patients to personalized screening protocols.

Due to its widespread availability, low cost, feasibility at the patient's bedside and accessibility even in low-resource settings, chest X-ray is one of the most requested examinations in radiology departments. Whilst it provides essential information on thoracic pathology, it can be difficult to interpret and is prone to diagnostic errors, particularly in the emergency setting. The increasing availability of large chest X-ray datasets has allowed the development of reliable Artificial Intelligence (AI) tools to help radiologists in everyday clinical practice. AI integration into the diagnostic workflow would benefit patients, radiologists, and healthcare systems in terms of improved and standardized reporting accuracy, quicker diagnosis, more efficient management, and appropriateness of the therapy. This review article aims to provide an overview of the applications of AI for chest X-rays in the emergency setting, emphasizing the detection and evaluation of pneumothorax, pneumonia, heart failure, and pleural effusion.

Abstract: Pseudolesions on contrast-enhanced computed tomography represent a diagnostic challenge for radiologists because they could be difficult to distinguish from true space-occupying lesions. This article aims to provide a detailed overview of these entities based on radiological criteria (hyperattenuation or hypoattenuation, localization, morphology), as well as a brief review of the hepatic vascular anatomy and pathophysiological process. Relevant examples from hospital case series are reported as helpful hints to assist radiologists in recognizing and correctly diagnosing these abnormalities., Competing Interests: The authors declare no conflict of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Lung cancer is one of the malignancies with higher morbidity and mortality. Imaging plays an essential role in each phase of lung cancer management, from detection to assessment of response to treatment. The development of imaging-based artificial intelligence (AI) models has the potential to play a key role in early detection and customized treatment planning. Computer-aided detection of lung nodules in screening programs has revolutionized the early detection of the disease. Moreover, the possibility to use AI approaches to identify patients at risk of developing lung cancer during their life can help a more targeted screening program. The combination of imaging features and clinical and laboratory data through AI models is giving promising results in the prediction of patients' outcomes, response to specific therapies, and risk for toxic reaction development. In this review, we provide an overview of the main imaging AI-based tools in lung cancer imaging, including automated lesion detection, characterization, segmentation, prediction of outcome, and treatment response to provide radiologists and clinicians with the foundation for these applications in a clinical scenario.

Orbital imaging plays a pivotal role in each hospital with an Ophthalmological Emergency Department. Unenhanced orbital computed tomography (CT) usually represents the first-line tool for the assessment of nontraumatic orbital emergencies, thanks to its quick execution, wide availability, high resolution, and availability of multiplanar reformats/reconstructions. Magnetic resonance imaging (MRI) is an essential tool that allows characterization and a better understanding of the anatomical involvement of different disorders due to its excellent contrast resolution and ability to study the visual pathways, even if, unfortunately, it is not always available in the emergency setting. It represents the first imaging choice in pediatric patients, due to the absence of ionizing radiation. When available, CT and MRI are often used together to diagnose, assess the extent, and provide treatment plans for various orbital nontraumatic emergencies, including infective, inflammatory, vascular, and neoplastic diseases. Familiarity with the imaging appearances of these disorders helps the radiologists to establish the correct diagnosis in the emergency setting, which contributes to timely clinical management. This pictorial essay provides a description of the clinical presentation and imaging findings of nontraumatic orbital emergencies., (© 2022. The Author(s), under exclusive licence to American Society of Emergency Radiology (ASER).)

Cancer-related secondary lymphedema (LE) is a widespread issue, which markedly affects patients' quality of life. Its diagnosis is mainly clinical since there is no consensus on the best imaging technique that should be used to assess this pathology. Even if lymphedema treatment has been traditionally conservative and mainly based on compressive bandages and decongestive therapy, new surgical techniques are proving their effectiveness in the management of the disease and made proper assessment and characterization of lymphedema necessary. In this scenario, non-contrast magnetic resonance lymphography (NCMRL) is acquiring an increasing role, as a non-invasive imaging technique, useful for the analysis of LE. NCMRL is an effective tool in diagnosis confirmation, in providing information about the structural changes of the affected limbs, in grading this disorder, and provides a guide for LE management and treatment planning. This article aims to provide an overview of the literature regarding this examination, analyzing the acquisition technique, the interpretation of the imaging findings and their usefulness, the advantages and limits of this technique, to help the radiologist approach this relatively new investigation in cases of cancer-related LE., (© 2021. Italian Society of Medical Radiology.)

