Histogram analysis of DCE-MRI for chemoradiotherapy response evaluation in locally advanced esophageal squamous cell carcinoma

Evaluating Neoadjuvant Immunochemotherapeutic Response for Bladder Carcinoma Using Amide Proton Transfer-Weighted MRI

RATIONALE AND OBJECTIVES

To investigate the feasibility of amide proton transfer-weighted (APTw) and diffusion-weighted MRI in evaluating the response of bladder cancer (BCa) to neoadjuvant immunochemotherapy.

MATERIALS AND METHODS

From June 2021 to July 2023, participants with pathologically confirmed BCa were prospectively recruited to undergo MRI examinations, including APTw and diffusion-weighted MRI before and after neoadjuvant immunochemotherapy. Histogram analysis features (mean, median, and entropy) were extracted from pre- and post-treatment APTw and apparent diffusion coefficient (ADC) maps, respectively. Participants were categorized into pCR (pathological complete response, no residual tumor) and non-pCR groups based on histologic evaluation of post-treatment cystectomy specimens. The diagnostic efficacy of parameters in predicting tumor responsiveness was evaluated by calculating the area under receiver operating characteristic curve (AUC).

RESULTS

Significant differences were found in several imaging biomarkers derived from pre-treatment APTw and diffusion-weighted MRI (P<0.05 for all). The baseline APTw mean values yielded the highest diagnostic performance, with an AUC of 0.85 (AUC: 0.75-0.93), for evaluating tumor responsiveness. For the pCR group, APTw values markedly decreased while ADC values noticeably increased at post-treatment MRI (P<0.05 for all). However, the parameter changes in non-pCR group were not significant (P>0.05 for all).

CONCLUSION

MRI parametrics derived from APTw and diffusion-weighted MRI can both serve as valuable noninvasive imaging biomarkers for evaluating the efficacy of immunochemotherapy and may be used to guide personalized precision therapy.

DCE-MRI quantitative analysis and MRI-based radiomics for predicting the early efficacy of microwave ablation in lung cancers

OBJECTIVES

To evaluate the feasibility and value of dynamic contrast-enhanced MRI (DCE-MRI) quantitative analysis and MRI-based radiomics in predicting the efficacy of microwave ablation (MWA) in lung cancers (LCs).

METHODS

Forty-three patients with LCs who underwent DCE-MRI within 24 h of receiving MWA were enrolled in the study and divided into two groups according to the modified response evaluation criteria in solid tumors (m-RECIST) criteria: the effective treatment (complete response + partial response + stable disease, n = 28) and the ineffective treatment (progressive disease, n = 15). DCE-MRI datasets were processed by Omni. Kinetics software, using the extended tofts model (ETM) and exchange model (ECM) to yield pharmacokinetic parameters and their histogram features. Changes in quantitative perfusion parameters were compared between the two groups. Scientific research platform ( https://medresearch.shukun.net/ ) was used for radiomics analysis. A total of 1874 radiomic features were extracted for each tumor by manually segmentation of T1WI and Contrast-enhanced of T1WI (Ce-T1WI) fat inhibition sequence. The performances of radiomics models were evaluated by the receiver operating characteristic curve. Based on radiomics features, survival curves were generated by Kaplan-Meier survival analysis to evaluate patient outcomes. P < 0.05 was set for the significance threshold.

RESULTS

The Vp value of ECM was significantly higher in the ineffective group compared to the effective group (p = 0.027). Additionally, the skewness, and kurtosis of Vp (p = 0.020 and 0.013, respectively) derived from ETM and Fp (p = 0.027 and 0.030, respectively) from ECM as well as the quantiles were higher in the ineffective group than in the effective group. Significant statistical differences were observed in the energy and entropy of Ve (p = 0.044 and 0.025, respectively) and Vp (p = 0.025 and 0.026, respectively) between the two groups. In the process of model construction, seven features from T1WI, five features from Ce-T1WI, and ten features from combined sequences were ultimately selected. The area under the curve (AUC) values for the T1WI model, Ce-T1WI model, and combined model were 0.910, 0.890, 0.965 in the training group, and 0.850, 0.700, 0.850 in the test group, respectively.

CONCLUSIONS

DCE-MRI quantitative analysis and MRI-based radiomics may be helpful in assessing the early response to MWA in patients with LCs.

