Preliminary data on artificial intelligence tool in magnetic resonance imaging assessment of degenerative pathologies of lumbar spine.

PURPOSE: To evaluate the ability of an artificial intelligence (AI) tool in magnetic resonance imaging (MRI) assessment of degenerative pathologies of lumbar spine using radiologist evaluation as a gold standard. METHODS: Patients with degenerative pathologies of lumbar spine, evaluated with MRI study, were enrolled in a retrospective study approved by local ethical committee. A comprehensive software solution (CoLumbo; SmartSoft Ltd., Varna, Bulgaria) designed to label the segments of the lumbar spine and to detect a broad spectrum of degenerative pathologies based on a convolutional neural network (CNN) was employed, utilizing an automatic segmentation. The AI tool efficacy was compared to data obtained by a senior neuroradiologist that employed a semiquantitative score. Chi-square test was used to assess the differences among groups, and Spearman's rank correlation coefficient was calculated between the grading assigned by radiologist and the grading obtained by software. Moreover, agreement was assessed between the value assigned by radiologist and software. RESULTS: Ninety patients (58 men; 32 women) affected with degenerative pathologies of lumbar spine and aged from 60 to 81 years (mean 66 years) were analyzed. Significant correlations were observed between grading assigned by radiologist and the grading obtained by software for each localization. However, only when the localization was L2-L3, there was a good correlation with a coefficient value of 0.72. The best agreements were obtained in case of L1-L2 and L2-L3 localizations and were, respectively, of 81.1% and 72.2%. The lowest agreement of 51.1% was detected in case of L4-L5 locations. With regard canal stenosis and compression, the highest agreement was obtained for identification of in L5-S1 localization. CONCLUSIONS: AI solution represents an efficacy and useful toll degenerative pathologies of lumbar spine to improve radiologist workflow.

Low dialysate sodium in children and young adults on maintenance hemodialysis: a prospective, randomized, crossover study.

BACKGROUND: The optimal dialysate sodium concentration (dNa) in children on hemodialysis (HD) is unknown. The aim of this study was to compare the effect on interdialytic weight gain (IDWG) and blood pressure (BP) of a low (135 mmol/l) and standard dNa (138 mmol/l) in children and young adults on maintenance HD. METHODS: This prospective single-blind randomized crossover study consisted of a randomized sequence of two phases: "standard dNa" of 138 mmol/L and "low dNa" of 135 mmol/L. Each phase lasted 4 weeks. Inclusion criteria were age < 25 years, hypertension, pre-HD serum Na (sNa) ≥ 130 mmol/L, and occurrence of symptoms in less than 25% of sessions. Primary outcomes were pre-HD systolic and diastolic BP and IDWG. RESULTS: Fifteen patients were recruited, mean age 17.8 ± 4.4 years. Pre-HD SBP and DBP were not different between the two treatments. Mean IDWG was significantly lower with low dNa than with standard dNa: 2.12 ± 1.39% vs. 2.77 ± 1.53%, respectively (p = 0.008). The first-hour refill index (a volume index based on blood-volume monitoring) was significantly lower with dNa 135 mmol/L (p = 0.018). The mean Na gradient (dNa-sNa) was - 2.53 ± 2.4 mmol/L with dNa 135 mmol/L and 0.17 ± 2.8 mmol/L with dNa 138 mmol/L (p = 0.0001). The incidence of symptomatic sessions was similar (1.0% vs. 1.0%). CONCLUSIONS: In a selected population of hypertensive pediatric and young adult HD patients, a dNa of 135 mmol/L was associated with a significant reduction of IDWG compared with a dNa of 138 mmol/L. Furthermore, long-term studies are needed to investigate the effect of lowering dNa on BP. A higher resolution version of the Graphical abstract is available as Supplementary information.

Structured reporting of computed tomography in the polytrauma patient assessment: a Delphi consensus proposal.