Background: As survival from malignancies continues to improve, a greater emphasis is being placed on the quality of life after cancer treatments. Lymphedema (LE) represents a common and devastating sequela of neoplastic therapies, even if its incidence in patients submitted to lymphadenectomy for prostatic cancer is still poorly documented. The purpose of the current study was to analyze the imaging findings provided by noncontrast magnetic resonance (MR) lymphography in secondary lower limb LE related to prostate cancer therapies. Methods and Results: Patients with diagnosed secondary LE related to prostatic cancer treatment who underwent noncontrast MR lymphography (NCMRL) between November 2019 and February 2020 were assessed. Image datasets were retrospectively reviewed for the severity of lymphedema and characteristics of the subcutaneous tissue, muscular compartment appearance, number of iliac and inguinal lymphatics, and number of locoregional lymph nodes. Ten patients with 17 affected lower extremities, nine right extremities, and eight left extremities were included in our analysis. Magnetic resonance imaging grading was classified as one in four extremities, two in five extremities, and three in eight lower extremities. Honeycomb pattern was observed in 15 extremities, without significant correlation with MR grading ( p  = 0.684); dermal thickening showed correlation with MR grading ( p  < 0.001), as well as reduction of muscular trophism ( p  = 0.021). We observed a significant correlation between the number of inguinal lymph nodes and recognizable inguinal lymphatics ( p  = 0.039). Conclusion: NCMRL is able to provide useful information for the management of secondary lower limb LE caused by prostate cancer treatments. Clinical Trials.gov ID: n.2019/ST/187.

Ultrasound, chest X-ray, and computed tomography (CT) have been used with excellent results in diagnosis, first assessment, and follow-up of COVID-19 confirmed and suspected patients. Ultrasound and chest X-ray have the advantages of the wide availability and acquisition at the patient's bed; CT showed high sensitivity in COVID-19 diagnosis. Ground-glass opacities and consolidation are the main CT and X-ray features; the distribution of lung abnormalities is typically bilateral and peripheral. Less typical findings, including pleural effusion, mediastinal lymphadenopathies, the bubble air sign, and cavitation, can also be visible on chest CT. Radiologists should be aware of the advantages and limitations of the available imaging techniques and of the different pulmonary aspects of COVID-19 infection.

Background: Invasive imaging techniques have been applied for lymphedema (LE) assessment; noncontrast MR lymphography (NCMLR) has potential as an alternative, but its performance is not known in secondary lower limb LE., Purpose: To assess the role of NCMRL for the classification and characterization of secondary lower limb LE., Study Type: Retrospective., Population: Fifty adults with clinically diagnosed secondary LE., Field Strength/sequence: 1.5T, 3D T 2 -weighted turbo spin-echo, 3D T 2 -weighted turbo spin-echo short tau inversion recovery., Assessment: Three radiologists assessed the following characteristics on NCMRL: honeycomb pattern, dermal thickening, muscular abnormalities, distal dilated lymphatics, inguinal lymph node number, appearance of iliac lymphatic trunks. An LE grading based on the MR images was assigned. The relationship between imaging findings and clinical staging was evaluated, as well as between dermal backflow at lymphoscintigraphy and MR staging, and between the limb swelling duration and peripheral lymphatics dilatation., Statistical Tests: Pearson's correlation test and Cramer's V coefficient were computed to measure the strength of association. The Mann-Whitney test was used to compare the limb swelling duration between patients with and without dilated distal vessels. Agreement among raters was assessed through Kendall's W coefficient of correlation., Results: Clinical stage and the MR grading were correlated, with Cramer's V coefficient of 1 for reader 1 (P < 0.05), 0.846 for reader 2 (P < 0.05), and 0.912 (P < 0.05) for reader 3; agreement between interraters was very good (W = 0.0.75; P = 0.05). A honeycomb pattern (P < 0.05), dermal thickening (P < 0.001), muscular abnormalities (P < 0.05), iliac lymphatic trunks appearance (P < 0.05), distal dilated vessels (P < 0.05), and lymph nodes number (P < 0.05) were significantly correlated with LE clinical stage. Dermal backflow at lymphoscintigraphy was described in 10 (20%) patients and showed a significant correlation with the MR grading (P < 0.05)., Data Conclusion: These preliminary results suggest that NCMRL may provide information useful for the staging and management of patients affected by secondary lower limb LE. Level of Evidence 4 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2021;53:458-466., (© 2020 International Society for Magnetic Resonance in Medicine.)