Meta-Analysis of MRI in Predicting Early Response to Radiotherapy and Chemotherapy in Esophageal Cancer

RATIONALE AND OBJECTIVES

At present, the application of magnetic resonance imaging (MRI) in the prediction of response to neoadjuvant therapy and concurrent chemoradiotherapy for the treatment of esophageal cancer still needs to be further explored, and its early differential value remains controversial, thus we carried out this systematic review with a meta-analysis. In the application, different MRI sequences and corresponding parameters are used for the differential diagnosis of the response to neoadjuvant therapy and concurrent chemoradiotherapy.

METHODS

All relevant studies evaluated the efficacy and response to MRI in neoadjuvant therapy or concurrent chemoradiotherapy for esophageal cancer on Pubmed, Embase, Cohrane Library, and Web of Science databases published before October 10, 2023 (inclusive) were systematically searched. A revised tool was used to assess the quality of diagnostic accuracy studies (QUADAS-2) to assess the risk of bias in the included original studies. A subgroup analysis of MRI sequences diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE) and their corresponding different parameters, as well as the acquisition timepoints (before and after treatment) for different parameters, was performed during the meta-analysis. The bivariate mixed-effects model was used for meta-analysis.

RESULTS

21 studies were finally included, involving 1128 patients with esophageal cancer. The sensitivity, specificity, and area under receiver operating characteristic curve (ROC curve) of DWI sequence for identifying response to concurrent chemoradiotherapy were 0.82 (95% CI: 0.74-0.87), 0.81 (95% CI: 0.72-0.87) and 0.88 (95% CI: 0.56-0.98), respectively. The sensitivity, specificity, and area under ROC curve of DCE sequence for identifying response to concurrent chemoradiotherapy were 0.78 (95% CI: 0.70-0.84), 0.65 (95% CI: 0.59-0.70) and 0.73 (95% CI: 0.50-0.88), respectively. In patients with esophageal cancer, the sensitivity, specificity, and area under the ROC curve of DWI sequences for identifying response to neoadjuvant therapy were 0.80 (95% CI: 0.69 - 0.88), 0.81 (95% CI: 0.69 - 0.89), and 0.88 (95% CI: 0.34 - 0.99), respectively; the sensitivity, specificity, and area under the ROC curve of DCE sequences for identifying response to neoadjuvant therapy were 0.84 (95% CI: 0.76 - 0.90), 0.61 (95% CI: 0.53 - 0.68), and 0.70 (95% CI: 0.27 - 0.94), respectively.

CONCLUSIONS

Based on the available evidence, MRI had a very good value in the early identification of response to neoadjuvant therapy and concurrent chemoradiotherapy for esophageal cancer, especially DWI. Apparent diffusion coefficient (ADC) value changes before and after treatment could be used as predictors of pathological response. Also, ADC value changes before and after treatment could be used as a tool to guide clinical decision-making.

Correlation of Ktrans derived from dynamic contrast-enhanced MRI with treatment response and survival in locally advanced NSCLC patients undergoing induction immunochemotherapy and concurrent chemoradiotherapy

PURPOSE

This study aimed to investigate the prognostic significance of pretreatment dynamic contrast-enhanced (DCE)-MRI parameters concerning tumor response following induction immunochemotherapy and survival outcomes in patients with locally advanced non-small cell lung cancer (NSCLC) who underwent immunotherapy-based multimodal treatments.

MATERIAL AND METHODS

Unresectable stage III NSCLC patients treated by induction immunochemotherapy, concurrent chemoradiotherapy (CCRT) with or without consolidative immunotherapy from two prospective clinical trials were screened. Using the two-compartment Extend Tofts model, the parameters including Ktrans, Kep, Ve, and Vp were calculated from DCE-MRI data. The apparent diffusion coefficient was calculated from diffusion-weighted-MRI data. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to assess the predictive performance of MRI parameters. The Cox regression model was used for univariate and multivariate analysis.

