The role of stereotactic radiotherapy in addition to immunotherapy in the management of melanoma brain metastases: results of a systematic review

Navigating the landscape of immune checkpoint inhibitors and novel immunotherapies in melanoma: long-term outcomes, progress, and challenges

INTRODUCTION

Melanoma has become the poster child for transformative outcomes in advanced malignancy from the use of immunotherapy over the last 10-15 years with median survival improving from ~ 1 to > 5 years. With the increasing repertoire of immune checkpoint inhibitors (ICI) and other novel immunotherapeutic approaches, integrating and sequencing treatments to create new paradigms has gained prominence, with focus on optimizing toxicity management and complex scenarios such as immunotherapy resistance, brain metastases, fertility, and duration of follow-up.

AREAS COVERED

In this review, we summarize the progress and emerging evidence in melanoma treatments to date and consider management and possible future directions to improve outcomes for above-mentioned specific patient cohorts.

EXPERT OPINION

Personalized care with integration of novel prognostic and predictive biomarkers is the way forward in tailoring not only patient selection and choice of therapy, but also duration of treatment and surveillance to allow for early recurrence detection and access to newer therapies such as tumor infiltrating lymphocytes (TIL) to maximize the curative fraction of melanoma patients. Further research is needed in optimizing ICI and other immunotherapy toxicity management, including reducing steroid exposure for better patient outcomes and preserving quality of life.

The clinical benefit of adding radiotherapy to ipilimumab in patients with melanoma brain metastasis: a systematic review and meta-analysis

Combining radiotherapy (RT) with Ipilimumab, a CTLA-4 inhibitor, holds promise in treating metastatic brain melanoma (MBM). Despite promising preclinical evidence, clinical studies evaluating their combined efficacy are limited and varied, necessitating a systematic review and meta-analysis to consolidate evidence and identify predictors of response or resistance in this challenging patient population. This study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The electronic databases of PubMed, Embase, Scopus, and Web of science were searched on July 9th, 2024, using the relevant key terms without filters. All statistical analysis was performed by STATA v.17. A total of 26 studies with 1059 participants were included. The 1, 2, and 3-year overall survival rates were 0.44 [95% CI: 0.32-0.55], 0.28 [95% CI: 0.17, 0.39], and 0.19 [95% CI: 0.06-0.32], respectively. The pooled 12-month local control and 1-year progression-free survival rate were 0.53 [95% CI: 0.34-0.71] and 0.20 [95%CI: 0.10-0.30]. The pooled overall response rate, partial response rates, and stable disease rate were 0.26 [95% CI: 0.10-0.41], 0.10 [95% CI:0.05-0.15], 0.17 [95%CI:0.10-0.23], and 0.58 [95%CI: 0.45-0.70]. This study demonstrated promising results regarding adding RT to ipilimumab which was associated with significantly higher 1-year OS, 18-month OS, 2-year OS, 3-year OS, overall radiological response rate, and stable disease rate and significantly lower rate of progressive disease rate compared to ipilimumab without RT. However, no significant difference was observed between two groups in 6-month OS, 12-month LC, 1-year PFS, and partial response rate.

Uncovering the Heterogeneity of Signaling Pathways in Skin Cutaneous Melanoma: Insights into Prognostic Values and Immune Interactions

Background

Signaling pathways play crucial roles in tumor cells. However, functional heterogeneity of signaling pathways in skin cutaneous melanoma (SKCM) has not been established.

Methods

Based on a recent computational pipeline, pathway activities between SKCM and normal samples were identified.

Results

The results showed that high activities in 12 pathways were associated with poor prognoses, while high activities in 17 pathways were associated with favorable prognoses. Interestingly, elevated metabolic pathway activity was unfavorable, whereas elevated immune activity was favorable for SKCM. Unfavorably elevated metabolic pathways strongly correlated with Wnt/beta-catenin signaling. Conversely, favorable pathways, such as glycosaminoglycan biosynthesis and keratan sulfate, were strongly correlated with anti-tumor pathways. Moreover, the activities of favorable pathways were strongly positively correlated with infiltrating CD8+ T cells, macrophages M1, immune score, and stromal score, all of which were favorable for SKCM.