Lymphedema (LE) is a progressive chronic disorder, frequently related to malignancies and their treatment in Western countries. It markedly affected patients' quality of life, and its management is challenging, mainly based on conservative therapy, as bandages and manual lymphatic drainage, with limited results.Recent advances in imaging technology and microsurgical techniques have changed the approach to this disorder, particularly the recent application of magnetic resonance for the study of LE and the increasingly widespread use of surgical interventions, such as vascularized lymph node transfer. As secondary LE due to radical prostatectomy and/or radiation treatment is a frequent cause of chronic disability in the male population, and few data are available in literature about which imaging technique can be applied to diagnose it and about the surgical modalities to treat this condition, we want to propose an overview on the lymphatic vessels anatomy and function, on the applications of noncontrast magnetic resonance lymphangiography and about the pieces of information this examination can provide, and on the technique of vascularized lymph node transfer and the rationale of this surgical procedure in secondary LE related to prostatic malignancy treatment.

Aim: To report our experience on CT investigation of animal mummies, focusing on the practical and radiological aspects of the study, the acquisition parameters and the different reconstruction techniques., Materials and Methods: Thirteen mummies underwent CT examination on the same CT scanner (Siemens sensation) with the following acquisition parameters: 120 kV; 140 mAs; slice thickness: 1 mm; reconstruction interval: 0.7 mm; and rotation time: 0.75 s. All datasets were reconstructed with both bone and soft tissue algorithms and archived on our picture archiving and communication system using their catalogue number as an identifier. Images were then transferred on IntelliSpace Portal (Philips Healthcare) for post-processing multiplanar and 3D reconstructions. The acquired data were submitted to anthropological analysis., Results: CT enabled the identification of the bundles content: four cats with complete skeleton, one upper part of a cat mummy, one lower part of a cat mummy, one cat head with four cervical vertebrae, two crocodiles, two raptors, skeletons from one or more snakes and one mummy with dog appearance, containing long bones. All cats and hawks showed cervical fractures; in one cat, the skull was collapsed inwards, and in another cat, the head was turned backwards; one cat presented a skeleton more radiopaque than normal with evidence of cracks related to the use of the resins for mummification that were poured directly over the corpse., Conclusions: CT is a valuable noninvasive technique to study Egyptian mummies, enabling in-depth analysis while preserving the integrity of the mummy bundles, ensuring protection of a valuable archaeological resource.

Aim: To assess imaging findings and characteristics of the lymphatic system in patients affected by lipedema and lipolymphedema of the lower extremities on Non-Contrast MR Lymphography (NCMRL)., Materials and Methods: 44 lower extremities in 11 consecutive female patients affected by lipedema, and 11 patients with lipolymphedema were examined by NCMRL. MR imaging was performed on 1.5-T system MR equipment. The examination consisted of one 3D short-tau inversion recovery (STIR) and one heavily T2-weighted 3D-Turbo Spin Echo (TSE) sequence., Results: All patients showed symmetrical enlargement of the lower extremities with increased subcutaneous fat tissue. The fat tissue was homogeneous, without any signs of edema in pure lipedema patients. In all the extremities with lipolymphedema, high signal intensity areas in the epifascial region could be detected on the 3D-TSE sequence (p < .001) with evidence of mild epifascial fluid collections (p < .001). No sign of honeycomb pattern fat appearance was observed. The appearance of the iliac lymphatic trunks was normal in both lipedema and lipolymphedema patients. Dilated peripheral lymphatics were observed in 2 patients affected by lipedema, indicating a subclinical status of lymphedema, and in 10 patients with lipolymphedema (p = .001). Signs of vascular stasis were observed in both groups, without statistically significant difference (p = .665)., Conclusion: NCMRL is a non-invasive imaging technique that is suitable for the evaluation of patients affected by lipedema and lipolymphedema, helping in the differential diagnosis., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Purpose: Sphenoid sinuses are pneumatised structures, placed in the body of the sphenoid bone, with highly variable morphology. The strict relationships with vascular and nervous structures determine the importance of their anatomical variants in otorhinolaryngology and neurosurgery; a precise understanding of the complex anatomy and anatomic variations of these structures is pivotal for radiological diagnosis of paranasal sinuses pathology and for surgical planning, to avoid potential complications. Our aim is to describe the anatomical variants of sphenoid sinuses, and to help general radiologists and specialists in endoscopic surgery in becoming familiar with these sensitive anatomical structures., Methods: A literature search of PubMed and Embase (Elsevier) databases was performed using the keywords "sphenoid sinus" and "anatomy, "sphenoid sinus" and "anatomic variants", "sphenoid sinus", and "anatomic variations"., Results: We described the anatomical variants of the sphenoid sinuses anatomy, according to their size, shape, degree of pneumatisation, protrusion of anatomical structures into their lumen, superimposition of ethmoid cells (Onodi cells), and presence of accessory septations CONCLUSION: The information provided by this study may help in the identification and description of the anatomical variations of the sphenoid sinuses and their relationship to neurovascular structures.