RESULTS

111 unresectable stage III NSCLC patients were enrolled. Patients received two cycles of induction immunochemotherapy and CCRT, with or without consolidative immunotherapy. With the median follow-up of 22.3 months, the median progression-free survival (PFS) and overall survival (OS) were 16.3 and 23.8 months. The multivariate analysis suggested that Eastern Cooperative Oncology Group score, TNM stage and the response to induction immunochemotherapy were significantly related to both PFS and OS. After induction immunochemotherapy, 67 patients (59.8%) achieved complete response or partial response and 44 patients (40.2%) had stable disease or progressive disease. The Ktrans of primary lung tumor before induction immunochemotherapy yielded the best performance in predicting the treatment response, with an AUC of 0.800. Patients were categorized into two groups: high-Ktrans group (n=67, Ktrans＞164.3×10-3/min) and low-Ktrans group (n=44, Ktrans≤164.3×10-3/min) based on the ROC analysis. The high-Ktrans group had a significantly higher objective response rate than the low-Ktrans group (85.1% (57/67) vs 22.7% (10/44), p<0.001). The high-Ktrans group also presented better PFS (median: 21.1 vs 11.3 months, p=0.002) and OS (median: 34.3 vs 15.6 months, p=0.035) than the low-Ktrans group.

CONCLUSIONS

Pretreatment Ktrans value emerged as a significant predictor of the early response to induction immunochemotherapy and survival outcomes in unresectable stage III NSCLC patients who underwent immunotherapy-based multimodal treatments. Elevated Ktrans values correlated positively with enhanced treatment response, leading to extended PFS and OS durations.

Construction and validation of classification models for predicting the response to concurrent chemo-radiotherapy of patients with esophageal squamous cell carcinoma based on multi-omics data

BACKGROUND

Concurrent chemo-radiotherapy (CCRT) is the preferred non-surgical treatment for patients with locally advanced esophageal squamous cell carcinoma (ESCC). Unfortunately, some patients respond poorly, which leads to inappropriate or excessive treatment and affects patient survival. To accurately predict the response of ESCC patients to CCRT, we developed classification models based on the clinical, serum proteomic and radiomic data.

METHODS

A total of 138 ESCC patients receiving CCRT were enrolled in this study and randomly split into a training cohort (n = 92) and a test cohort (n = 46). All patients were classified into either complete response (CR) or incomplete response (non-CR) groups according to RECIST1.1. Radiomic features were extracted by 3Dslicer. Serum proteomic data was obtained by Olink proximity extension assay. The logistic regression model with elastic-net penalty and the R-package "rms" v6.2-0 were applied to construct classification and nomogram models, respectively. The area under the receiver operating characteristic curves (AUC) was used to evaluate the predictive performance of the models.

RESULTS

Seven classification models based on multi-omics data were constructed, of which Model-COR, which integrates five clinical, five serum proteomic, and seven radiomic features, achieved the best predictive performance on the test cohort (AUC = 0.8357, 95 % CI: 0.7158-0.9556). Meanwhile, patients predicted to be CR by Model-COR showed significantly longer overall survival than those predicted to be non-CR in both cohorts (Log-rank P = 0.0014 and 0.027, respectively). Furthermore, two nomogram models based on multi-omics data also performed well in predicting response to CCRT (AUC = 0.8398 and 0.8483, respectively).

CONCLUSION

We developed and validated a multi-omics based classification model and two nomogram models for predicting the response of ESCC patients to CCRT, which achieved the best prediction performance by integrating clinical, serum Olink proteomic, and radiomic data. These models could be useful for personalized treatment decisions and more precise clinical radiotherapy and chemotherapy for ESCC patients.

Novel Advances in Qualitative Diagnostic Imaging for Decision Making in Multidisciplinary Treatment for Advanced Esophageal Cancer

Background: Recently, neoadjuvant therapy and the succeeding surgery for advanced esophageal cancer have been evaluated. In particular, the response to the therapy has been found to affect surgical outcomes, and thus a precise evaluation of treatment effect is important for this strategy. In this study, articles on qualitative diagnostic modalities to evaluate tumor activities were reviewed, and the diagnostic indices were examined. Methods: For prediction of the effect, perfusion CT and diffusion MRI were estimated. For the histological response evaluation, perfusion CT, diffusion-MRI, and FDG-PET were estimated. For downstaging evaluation of T4, tissue-selective image reconstruction using enhanced CT was estimated and diagnostic indices were reviewed. Results: The prediction of the effect using perfusion CT with 'pre CRT blood flow' and diffusion MRI with 'pre CRT ADC value'; the estimation of the histological response using perfusion CT with 'post CRT blood flow reduction, using diffusion MRI with 'post CRT ADC increasing', and using FDG-PET with 'post CRT SUV reduction'; and the downstaging evaluation of T4 using CT image reconstruction with 'fibrous changed layer' were performed well, respectively. Conclusions: Qualitative imaging modalities for prediction or response evaluation of neoadjuvant therapy for progressive esophageal cancer were useful for the decision making of the treatment strategy of the multidisciplinary treatment.