Conclusion

Taken together, our study provides insights into the characteristics of several pathways in SKCM.

Radiation and Melanoma: Where Are We Now?

PURPOSE OF REVIEW

This review summarizes the current role of radiotherapy for the treatment of cutaneous melanoma in the definitive, adjuvant, and palliative settings, and combinations with immunotherapy and targeted therapies.

RECENT FINDINGS

Definitive radiotherapy may be considered for lentigo maligna if surgery would be disfiguring. High risk, resected melanoma may be treated with adjuvant radiotherapy, but the role is poorly defined since the advent of effective systemic therapies. For patients with metastatic disease, immunotherapy and targeted therapies can be delivered safely in tandem with radiotherapy to improve outcomes. Radiotherapy and modern systemic therapies act in concert to improve outcomes, especially in the metastatic setting. Further prospective data is needed to guide the use of definitive radiotherapy for lentigo maligna and adjuvant radiotherapy for high-risk melanoma in the immunotherapy era. Current evidence does not support an abscopal response or at least identify the conditions necessary to reliably produce one with combinations of radiation and immunotherapy.

'Immunotherapeutic Strategies for Intra-cranial Metastatic Melanoma - a Meta-analysis and Systematic Review'

Immune-activating anti-CTLA4 and anti-PD1 monoclonal antibodies (alone or in combination) are being used to treat advanced melanoma patients and can lead to durable remissions, and long-term overall survival may be achieved in between 50-60% of patients. Although intracranial metastases are very common in melanoma (about 50-75% of all patients with advanced disease), most of the pivotal prospective clinical trials exclude patients with intra-cranial metastases, certainly if their lesions are symptomatic and steroid-requiring and the degree of sensitivity of intra-cranial melanoma to immunotherapy remains uncertain, and requires further investigation especially in view of the demonstrable activity of RAF-MEK inhibitors in this clinical setting and the emergence of stereotactic radiotherapy. Our study aimed to evaluate the efficacy and toxicity of immunotherapy against advanced melanoma patients with brain metastases. In terms of comparative studies, only retrospective analyses could be identified. Based on 3 retrospective studies, treatment of patients with melanoma brain metastases with immunotherapeutic approaches improves overall survival substantially compared with supportive measures alone (no active anticancer treatment). The efficacy of targeted therapy appeared to be comparable to that of immune therapy in terms of overall survival, based on a small number of patients. The combination of concurrent radiation therapy to the brain and systemic immunotherapy led to improved overall survival compared to radiotherapy alone, suggesting potential synergism between the approaches, and combination treatment could be delivered safely. Our review supports the use of immunotherapeutic strategies for these patients although treatment efficacy appears to be lower for symptomatic lesions. In view of the extremely high efficacy of stereotactic radiotherapy approaches in the brain, understanding the interaction between radiotherapy and immunotherapy is vital and should be an area of active investigation.

Scientific Status Quo of Small Renal Lesions: Diagnostic Assessment and Radiomics