Purpose: Leakage of the gastric remnant after laparoscopic sleeve gastrectomy (LSG) represents an unpredictable, dreadful occurrence. Our aim was to assess whether routine postoperative CT scan is an effective tool for early prediction of leakage after LSG., Materials and Methods: From a prospectively acquired database, all consecutive patients who underwent LSG between January 2015 and December 2018 were identified; within this database, all patients who were evaluated with at least one contrast-enhanced CT scan within 48 h from surgery were enrolled in this retrospective study. The selected CT findings included twisting of the gastric remnant, perigastric air bubbles, and hematoma; the antral segment proximal from the pylorus to the first staple firing was also analyzed in terms of distance (StP, stapler to pylorus distance) and linearity (LI, linearity index)., Results: After exclusions, 250 patients were included; 10 patients suffered from gastric leakage. Patients with perigastric hematoma and/or twisting of the distal part of the gastric remnant on routine postoperative CT scan were found to be more likely to develop leakage after LSG (p = 0.005 and p < 0.001, respectively). The mean StP was 45 ± 19.1 mm; the mean LI was 1.54 ± 0.4. Patients with subsequent development of leakage had significantly lower StP (26.7 ± 12.5 mm vs. 45.9 ± 18.9 mm; p = 0.001) and LI values (1.16 ± 0.11 vs. 1.55 ± 0.39; p = 0.002)., Conclusion: Routine postoperative CT scan after LSG permits early stratification of leakage risk, thus providing an actual aid for patients' management.

Background: National health-system hospitals of Lombardy faced a heavy burden of admissions for acute respiratory distress syndromes associated with coronavirus disease (COVID-19). Data on patients of European origin affected by COVID-19 are limited., Methods: All consecutive patients aged ≥18 years, coming from North-East of Milan's province and admitted at San Raffaele Hospital with COVID-19, between February 25th and March 24th, were reported, all patients were followed for at least one month. Clinical and radiological features at admission and predictors of clinical outcomes were evaluated., Results: Of the 500 patients admitted to the Emergency Unit, 410 patients were hospitalized and analyzed: median age was 65 (IQR 56-75) years, and the majority of patients were males (72.9%). Median (IQR) days from COVID-19 symptoms onset was 8 (5-11) days. At hospital admission, fever (≥ 37.5 °C) was present in 67.5% of patients. Median oxygen saturation (SpO2) was 93% (range 60-99), with median PaO 2 /FiO 2 ratio, 267 (IQR 184-314). Median Radiographic Assessment of Lung Edema (RALE) score was 9 (IQR 4-16). More than half of the patients (56.3%) had comorbidities, with hypertension, coronary heart disease, diabetes and chronic kidney failure being the most common. The probability of overall survival at day 28 was 66%. Multivariable analysis showed older age, coronary artery disease, cancer, low lymphocyte count and high RALE score as factors independently associated with an increased risk of mortality., Conclusion: In a large cohort of COVID-19 patients of European origin, main risk factors for mortality were older age, comorbidities, low lymphocyte count and high RALE., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)