The gap before real clinical application of imaging-based machine-learning and radiomic models for chemoradiation outcome prediction in esophageal cancer: a systematic review and meta-analysis

BACKGROUND

Due to tumoral heterogeneity and the lack of robust biomarkers, the prediction of chemoradiotherapy response and prognosis in patients with esophageal cancer (EC) is challenging. The goal of this study was to assess the study quality and clinical value of machine learning and radiomic-based quantitative imaging studies for predicting the outcomes of EC patients after chemoradiotherapy.

MATERIALS AND METHODS

PubMed, Embase, and Cochrane were searched for eligible articles. The methodological quality and risk of bias were evaluated using the Radiomics Quality Score (RQS), Image Biomarkers Standardization Initiative (IBSI) Guideline, and Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) statement, as well as the modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. A meta-analysis of the evidence focusing on predicting chemoradiotherapy response and outcome in EC patients was implemented.

RESULTS

Forty-six studies were eligible for qualitative synthesis. The mean RQS score was 9.07, with an adherence rate of 42.52%. The adherence rates of the TRIPOD and IBSI were 61.70 and 43.17%, respectively. Ultimately, 24 studies were included in the meta-analysis, of which 16 studies had a pooled sensitivity, specificity, and area under the curve (AUC) of 0.83 (0.76-0.89), 0.83 (0.79-0.86), and 0.84 (0.81-0.87) in neoadjuvant chemoradiotherapy datasets, as well as 0.84 (0.75-0.93), 0.89 (0.83-0.93), and 0.93 (0.90-0.95) in definitive chemoradiotherapy datasets, respectively. Moreover, radiomics could distinguish patients from the low-risk and high-risk groups with different disease-free survival (DFS) (pooled hazard ratio: 3.43, 95% CI 2.39-4.92) and overall survival (pooled hazard ratio: 2.49, 95% CI 1.91-3.25). The results of subgroup and regression analyses showed that some of the heterogeneity was explained by the combination with clinical factors, sample size, and usage of the deep learning (DL) signature.

CONCLUSIONS

Noninvasive radiomics offers promising potential for optimizing treatment decision-making in EC patients. However, it is necessary to make scientific advancements in EC radiomics regarding reproducibility, clinical usefulness analysis, and open science categories. Improved model reporting of study objectives, blind assessment, and image processing steps are required to help promote real clinical applications of radiomics in EC research.

Progress of magnetic resonance imaging radiomics in preoperative lymph node diagnosis of esophageal cancer

Esophageal cancer, also referred to as esophagus cancer, is a prevalent disease in the cardiothoracic field and is a leading cause of cancer-related mortality in China. Accurately determining the status of lymph nodes is crucial for developing treatment plans, defining the scope of intraoperative lymph node dissection, and ascertaining the prognosis of patients with esophageal cancer. Recent advances in diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging (MRI) have improved the effectiveness of MRI for assessing lymph node involvement, making it a beneficial tool for guiding personalized treatment plans for patients with esophageal cancer in a clinical setting. Radiomics is a recently developed imaging technique that transforms radiological image data from regions of interest into high-dimensional feature data that can be analyzed. The features, such as shape, texture, and waveform, are associated with the cancer phenotype and tumor microenvironment. When these features correlate with the clinical disease outcomes, they form the basis for specific and reliable clinical evidence. This study aimed to review the potential clinical applications of MRI-based radiomics in studying the lymph nodes affected by esophageal cancer. The combination of MRI and radiomics is a powerful tool for diagnosing and treating esophageal cancer, enabling a more personalized and effectual approach.

Tuning the optimal diffusion-weighted MRI parameters on a 0.35-T MR-Linac for clinical implementation: A phantom study

PURPOSE

This study aims to assess the quality of a new diffusion-weighted imaging (DWI) sequence implemented on an MR-Linac MRIdian system, evaluating and optimizing the acquisition parameters to explore the possibility of clinically implementing a DWI acquisition protocol in a 0.35-T MR-Linac.