Background: Small renal masses (SRMs) are defined as contrast-enhanced renal lesions less than or equal to 4 cm in maximal diameter, which can be compatible with stage T1a renal cell carcinomas (RCCs). Currently, 50-61% of all renal tumors are found incidentally. Methods: The characteristics of the lesion influence the choice of the type of management, which include several methods SRM of management, including nephrectomy, partial nephrectomy, ablation, observation, and also stereotactic body radiotherapy. Typical imaging methods available for differentiating benign from malignant renal lesions include ultrasound (US), contrast-enhanced ultrasound (CEUS), computed tomography (CT), and magnetic resonance imaging (MRI). Results: Although ultrasound is the first imaging technique used to detect small renal lesions, it has several limitations. CT is the main and most widely used imaging technique for SRM characterization. The main advantages of MRI compared to CT are the better contrast resolution and tissue characterization, the use of functional imaging sequences, the possibility of performing the examination in patients allergic to iodine-containing contrast medium, and the absence of exposure to ionizing radiation. For a correct evaluation during imaging follow-up, it is necessary to use a reliable method for the assessment of renal lesions, represented by the Bosniak classification system. This classification was initially developed based on contrast-enhanced CT imaging findings, and the 2019 revision proposed the inclusion of MRI features; however, the latest classification has not yet received widespread validation. Conclusions: The use of radiomics in the evaluation of renal masses is an emerging and increasingly central field with several applications such as characterizing renal masses, distinguishing RCC subtypes, monitoring response to targeted therapeutic agents, and prognosis in a metastatic context.

Mitochondria-Targeted Nitronyl Nitroxide Radical Nanoparticles for Protection against Radiation-Induced Damage with Antioxidant Effects

Radiotherapy is a non-invasive method that is widely applied to treat and alleviate cancers. However, radiation-induced effects in the immune system are associated with several side effects via an increase in oxidative stress and the inflammatory response. Therefore, it is imperative to develop effective clinical radiological protection strategies for the radiological protection of the normal organs and immune system in these patients. To explore more effective radioprotective agents with minimal toxicity, a mitochondria-targeted nitronyl nitroxide radical with a triphenylphosphine ion (TPP-NIT) was synthesized and its nanoparticles (NPs-TPP-NIT) were prepared and characterized. The TPP-NIT nanoparticles (NPs-TPP-NIT) were narrow in their size distribution and uniformly distributed; they showed good drug encapsulation efficiency and a low hemolysis rate (<3%). The protective effect of NPs-TPP-NIT against X-ray irradiation-induced oxidative damage was measured in vitro and in vivo. The results show that NPs-TPP-NIT were associated with no obvious cytotoxicity to L-02 cells when the concentration was below 1.5 × 10-2 mmol. NPs-TPP-NIT enhanced the survival rate of L-02 cells significantly under 2, 4, 6, and 8 Gy X-ray radiation exposure; the survival rate of mice was highest after 6 Gy X-ray irradiation. The results also show that NPs-TPP-NIT could increase superoxide dismutase (SOD) activity and decrease malondialdehyde (MDA) levels after the L-02 cells were exposed to 6.0 Gy of X-ray radiation. Moreover, NPs-TPP-NIT could significantly inhibit cell apoptosis. NPs-TPP-NIT significantly increased the mouse survival rate after irradiation. NPs-TPP-NIT displayed a marked ability to reduce the irradiation-induced depletion of red blood cells (RBCs), white blood cells (WBCs), and platelets (PLTs). These results demonstrate the feasibility of using NPs-TPP-NIT to provide protection from radiation-induced damage. In conclusion, this study revealed that NPs-TPP-NIT may be promising radioprotectors and could therefore be applied to protect healthy tissues and organs from radiation during the treatment of cancer with radiotherapy.

Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment

PURPOSE

We aimed to assess the efficacy of machine learning and radiomics analysis using magnetic resonance imaging (MRI) with a hepatospecific contrast agent, in a pre-surgical setting, to predict tumor budding in liver metastases.

METHODS

Patients with MRI in a pre-surgical setting were retrospectively enrolled. Manual segmentation was made by means 3D Slicer image computing, and 851 radiomics features were extracted as median values using the PyRadiomics Python package. Balancing was performed and inter- and intraclass correlation coefficients were calculated to assess the between observer and within observer reproducibility of all radiomics extracted features. A Wilcoxon-Mann-Whitney nonparametric test and receiver operating characteristics (ROC) analysis were carried out. Balancing and feature selection procedures were performed. Linear and non-logistic regression models (LRM and NLRM) and different machine learning-based classifiers including decision tree (DT), k-nearest neighbor (KNN) and support vector machine (SVM) were considered.