OBJECTIVES: To develop a structured reporting (SR) template for whole-body CT examinations of polytrauma patients, based on the consensus of a panel of emergency radiology experts from the Italian Society of Medical and Interventional Radiology. METHODS: A multi-round Delphi method was used to quantify inter-panelist agreement for all SR sections. Internal consistency for each section and quality analysis in terms of average inter-item correlation were evaluated by means of the Cronbach's alpha (Cα) correlation coefficient. RESULTS: The final SR form included 118 items (6 in the "Patient Clinical Data" section, 4 in the "Clinical Evaluation" section, 9 in the "Imaging Protocol" section, and 99 in the "Report" section). The experts' overall mean score and sum of scores were 4.77 (range 1-5) and 257.56 (range 206-270) in the first Delphi round, and 4.96 (range 4-5) and 208.44 (range 200-210) in the second round, respectively. In the second Delphi round, the experts' overall mean score was higher than in the first round, and standard deviation was lower (3.11 in the second round vs 19.71 in the first round), reflecting a higher expert agreement in the second round. Moreover, Cα was higher in the second round than in the first round (0.97 vs 0.87). CONCLUSIONS: Our SR template for whole-body CT examinations of polytrauma patients is based on a strong agreement among panel experts in emergency radiology and could improve communication between radiologists and the trauma team.

Comparison between two packages for pectoral muscle removal on mammographic images.

BACKGROUND: Pectoral muscle removal is a fundamental preliminary step in computer-aided diagnosis systems for full-field digital mammography (FFDM). Currently, two open-source publicly available packages (LIBRA and OpenBreast) provide algorithms for pectoral muscle removal within Matlab environment. PURPOSE: To compare performance of the two packages on a single database of FFDM images. METHODS: Only mediolateral oblique (MLO) FFDM was considered because of large presence of pectoral muscle on this type of projection. For obtaining ground truth, pectoral muscle has been manually segmented by two radiologists in consensus. Both LIBRA's and OpenBreast's removal performance with respect to ground truth were compared using Dice similarity coefficient and Cohen-kappa reliability coefficient; Wilcoxon signed-rank test has been used for assessing differences in performances; Kruskal-Wallis test has been used to verify possible dependence of the performance from the breast density or image laterality. RESULTS: FFDMs from 168 consecutive women at our institution have been included in the study. Both LIBRA's Dice-index and Cohen-kappa were significantly higher than OpenBreast (Wilcoxon signed-rank test P < 0.05). No dependence on breast density or laterality has been found (Kruskal-Wallis test P > 0.05). CONCLUSION: Libra has a better performance than OpenBreast in pectoral muscle delineation so that, although our study has not a direct clinical application, these results are useful in the choice of packages for the development of complex systems for computer-aided breast evaluation.

Radiomics textural features by MR imaging to assess clinical outcomes following liver resection in colorectal liver metastases.

PURPOSE: To assess the efficacy of radiomics features obtained by T2-weighted sequences to predict clinical outcomes following liver resection in colorectal liver metastases patients. METHODS: This retrospective analysis was approved by the local Ethical Committee board and radiological databases were interrogated, from January 2018 to May 2021, to select patients with liver metastases with pathological proof and MRI study in pre-surgical setting. The cohort of patients included a training set and an external validation set. The internal training set included 51 patients with 61 years of median age and 121 liver metastases. The validation cohort consisted a total of 30 patients with single lesion with 60 years of median age. For each volume of interest, 851 radiomics features were extracted as median values using PyRadiomics. Nonparametric test, intraclass correlation, receiver operating characteristic (ROC) analysis, linear regression modelling and pattern recognition methods (support vector machine (SVM), k-nearest neighbours (KNN), artificial neural network (NNET) and decision tree (DT)) were considered. RESULTS: The best predictor to discriminate expansive versus infiltrative front of tumour growth was obtained by wavelet_LHL_gldm_DependenceNonUniformityNormalized with an accuracy of 82%; to discriminate high grade versus low grade or absent was the wavelet_LLH_glcm_Imc1 with accuracy of 88%; to differentiate the mucinous type of tumour was the wavelet_LLH_glcm_JointEntropy with accuracy of 92% while to identify tumour recurrence was the wavelet_LLL_glcm_Correlation with accuracy of 85%. Linear regression model increased the performance obtained with respect to the univariate analysis exclusively in the discrimination of expansive versus infiltrative front of tumour growth reaching an accuracy of 90%, a sensitivity of 95% and a specificity of 80%. Considering significant texture metrics tested with pattern recognition approaches, the best performance was reached by the KNN in the discrimination of the tumour budding considering the four textural predictors obtaining an accuracy of 93%, a sensitivity of 81% and a specificity of 97%. CONCLUSIONS: Ours results confirmed the capacity of radiomics to identify as biomarkers, several prognostic features that could affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach.