MATERIALS AND METHODS

All the performed analyses have been carried out on two types of phantoms: a homogeneous 24-cm diameter polymethylmethacrylate (PMMA) sphere (SP) and a homemade phantom (HMP) constating in a PMMA cylinder filled with distilled water with empty sockets into which five cylindrical vials filled with five different concentrations of methylcellulose water solutions have been inserted. SP was used to evaluate the dependence of diffusion gradient inhomogeneity artifacts on gantry position. Four diffusion sequences with b-values of 500 s/mm2 and 3 averages have been acquired: three with diffusion gradients in the three main directions (phase direction, read direction, slice direction) and one with the diffusion gradients switched off. The dependence of diffusion image uniformity and SNR on the number of averages in the MR sequences was also investigated to determine the optimal number of averages. Finally, the ADC values of HMP have been computed and then compared between images acquired in the scanners at 0.35 and 1.5 T.

RESULTS

In order to acquire high-quality artifact-free DWI images, the "slice" gradient direction has been identified to be the optimal one and 0° to be the best gradient angle. Both the SNR ratio and the uniformity increase with the number of averages. A threshold value of 80 for SNR and 85% for uniformity was adopted to choose the best number of averages. By making a compromise between time and quality and limiting the number of b-values, it is possible to reduce the acquisition time to 78 s. The Passing-Bablok test showed that the two methods, with 0.35 and 1.5 T scanners, led to similar results.

CONCLUSION

The quality of the DWI has been accurately evaluated in relation to different sequence parameters, and optimal parameters have been identified to select a clinical protocol for the acquisition of ADC maps sustainable in the workflow of a hybrid radiotherapy system with a 0.35-T MRI scanner.

Integration between Novel Imaging Technologies and Modern Radiotherapy Techniques: How the Eye Drove the Chisel

INTRODUCTION

Targeted dose-escalation and reduction of dose to adjacent organs at risk have been the main goal of radiotherapy in the last decade. Prostate cancer benefited the most from this process. In recent years, the development of Intensity Modulated Radiation Therapy (IMRT) and Stereotactic Body Radiotherapy (SBRT) radically changed clinical practice, also thanks to the availability of modern imaging techniques. The aim of this paper is to explore the relationship between diagnostic imaging and prostate cancer radiotherapy techniques.

MATERIALS AND METHODS

Aiming to provide an overview of the integration between modern imaging and radiotherapy techniques, we performed a non-systematic search of papers exploring the predictive value of imaging before treatment, the role of radiomics in predicting treatment outcomes, implementation of novel imaging in RT planning and influence of imaging integration on use of RT in current clinical practice. Three independent authors (GF, IM and ID) performed an independent review focusing on these issues. Key references were derived from a PubMed query. Hand searching and clinicaltrials.gov were also used, and grey literature was searched for further papers of interest. The final choice of papers included was discussed between all co-authors.

RESULTS

This paper contains a narrative report and a critical discussion of the role of new modern techniques in predicting outcomes before treatment, in radiotherapy planning and in the integration with systemic therapy in the management of prostate cancer. Also, the role of radiomics in a tailored treatment approach is explored.

CONCLUSIONS

Integration between diagnostic imaging and radiotherapy is of great importance for the modern treatment of prostate cancer. Future clinical trials should be aimed at exploring the real clinical benefit of complex workflows in clinical practice.

Multimodality Imaging Assessment of Desmoid Tumors: The Great Mime in the Era of Multidisciplinary Teams

Desmoid tumors (DTs), also known as desmoid fibromatosis or aggressive fibromatosis, are rare, locally invasive, non-metastatic soft tissue tumors. Although histological results represent the gold standard diagnosis, imaging represents the fundamental tool for the diagnosis of these tumors. Although histological analysis represents the gold standard for diagnosis, imaging represents the fundamental tool for the diagnosis of these tumors. DTs represent a challenge for the radiologist, being able to mimic different pathological conditions. A proper diagnosis is required to establish an adequate therapeutic approach. Multimodality imaging, including ultrasound (US), computed tomography (CT) and Magnetic Resonance Imaging (MRI), should be preferred. Different imaging techniques can also guide minimally invasive treatments and monitor their effectiveness. The purpose of this review is to describe the state-of-the-art multidisciplinary imaging of DTs; and its role in patient management.