RESULTS

The internal training set included 49 patients and 119 liver metastases. The validation cohort consisted of a total of 28 single lesion patients. The best single predictor to classify tumor budding was original_glcm_Idn obtained in the T1-W VIBE sequence arterial phase with an accuracy of 84%; wavelet_LLH_firstorder_10Percentile was obtained in the T1-W VIBE sequence portal phase with an accuracy of 92%; wavelet_HHL_glcm_MaximumProbability was obtained in the T1-W VIBE sequence hepatobiliary excretion phase with an accuracy of 88%; and wavelet_LLH_glcm_Imc1 was obtained in T2-W SPACE sequences with an accuracy of 88%. Considering the linear regression analysis, a statistically significant increase in accuracy to 96% was obtained using a linear weighted combination of 13 radiomic features extracted from the T1-W VIBE sequence arterial phase. Moreover, the best classifier was a KNN trained with the 13 radiomic features extracted from the arterial phase of the T1-W VIBE sequence, obtaining an accuracy of 95% and an AUC of 0.96. The validation set reached an accuracy of 94%, a sensitivity of 86% and a specificity of 95%.

CONCLUSIONS

Machine learning and radiomics analysis are promising tools in predicting tumor budding. Considering the linear regression analysis, there was a statistically significant increase in accuracy to 96% using a weighted linear combination of 13 radiomics features extracted from the arterial phase compared to a single radiomics feature.

Novel Combination Treatment for Melanoma: FLASH Radiotherapy and Immunotherapy Delivered by a Radiopaque and Radiation Responsive Hydrogel

Immunotherapies have become the standard treatment for melanoma. To further improve patient responses, combinations of immunotherapies and radiotherapy (RT) are being studied, since radiotherapies can potentially provide additional immune stimulation, in addition to direct antitumor effects. FLASH-RT is a novel, ultrahigh dose rate, radiation delivery approach, with the potential of at least equivalent tumor control efficacy and reduced damage to healthy tissue. However, the effects of combining FLASH-RT and immunotherapy have not been extensively studied in melanoma. Toll-like receptor (TLR) agonists, such as imiquimod (IMQ), are potent immunostimulatory agents, although their utility is limited due to poor solubility and systemic side effects. We therefore developed a novel combination therapy for melanoma consisting of IMQ delivered to the tumor via a radiopaque and radiation responsive hydrogel combined with FLASH-RT. We found that FLASH was able to effectively stimulate IMQ release from the hydrogel. In addition, we found that the combination of FLASH and released IMQ resulted in synergistic melanoma cell killing in vitro. The combination therapy reduced tumor growth compared to controls, enhanced survival, and resulted in remarkable enhancements in certain tumor cytokine levels. CT imaging allowed the hydrogel to be monitored in vivo. In addition, no adverse effects of the treatment were observed. Overall, this IMQ-gel and FLASH-RT combination may have potential as an improved treatment for melanoma and indicates that the interactions of FLASH-RT and TLR agonists merit further study.

Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment

OBJECTIVE

The aim of this study was the evaluation radiomics analysis efficacy performed using computed tomography (CT) and magnetic resonance imaging in the prediction of colorectal liver metastases patterns linked to patient prognosis: tumor growth front; grade; tumor budding; mucinous type. Moreover, the prediction of liver recurrence was also evaluated.

METHODS

The retrospective study included an internal and validation dataset; the first was composed by 119 liver metastases from 49 patients while the second consisted to 28 patients with single lesion. Radiomic features were extracted using PyRadiomics. Univariate and multivariate approaches including machine learning algorithms were employed.