Radiomics and machine learning analysis based on magnetic resonance imaging in the assessment of liver mucinous colorectal metastases.

PURPOSE: The purpose of this study is to evaluate the Radiomics and Machine Learning Analysis based on MRI in the assessment of Liver Mucinous Colorectal Metastases.Query METHODS: The cohort of patients included a training set (121 cases) and an external validation set (30 cases) with colorectal liver metastases with pathological proof and MRI study enrolled in this approved study retrospectively. About 851 radiomics features were extracted as median values by means of the PyRadiomics tool on volume on interest segmented manually by two expert radiologists. Univariate analysis, linear regression modelling and pattern recognition methods were used as statistical and classification procedures. RESULTS: The best results at univariate analysis were reached by the wavelet_LLH_glcm_JointEntropy extracted by T2W SPACE sequence with accuracy of 92%. Linear regression model increased the performance obtained respect to the univariate analysis. The best results were obtained by a linear regression model of 15 significant features extracted by the T2W SPACE sequence with accuracy of 94%, a sensitivity of 92% and a specificity of 95%. The best classifier among the tested pattern recognition approaches was k-nearest neighbours (KNN); however, KNN achieved lower precision than the best linear regression model. CONCLUSIONS: Radiomics metrics allow the mucinous subtype lesion characterization, in order to obtain a more personalized approach. We demonstrated that the best performance was obtained by T2-W extracted textural metrics.

Ca2+-activated K+ channels modulate microglia affecting motor neuron survival in hSOD1G93A mice.

Recent studies described a critical role for microglia in amyotrophic lateral sclerosis (ALS), where these CNS-resident immune cells participate in the establishment of an inflammatory microenvironment that contributes to motor neuron degeneration. Understanding the mechanisms leading to microglia activation in ALS could help to identify specific molecular pathways which could be targeted to reduce or delay motor neuron degeneration and muscle paralysis in patients. The intermediate-conductance calcium-activated potassium channel KCa3.1 has been reported to modulate the "pro-inflammatory" phenotype of microglia in different pathological conditions. We here investigated the effects of blocking KCa3.1 activity in the hSOD1G93AALS mouse model, which recapitulates many features of the human disease. We report that treatment of hSOD1G93A mice with a selective KCa3.1 inhibitor, 1-[(2-chlorophenyl)diphenylmethyl]-1H-pyrazole (TRAM-34), attenuates the "pro-inflammatory" phenotype of microglia in the spinal cord, reduces motor neuron death, delays onset of muscle weakness, and increases survival. Specifically, inhibition of KCa3.1 channels slowed muscle denervation, decreased the expression of the fetal acetylcholine receptor γ subunit and reduced neuromuscular junction damage. Taken together, these results demonstrate a key role for KCa3.1 in driving a pro-inflammatory microglia phenotype in ALS.

Cord blood platelet gel for the treatment of inherited epidermolysis bullosa.