Ability of Delta Radiomics to Predict a Complete Pathological Response in Patients with Loco-Regional Rectal Cancer Addressed to Neoadjuvant Chemo-Radiation and Surgery

Simple Summary

The present study aimed to investigate the possible use of MRI delta texture analysis (D-TA) in order to predict the extent of pathological response in patients with locally advanced rectal cancer addressed to neoadjuvant chemo-radiotherapy (C-RT) followed by surgery. We found that D-TA may really predict the frequency of pCR in this patient setting and, thus, it may be investigated as a potential item to identify candidate patients who may benefit from an aggressive radical surgery.

Abstract

We performed a pilot study to evaluate the use of MRI delta texture analysis (D-TA) as a methodological item able to predict the frequency of complete pathological responses and, consequently, the outcome of patients with locally advanced rectal cancer addressed to neoadjuvant chemoradiotherapy (C-RT) and subsequently, to radical surgery. In particular, we carried out a retrospective analysis including 100 patients with locally advanced rectal adenocarcinoma who received C-RT and then radical surgery in three different oncological institutions between January 2013 and December 2019. Our experimental design was focused on the evaluation of the gross tumor volume (GTV) at baseline and after C-RT by means of MRI, which was contoured on T2, DWI, and ADC sequences. Multiple texture parameters were extracted by using a LifeX Software, while D-TA was calculated as percentage of variations in the two time points. Both univariate and multivariate analysis (logistic regression) were, therefore, carried out in order to correlate the above-mentioned TA parameters with the frequency of pathological responses in the examined patients’ population focusing on the detection of complete pathological response (pCR, with no viable cancer cells: TRG 1) as main statistical endpoint. ROC curves were performed on three different datasets considering that on the 21 patients, only 21% achieved an actual pCR. In our training dataset series, pCR frequency significantly correlated with ADC GLCM-Entropy only, when univariate and binary logistic analysis were performed (AUC for pCR was 0.87). A confirmative binary logistic regression analysis was then repeated in the two remaining validation datasets (AUC for pCR was 0.92 and 0.88, respectively). Overall, these results support the hypothesis that D-TA may have a significant predictive value in detecting the occurrence of pCR in our patient series. If confirmed in prospective and multicenter trials, these results may have a critical role in the selection of patients with locally advanced rectal cancer who may benefit form radical surgery after neoadjuvant chemoradiotherapy.

Imaging Features of Main Posthepatectomy Complications: A Radiologist’s Challenge

In the recent years, the number of liver resections has seen an impressive growth. Usually, hepatic resections remain the treatment of various liver diseases, such as malignant tumors, benign tumors, hydatid disease, and abscesses. Despite technical advancements and tremendous experience in the field of liver resection of specialized centers, there are moderately high rates of postoperative morbidity and mortality, especially in high-risk and older patient populations. Although ultrasonography is usually the first-line imaging examination for postoperative complications, Computed Tomography (CT) is the imaging tool of choice in emergency settings due to its capability to assess the whole body in a few seconds and detect all possible complications. Magnetic resonance cholangiopancreatography (MRCP) is the imaging modality of choice for delineating early postoperative bile duct injuries and ischemic cholangitis that may arise in the late postoperative phase. Moreover, both MDCT and MRCP can precisely detect tumor recurrence. Consequently, radiologists should have knowledge of these surgical procedures for better comprehension of postoperative changes and recognition of the radiological features of various postoperative complications.

Complications Risk Assessment and Imaging Findings of Thermal Ablation Treatment in Liver Cancers: What the Radiologist Should Expect

One of the major fields of application of ablation treatment is liver tumors. With respect to HCC, ablation treatments are considered as upfront treatments in patients with early-stage disease, while in colorectal liver metastases (CLM), they can be employed as an upfront treatment or in association with surgical resection. The main prognostic feature of ablation is the tumor size, since the goal of the treatment is the necrosis of all viable tumor tissue with an adequate tumor-free margin. Radiofrequency ablation (RFA) and microwave ablation (MWA) are the most employed ablation techniques. Ablation therapies in HCC and liver metastases have presented a challenge to radiologists, who need to assess response to determine complication-related treatment. Complications, defined as any unexpected variation from a procedural course, and adverse events, defined as any actual or potential injury related to the treatment, could occur either during the procedure or afterwards. To date, RFA and MWA have shown no statistically significant differences in mortality rates or major or minor complications. To reduce the rate of major complications, patient selection and risk assessment are essential. To determine the right cost-benefit ratio for the ablation method to be used, it is necessary to identify patients at high risk of infections, coagulation disorders and previous abdominal surgery interventions. Based on risk assessment, during the procedure as part of surveillance, the radiologists should pay attention to several complications, such as vascular, biliary, mechanical and infectious. Multiphase CT is an imaging tool chosen in emergency settings. The radiologist should report technical success, treatment efficacy, and complications. The complications should be assessed according to well-defined classification systems, and these complications should be categorized consistently according to severity and time of occurrence.