RESULTS

The best predictor to identify tumor growth was the Wavelet_HLH_glcm_MaximumProbability with an accuracy of 84% and to detect recurrence the best predictor was wavelet_HLH_ngtdm_Complexity with an accuracy of 90%, both extracted by T1-weigthed arterial phase sequence. The best predictor to detect tumor budding was the wavelet_LLH_glcm_Imc1 with an accuracy of 88% and to identify mucinous type was wavelet_LLH_glcm_JointEntropy with an accuracy of 92%, both calculated on T2-weigthed sequence. An increase statistically significant of accuracy (90%) was obtained using a linear weighted combination of 15 predictors extracted by T2-weigthed images to detect tumor front growth. An increase statistically significant of accuracy at 93% was obtained using a linear weighted combination of 11 predictors by the T1-weigthed arterial phase sequence to classify tumor budding. An increase statistically significant of accuracy at 97% was obtained using a linear weighted combination of 16 predictors extracted on CT to detect recurrence. An increase statistically significant of accuracy was obtained in the tumor budding identification considering a K-nearest neighbors and the 11 significant features extracted T1-weigthed arterial phase sequence.

CONCLUSIONS

The results confirmed the Radiomics capacity to recognize clinical and histopathological prognostic features that should influence the choice of treatments in colorectal liver metastases patients to obtain a more personalized therapy.

Radiosurgery for Brain Metastases: Challenges in Imaging Interpretation after Treatment

Stereotactic radiosurgery (SRS) has transformed the management of brain metastases by achieving local tumor control, reducing toxicity, and minimizing the need for whole-brain radiation therapy (WBRT). This review specifically investigates radiation-induced changes in patients treated for metastasis, highlighting the crucial role of magnetic resonance imaging (MRI) in the evaluation of treatment response, both at very early and late stages. The primary objective of the review is to evaluate the most effective imaging techniques for assessing radiation-induced changes and distinguishing them from tumor growth. The limitations of conventional imaging methods, which rely on size measurements, dimensional criteria, and contrast enhancement patterns, are critically evaluated. In addition, it has been investigated the potential of advanced imaging modalities to offer a more precise and comprehensive evaluation of treatment response. Finally, an overview of the relevant literature concerning the interpretation of brain changes in patients undergoing immunotherapies is provided.

Prognostic Assessment of Gastropancreatic Neuroendocrine Neoplasm: Prospects and Limits of Radiomics

Neuroendocrine neoplasms (NENs) are a group of lesions originating from cells of the diffuse neuroendocrine system. NENs may involve different sites, including the gastrointestinal tract (GEP-NENs). The incidence and prevalence of GEP-NENs has been constantly rising thanks to the increased diagnostic power of imaging and immuno-histochemistry. Despite the plethora of biochemical markers and imaging techniques, the prognosis and therapeutic choice in GEP-NENs still represents a challenge, mainly due to the great heterogeneity in terms of tumor lesions and clinical behavior. The concept that biomedical images contain information about tissue heterogeneity and pathological processes invisible to the human eye is now well established. From this substrate comes the idea of radiomics. Computational analysis has achieved promising results in several oncological settings, and the use of radiomics in different types of GEP-NENs is growing in the field of research, yet with conflicting results. The aim of this narrative review is to provide a comprehensive update on the role of radiomics on GEP-NEN management, focusing on the main clinical aspects analyzed by most existing reports: predicting tumor grade, distinguishing NET from other tumors, and prognosis assessment.

Artificial intelligence and radiation effects on brain tissue in glioblastoma patient: preliminary data using a quantitative tool

PURPOSE

The quantification of radiotherapy (RT)-induced functional and morphological brain alterations is fundamental to guide therapeutic decisions in patients with brain tumors. The magnetic resonance imaging (MRI) allows to define structural RT-brain changes, but it is unable to evaluate early injuries and to objectively quantify the volume tissue loss. Artificial intelligence (AI) tools extract accurate measurements that permit an objective brain different region quantification. In this study, we assessed the consistency between an AI software (Quibim Precision^® 2.9) and qualitative neruroradiologist evaluation, and its ability to quantify the brain tissue changes during RT treatment in patients with glioblastoma multiforme (GBM).