The management of patients affected by epidemolysis bullosa requires an integrated approach involving different specialties. A cornerstone of clinical management is the prevention and treatment of mechanobullous ulcerations of the patient's skin, which significantly impact the quality of life and can be the cause of septic and neoplatic complications. This article describes the preliminary clinical evaluation of the use of allogeneic cord blood platelet gel, a novel blood component obtained from umbilical cord blood of healthy, term neonates, for the treatment of skin ulcers in patients with dystrophic epidermolysis bullosa. The promising clinical results obtained in this small patient group support the development of larger controlled clinical trials to compare the efficacy of platelet gel obtained from cord blood versus traditional platelet gel prepared from adult blood donors and versus current standard approaches of wound care in these patients.

Fluoxetine prevents acetylcholine-induced excitotoxicity blocking human endplate acetylcholine receptor.

INTRODUCTION: Fluoxetine is an open channel blocker of fetal muscle acetylcholine (ACh) receptor (AChR) and slow-channel mutant AChRs. It is used commonly to treat patients with slow-channel congenital myasthenic syndromes. Fluoxetine effects on adult wild-type endplate AChR are less characterized, although muscle AChR isoforms are differentially modulated by some drugs. METHODS: Excitotoxicity assays and patch clamp recordings were performed in human embryonic kidney 293 (HEK) cells expressing wild-type or slow-channel mutant human AChRs. RESULTS: Fluoxetine (2-10 µM) abolished ACh-induced death and decreased ACh-activated whole-cell currents in cells expressing all AChR types. In outside-out patches, fluoxetine rapidly curtailed ACh evoked unitary activity and macroscopic currents. The effect was increased if fluoxetine was applied before ACh. CONCLUSIONS: Fluoxetine is an open channel blocker, but it also affects AChR in the closed state. AChR blockade likely underlies the rescue of HEK cells from ACh-induced death.

Physiological characterization of human muscle acetylcholine receptors from ALS patients.

Amyotrophic lateral sclerosis (ALS) is characterized by progressive degeneration of motor neurons leading to muscle paralysis. Research in transgenic mice suggests that the muscle actively contributes to the disease onset, but such studies are difficult to pursue in humans and in vitro models would represent a good starting point. In this work we show that tiny amounts of muscle from ALS or from control denervated muscle, obtained by needle biopsy, are amenable to functional characterization by two different technical approaches: "microtransplantation" of muscle membranes into Xenopus oocytes and culture of myogenic satellite cells. Acetylcholine (ACh)-evoked currents and unitary events were characterized in oocytes and multinucleated myotubes. We found that ALS acetylcholine receptors (AChRs) retain their native physiological characteristics, being activated by ACh and nicotine and blocked by α-bungarotoxin (α-BuTX), d-tubocurarine (dTC), and galantamine. The reversal potential of ACh-evoked currents and the unitary channel behavior were also typical of normal muscle AChRs. Interestingly, in oocytes injected with muscle membranes derived from ALS patients, the AChRs showed a significant decrease in ACh affinity, compared with denervated controls. Finally, riluzole, the only drug currently used against ALS, reduced, in a dose-dependent manner, the ACh-evoked currents, indicating that its action remains to be fully characterized. The two methods described here will be important tools for elucidating the role of muscle in ALS pathogenesis and for developing drugs to counter the effects of this disease.

Gross hematuria: Renal cell carcinoma mimicking a renal arteriovenous malformation.

The differential diagnosis between renal arteriovenous malformations (AVM) and cancer may be a challenge, due to the similar clinical and imaging findings. Herein, we report the case of an 80-year-old male patient presenting gross hematuria, initially diagnosed and treated with embolization for a renal AVM. Due to the recurrence of hematuria and rapid progression and changes of the vascular lesion with detection also of an intralesional solid nodule, a radical nephrectomy was performed revealing the presence of a renal cell carcinoma (RCC). Renal cell carcinoma and renal AVM can be difficult to differentiate from one another, for this reason a short-term follow-up should be carried out in patients diagnosed and treated for renal AVM to confirm the resolution of AVM or to assess any changes, such as atypical neovascularization or intralesional renal masses, which may increase the suspect of a hidden renal tumor.