Lymph Nodes Evaluation in Rectal Cancer: Where Do We Stand and Future Perspective

The assessment of nodal involvement in patients with rectal cancer (RC) is fundamental in disease management. Magnetic Resonance Imaging (MRI) is routinely used for local and nodal staging of RC by using morphological criteria. The actual dimensional and morphological criteria for nodal assessment present several limitations in terms of sensitivity and specificity. For these reasons, several different techniques, such as Diffusion Weighted Imaging (DWI), Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Dynamic Contrast Enhancement (DCE) in MRI have been introduced but still not fully validated. Positron Emission Tomography (PET)/CT plays a pivotal role in the assessment of LNs; more recently PET/MRI has been introduced. The advantages and limitations of these imaging modalities will be provided in this narrative review. The second part of the review includes experimental techniques, such as iron-oxide particles (SPIO), and dual-energy CT (DECT). Radiomics analysis is an active field of research, and the evidence about LNs in RC will be discussed. The review also discusses the different recommendations between the European and North American guidelines for the evaluation of LNs in RC, from anatomical considerations to structured reporting.

Conventional, functional and radiomics assessment for intrahepatic cholangiocarcinoma

Background

This paper offers an assessment of diagnostic tools in the evaluation of Intrahepatic Cholangiocarcinoma (ICC).

Methods

Several electronic datasets were analysed to search papers on morphological and functional evaluation in ICC patients. Papers published in English language has been scheduled from January 2010 to December 2021.

Results

We found that 88 clinical studies satisfied our research criteria. Several functional parameters and morphological elements allow a truthful ICC diagnosis. The contrast medium evaluation, during the different phases of contrast studies, support the recognition of several distinctive features of ICC. The imaging tool to employed and the type of contrast medium in magnetic resonance imaging, extracellular or hepatobiliary, should change considering patient, departement, and regional features. Also, Radiomics is an emerging area in the evaluation of ICCs.

Post treatment studies are required to evaluate the efficacy and the safety of therapies so as the patient surveillance.

Conclusions

Several morphological and functional data obtained during Imaging studies allow a truthful ICC diagnosis.

Radiomics in medical imaging: pitfalls and challenges in clinical management

BACKGROUND

Radiomics and radiogenomics are two words that recur often in language of radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics is the technique of medical images analysis to extract quantitative data that are not detected by human eye.

METHODS

This article is a narrative review on Radiomics in Medical Imaging. In particular, the review exposes the process, the limitations related to radiomics, and future prospects are discussed.

RESULTS

Several studies showed that radiomics is very promising. However, there were some critical issues: poor standardization and generalization of radiomics results, data-quality control, repeatability, reproducibility, database balancing and issues related to model overfitting.

CONCLUSIONS

Radiomics procedure should made considered all pitfalls and challenges to obtain robust and reproducible results that could be generalized in other patients cohort.

Advanced Magnetic Resonance Imaging (MRI) Techniques: Technical Principles and Applications in Nanomedicine

Simple Summary

Magnetic Resonance Imaging (MRI) is a consolidated imaging tool for the multiparametric assessment of tissues in various pathologies from degenerative and inflammatory diseases to cancer. In recent years, the continuous technological evolution of the equipment has led to the development of sequences that provide not only anatomical but also functional and metabolic information. In addition, there is a growing and emerging field of research in clinical applications using MRI to exploit the diagnostic and therapeutic capabilities of nanocompounds. This review illustrates the application of the most advanced magnetic resonance techniques in the field of nanomedicine.

Abstract

In the last decades, nanotechnology has been used in a wide range of biomedical applications, both diagnostic and therapeutic. In this scenario, imaging techniques represent a fundamental tool to obtain information about the properties of nanoconstructs and their interactions with the biological environment in preclinical and clinical settings. This paper reviews the state of the art of the application of magnetic resonance imaging in the field of nanomedicine, as well as the use of nanoparticles as diagnostic and therapeutic tools, especially in cancer, including the characteristics that hinder the use of nanoparticles in clinical practice.