METHODS

GBM patients treated with RT and subjected to MRI assessment were enrolled. Each patient, pre- and post-RT, undergoes to a qualitative evaluation with global cerebral atrophy (GCA) and medial temporal lobe atrophy (MTA) and a quantitative assessment with Quibim Brain screening and hippocampal atrophy and asymmetry modules on 19 extracted brain structures features.

RESULTS

A statistically significant strong negative association between the percentage value of the left temporal lobe and the GCA score and the left temporal lobe and the MTA score was found, while a moderate negative association between the percentage value of the right hippocampus and the GCA score and the right hippocampus and the MTA score was assessed. A statistically significant strong positive association between the CSF percentage value and the GCA score and a moderate positive association between the CSF percentage value and the MTA score was found. Finally, quantitative feature values showed that the percentage value of the cerebro-spinal fluid (CSF) statistically differences between pre- and post-RT.

CONCLUSIONS

AI tools can support a correct evaluation of RT-induced brain injuries, allowing an objective and earlier assessment of the brain tissue modifications.

Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics

In this narrative review, we reported un up-to-date on the role of radiomics to assess prognostic features, which can impact on the liver metastases patient treatment choice. In the liver metastases patients, the possibility to assess mutational status (RAS or MSI), the tumor growth pattern and the histological subtype (NOS or mucinous) allows a better treatment selection to avoid unnecessary therapies. However, today, the detection of these features require an invasive approach. Recently, radiomics analysis application has improved rapidly, with a consequent growing interest in the oncological field. Radiomics analysis allows the textural characteristics assessment, which are correlated to biological data. This approach is captivating since it should allow to extract biological data from the radiological images, without invasive approach, so that to reduce costs and time, avoiding any risk for the patients. Several studies showed the ability of Radiomics to identify mutational status, tumor growth pattern and histological type in colorectal liver metastases. Although, radiomics analysis in a non-invasive and repeatable way, however features as the poor standardization and generalization of clinical studies results limit the translation of this analysis into clinical practice. Clear limits are data-quality control, reproducibility, repeatability, generalizability of results, and issues related to model overfitting.

Dose Reduction Strategies for Pregnant Women in Emergency Settings

In modern clinical practice, there is an increasing dependence on imaging techniques in several settings, and especially during emergencies. Consequently, there has been an increase in the frequency of imaging examinations and thus also an increased risk of radiation exposure. In this context, a critical phase is a woman's pregnancy management that requires a proper diagnostic assessment to reduce radiation risk to the fetus and mother. The risk is greatest during the first phases of pregnancy at the time of organogenesis. Therefore, the principles of radiation protection should guide the multidisciplinary team. Although diagnostic tools that do not employ ionizing radiation, such as ultrasound (US) and magnetic resonance imaging (MRI) should be preferred, in several settings as polytrauma, computed tomography (CT) nonetheless remains the examination to perform, beyond the fetus risk. In addition, protocol optimization, using dose-limiting protocols and avoiding multiple acquisitions, is a critical point that makes it possible to reduce risks. The purpose of this review is to provide a critical evaluation of emergency conditions, e.g., abdominal pain and trauma, considering the different diagnostic tools that should be used as study protocols in order to control the dose to the pregnant woman and fetus.

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.

Risk Assessment and Cholangiocarcinoma: Diagnostic Management and Artificial Intelligence

Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver tumor, with a median survival of only 13 months. Surgical resection remains the only curative therapy; however, at first detection, only one-third of patients are at an early enough stage for this approach to be effective, thus rendering early diagnosis as an efficient approach to improving survival. Therefore, the identification of higher-risk patients, whose risk is correlated with genetic and pre-cancerous conditions, and the employment of non-invasive-screening modalities would be appropriate. For several at-risk patients, such as those suffering from primary sclerosing cholangitis or fibropolycystic liver disease, the use of periodic (6-12 months) imaging of the liver by ultrasound (US), magnetic Resonance Imaging (MRI)/cholangiopancreatography (MRCP), or computed tomography (CT) in association with serum CA19-9 measurement has been proposed. For liver cirrhosis patients, it has been proposed that at-risk iCCA patients are monitored in a similar fashion to at-risk HCC patients. The possibility of using Artificial Intelligence models to evaluate higher-risk patients could favor the diagnosis of these entities, although more data are needed to support the practical utility of these applications in the field of screening. For these reasons, it would be appropriate to develop screening programs in the research protocols setting. In fact, the success of these programs reauires patient compliance and multidisciplinary cooperation.