Associations between Radiomics and Genomics in Non-Small Cell Lung Cancer Utilizing Computed Tomography and Next-Generation Sequencing: An Exploratory Study.

BACKGROUND: Radiomics, an evolving paradigm in medical imaging, involves the quantitative analysis of tumor features and demonstrates promise in predicting treatment responses and outcomes. This study aims to investigate the predictive capacity of radiomics for genetic alterations in non-small cell lung cancer (NSCLC). METHODS: This exploratory, observational study integrated radiomic perspectives using computed tomography (CT) and genomic perspectives through next-generation sequencing (NGS) applied to liquid biopsies. Associations between radiomic features and genetic mutations were established using the Area Under the Receiver Operating Characteristic curve (AUC-ROC). Machine learning techniques, including Support Vector Machine (SVM) classification, aim to predict genetic mutations based on radiomic features. The prognostic impact of selected gene variants was assessed using Kaplan-Meier curves and Log-rank tests. RESULTS: Sixty-six patients underwent screening, with fifty-seven being comprehensively characterized radiomically and genomically. Predominantly males (68.4%), adenocarcinoma was the prevalent histological type (73.7%). Disease staging is distributed across I/II (38.6%), III (31.6%), and IV (29.8%). Significant correlations were identified with mutations of ROS1 p.Thr145Pro (shape_Sphericity), ROS1 p.Arg167Gln (glszm_ZoneEntropy, firstorder_TotalEnergy), ROS1 p.Asp2213Asn (glszm_GrayLevelVariance, firstorder_RootMeanSquared), and ALK p.Asp1529Glu (glcm_Imc1). Patients with the ROS1 p.Thr145Pro variant demonstrated markedly shorter median survival compared to the wild-type group (9.7 months vs. not reached, p = 0.0143; HR: 5.35; 95% CI: 1.39-20.48). CONCLUSIONS: The exploration of the intersection between radiomics and cancer genetics in NSCLC is not only feasible but also holds the potential to improve genetic predictions and enhance prognostic accuracy.

Diagnostic Management of Gastroenteropancreatic Neuroendocrine Neoplasms: Technique Optimization and Tips and Tricks for Radiologists.

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) comprise a heterogeneous group of neoplasms, which derive from cells of the diffuse neuroendocrine system that specializes in producing hormones and neuropeptides and arise in most cases sporadically and, to a lesser extent, in the context of complex genetic syndromes. Furthermore, they are primarily nonfunctioning, while, in the case of insulinomas, gastrinomas, glucagonomas, vipomas, and somatostatinomas, they produce hormones responsible for clinical syndromes. The GEP-NEN tumor grade and cell differentiation may result in different clinical behaviors and prognoses, with grade one (G1) and grade two (G2) neuroendocrine tumors showing a more favorable outcome than grade three (G3) NET and neuroendocrine carcinoma. Two critical issues should be considered in the NEN diagnostic workup: first, the need to identify the presence of the tumor, and, second, to define the primary site and evaluate regional and distant metastases. Indeed, the primary site, stage, grade, and function are prognostic factors that the radiologist should evaluate to guide prognosis and management. The correct diagnostic management of the patient includes a combination of morphological and functional evaluations. Concerning morphological evaluations, according to the consensus guidelines of the European Neuroendocrine Tumor Society (ENETS), computed tomography (CT) with a contrast medium is recommended. Contrast-enhanced magnetic resonance imaging (MRI), including diffusion-weighted imaging (DWI), is usually indicated for use to evaluate the liver, pancreas, brain, and bones. Ultrasonography (US) is often helpful in the initial diagnosis of liver metastases, and contrast-enhanced ultrasound (CEUS) can solve problems in characterizing the liver, as this tool can guide the biopsy of liver lesions. In addition, intraoperative ultrasound is an effective tool during surgical procedures. Positron emission tomography (PET-CT) with FDG for nonfunctioning lesions and somatostatin analogs for functional lesions are very useful for identifying and evaluating metabolic receptors. The detection of heterogeneity in somatostatin receptor (SSTR) expression is also crucial for treatment decision making. In this narrative review, we have described the role of morphological and functional imaging tools in the assessment of GEP-NENs according to current major guidelines.