Immunotherapy Assessment: A New Paradigm for Radiologists

Immunotherapy denotes an exemplar change in an oncological setting. Despite the effective application of these treatments across a broad range of tumors, only a minority of patients have beneficial effects. The efficacy of immunotherapy is affected by several factors, including human immunity, which is strongly correlated to genetic features, such as intra-tumor heterogeneity. Classic imaging assessment, based on computed tomography (CT) or magnetic resonance imaging (MRI), which is useful for conventional treatments, has a limited role in immunotherapy. The reason is due to different patterns of response and/or progression during this kind of treatment which differs from those seen during other treatments, such as the possibility to assess the wide spectrum of immunotherapy-correlated toxic effects (ir-AEs) as soon as possible. In addition, considering the unusual response patterns, the limits of conventional response criteria and the necessity of using related immune-response criteria are clear. Radiomics analysis is a recent field of great interest in a radiological setting and recently it has grown the idea that we could identify patients who will be fit for this treatment or who will develop ir-AEs.

Imaging Features of Main Hepatic Resections: The Radiologist Challenging

Liver resection is still the most effective treatment of primary liver malignancies, including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), and of metastatic disease, such as colorectal liver metastases. The type of liver resection (anatomic versus non anatomic resection) depends on different features, mainly on the type of malignancy (primary liver neoplasm versus metastatic lesion), size of tumor, its relation with blood and biliary vessels, and the volume of future liver remnant (FLT). Imaging plays a critical role in postoperative assessment, offering the possibility to recognize normal postoperative findings and potential complications. Ultrasonography (US) is the first-line diagnostic tool to use in post-surgical phase. However, computed tomography (CT), due to its comprehensive assessment, allows for a more accurate evaluation and more normal findings than the possible postoperative complications. Magnetic resonance imaging (MRI) with cholangiopancreatography (MRCP) and/or hepatospecific contrast agents remains the best tool for bile duct injuries diagnosis and for ischemic cholangitis evaluation. Consequently, radiologists should be familiar with the surgical approaches for a better comprehension of normal postoperative findings and of postoperative complications.

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.

Risk Assessment and Pancreatic Cancer: Diagnostic Management and Artificial Intelligence

Pancreatic cancer (PC) is one of the deadliest cancers, and it is responsible for a number of deaths almost equal to its incidence. The high mortality rate is correlated with several explanations; the main one is the late disease stage at which the majority of patients are diagnosed. Since surgical resection has been recognised as the only curative treatment, a PC diagnosis at the initial stage is believed the main tool to improve survival. Therefore, patient stratification according to familial and genetic risk and the creation of screening protocol by using minimally invasive diagnostic tools would be appropriate. Pancreatic cystic neoplasms (PCNs) are subsets of lesions which deserve special management to avoid overtreatment. The current PC screening programs are based on the annual employment of magnetic resonance imaging with cholangiopancreatography sequences (MR/MRCP) and/or endoscopic ultrasonography (EUS). For patients unfit for MRI, computed tomography (CT) could be proposed, although CT results in lower detection rates, compared to MRI, for small lesions. The actual major limit is the incapacity to detect and characterize the pancreatic intraepithelial neoplasia (PanIN) by EUS and MR/MRCP. The possibility of utilizing artificial intelligence models to evaluate higher-risk patients could favour the diagnosis of these entities, although more data are needed to support the real utility of these applications in the field of screening. For these motives, it would be appropriate to realize screening programs in research settings.