Traumatic segmental renal infarction due to renal apical artery thrombosis by minor blunt abdominal trauma: the role of CEUS.

Post-traumatic segmental renal infarction is an extremely rare event, especially in case of minor blunt abdominal trauma. While major trauma guidelines are well established, several problems account for the adequate management of minor trauma. Herein, we report a case of minor blunt abdominal trauma determining traumatic thrombosis of the apical renal artery and segmental renal infarction, firstly diagnosed by CEUS in emergency care setting.

Gunshot vaginal trauma.

Nonobstetric vaginal or vulva trauma is an extremely rare occurrence, with an incidence of < 0.2% of traumas. CT represents the gold standard in the diagnosis of gunshot lesions due to its ability to detect and stage injuries with very high sensitivity and specificity. A standardized protocol for penetrating trauma is still under debate for the use of intravenous contrast only or also rectal and oral contrast. Herein, we report a case of gunshot vaginal trauma in a 43-year-old patient presenting with vaginal bleeding. In our case, the protocol was "patient's tailored," the intravaginal selective use of air was administered due to symptoms (vaginal bleeding) and CT findings, this 2-step protocol increased diagnostic confidence and allow a correct and challenging diagnosis.

Percutanous Electrochemotherapy (ECT) in Primary and Secondary Liver Malignancies: A Systematic Review.

The aim of the study was to analyse papers describing the use of Electrochemotherapy (ECT) in local treatment of primary and secondary liver tumours located at different sites and with different histologies. Other Local Ablative Therapies (LAT) are also discussed. Analyses of these papers demonstrate that ECT use is safe and effective in lesions of large size, independently of the histology of the treated lesions. ECT performed better than other thermal ablation techniques in lesions > 6 cm in size and can be safely used to treat lesions distant, close, or adjacent to vital structures. ECT spares vessel and bile ducts, is repeatable, and can be performed between chemotherapeutic cycles. ECT can fill the gap in local ablative therapies due to being lesions too large or localized in highly challenging anatomical sites.

Qualitative and semi-quantitative ultrasound assessment in delta and Omicron Covid-19 patients: data from high volume reference center.

OBJECTIVE: to evaluate the efficacy of US, both qualitatively and semi-quantitatively, in the selection of treatment for the Covid-19 patient, using patient triage as the gold standard. METHODS: Patients admitted to the Covid-19 clinic to be treated with monoclonal antibodies (mAb) or retroviral treatment and undergoing lung ultrasound (US) were selected from the radiological data set between December 2021 and May 2022 according to the following inclusion criteria: patients with proven Omicron variant and Delta Covid-19 infection; patients with known Covid-19 vaccination with at least two doses. Lung US (LUS) was performed by experienced radiologists. The presence, location, and distribution of abnormalities, such as B-lines, thickening or ruptures of the pleural line, consolidations, and air bronchograms, were evaluated. The anomalous findings in each scan were classified according to the LUS scoring system. Nonparametric statistical tests were performed. RESULTS: The LUS score median value in the patients with Omicron variant was 1.5 (1-20) while the LUS score median value in the patients with Delta variant was 7 (3-24). A difference statistically significant was observed for LUS score values among the patients with Delta variant between the two US examinations (p value = 0.045 at Kruskal Wallis test). There was a difference in median LUS score values between hospitalized and non-hospitalized patients for both the Omicron and Delta groups (p value = 0.02 on the Kruskal Wallis test). For Delta patients groups the sensitivity, specificity, positive and negative predictive values, considering a value of 14 for LUS score for the hospitalization, were of 85.29%, 44.44%, 85.29% and 76.74% respectively. CONCLUSIONS: LUS is an interesting diagnostic tool in the context of Covid-19, it could allow to identify the typical pattern of diffuse interstitial pulmonary syndrome and could guide the correct management of patients.

Machine Learning Approaches with Textural Features to Calculate Breast Density on Mammography.

BACKGROUND: breast cancer (BC) is the world's most prevalent cancer in the female population, with 2.3 million new cases diagnosed worldwide in 2020. The great efforts made to set screening campaigns, early detection programs, and increasingly targeted treatments led to significant improvement in patients' survival. The Full-Field Digital Mammograph (FFDM) is considered the gold standard method for the early diagnosis of BC. From several previous studies, it has emerged that breast density (BD) is a risk factor in the development of BC, affecting the periodicity of screening plans present today at an international level. OBJECTIVE: in this study, the focus is the development of mammographic image processing techniques that allow the extraction of indicators derived from textural patterns of the mammary parenchyma indicative of BD risk factors. METHODS: a total of 168 patients were enrolled in the internal training and test set while a total of 51 patients were enrolled to compose the external validation cohort. Different Machine Learning (ML) techniques have been employed to classify breasts based on the values of the tissue density. Textural features were extracted only from breast parenchyma with which to train classifiers, thanks to the aid of ML algorithms. RESULTS: the accuracy of different tested classifiers varied between 74.15% and 93.55%. The best results were reached by a Support Vector Machine (accuracy of 93.55% and a percentage of true positives and negatives equal to TPP = 94.44% and TNP = 92.31%). The best accuracy was not influenced by the choice of the features selection approach. Considering the external validation cohort, the SVM, as the best classifier with the 7 features selected by a wrapper method, showed an accuracy of 0.95, a sensitivity of 0.96, and a specificity of 0.90. CONCLUSIONS: our preliminary results showed that the Radiomics analysis and ML approach allow us to objectively identify BD.

Radiation Recall Pneumonitis: The Open Challenge in Differential Diagnosis of Pneumonia Induced by Oncological Treatments.

The treatment of primary and secondary lung neoplasms now sees the fundamental role of radiotherapy, associated with surgery and systemic therapies. The improvement in survival outcomes has also increased attention to the quality of life, treatment compliance and the management of side effects. The role of imaging is not only limited to recognizing the efficacy of treatment but also to identifying, as soon as possible, the uncommon effects, especially when more treatments, such as chemotherapy, immunotherapy and radiotherapy, are associated. Radiation recall pneumonitis is an uncommon treatment complication that should be correctly characterized, and it is essential to recognize the mechanisms of radiation recall pneumonitis pathogenesis and diagnostic features in order to promptly identify them and adopt the best therapeutic strategy, with the shortest possible withdrawal of the current oncological drug. In this setting, artificial intelligence could have a critical role, although a larger patient data set is required.

Post-Surgical Imaging Assessment in Rectal Cancer: Normal Findings and Complications.

Rectal cancer (RC) is one of the deadliest malignancies worldwide. Surgery is the most common treatment for RC, performed in 63.2% of patients. The type of surgical approach chosen aims to achieve maximum residual function with the lowest risk of recurrence. The selection is made by a multidisciplinary team that assesses the characteristics of the patient and the tumor. Total mesorectal excision (TME), including both low anterior resection (LAR) and abdominoperineal resection (APR), is still the standard of care for RC. Radical surgery is burdened by a 31% rate of major complications (Clavien-Dindo grade 3-4), such as anastomotic leaks and a risk of a permanent stoma. In recent years, less-invasive techniques, such as local excision, have been tested. These additional procedures could mitigate the morbidity of rectal resection, while providing acceptable oncologic results. The "watch and wait" approach is not a globally accepted model of care but encouraging results on selected groups of patients make it a promising strategy. In this plethora of treatments, the radiologist is called upon to distinguish a physiological from a pathological postoperative finding. The aim of this narrative review is to identify the main post-surgical complications and the most effective imaging techniques.