Association Between DCE-MRI Perfusion Histogram Parameters and EGFR and VEGF Expressions in Different Lauren Classifications of Advanced Gastric Cancer

Objective: To investigate the correlations between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion histogram parameters and vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR) expressions in advanced gastric cancer (AGC).

Methods: This retrospective study included 80 pathologically confirmed patients with AGC who underwent DCE-MRI before surgery from February 2017 to May 2021. The DCE-MRI perfusion histogram parameters were calculated by Omni Kinetics software in four quantitative parameter maps. Immunohistochemical methods were used to detect VEGF and EGFR expressions and calculate the immunohistochemical score.

Results: VEGF expression was relatively lower in patients with intestinal-type AGC than those with diffuse-type AGC (p < 0.05). For VEGF, Receiver operating characteristics (ROC) curve analysis revealed that Quantile 90 of Ktrans, Meanvalue of Kep and Quantile 50 of Ve provided the perfect combination of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for distinguishing high and low VEGF expression, For EGFR, Skewness of Ktrans, Energy of Kep and Entropy of Vp provided the perfect combination of sensitivity, specificity, PPV and NPV for distinguishing high and low EGFR expression. Ktrans (Quantile 90, Entropy) showed the strongest correlation with VEGF and EGFR in patients with intestinal-type AGC (r = 0.854 and r = 0.627, respectively); Ktrans (Mean value, Entropy) had the strongest correlation with VEGF and EGFR in patients with diffuse-type AGC (r = 0.635 and 0.656, respectively).

Conclusion: DCE-MRI perfusion histogram parameters can serve as imaging biomarkers to reflect VEGF and EGFR expressions and estimate their difference in different Lauren classifications of AGC.

Diagnostic evaluation and ablation treatments assessment in hepatocellular carcinoma

This article provides an overview of diagnostic evaluation and ablation treatment assessment in Hepatocellular Carcinoma (HCC). Only studies, in the English language from January 2010 to January 202, evaluating the diagnostic tools and assessment of ablative therapies in HCC patients were included. We found 173 clinical studies that satisfied the inclusion criteria.HCC may be noninvasively diagnosed by imaging findings. Multiphase contrast-enhanced imaging is necessary to assess HCC. Intravenous extracellular contrast agents are used for CT, while the agents used for MRI may be extracellular or hepatobiliary. Both gadoxetate disodium and gadobenate dimeglumine may be used in hepatobiliary phase imaging. For treatment-naive patients undergoing CT, unenhanced imaging is optional; however, it is required in the post treatment setting for CT and all MRI studies. Late arterial phase is strongly preferred over early arterial phase. The choice of modality (CT, US/CEUS or MRI) and MRI contrast agent (extracelllar or hepatobiliary) depends on patient, institutional, and regional factors. MRI allows to link morfological and functional data in the HCC evaluation. Also, Radiomics is an emerging field in the assessment of HCC patients.Postablation imaging is necessary to assess the treatment results, to monitor evolution of the ablated tissue over time, and to evaluate for complications. Post- thermal treatments, imaging should be performed at regularly scheduled intervals to assess treatment response and to evaluate for new lesions and potential complications.

Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment

INTRODUCTION

Neoadjuvant radiotherapy is currently used mainly in locally advanced rectal cancer and sarcoma and in a subset of non-small cell lung cancer and esophageal cancer, whereas in other diseases it is under investigation. The evaluation of the efficacy of the induction strategy is made possible by performing imaging investigations before and after the neoadjuvant therapy and is usually challenging. In the last decade, texture analysis (TA) has been developed to help the radiologist to quantify and identify the parameters related to tumor heterogeneity, which cannot be appreciated by the naked eye. The aim of this narrative is to review the impact of TA on the prediction of response to neoadjuvant radiotherapy and or chemoradiotherapy.

MATERIALS AND METHODS

Key references were derived from a PubMed query. Hand searching and ClinicalTrials.gov were also used.

RESULTS

This paper contains a narrative report and a critical discussion of radiomics approaches in different fields of neoadjuvant radiotherapy, including esophageal cancer, lung cancer, sarcoma, and rectal cancer.

CONCLUSIONS

Radiomics can shed a light on the setting of neoadjuvant therapies that can be used to tailor subsequent approaches or even to avoid surgery in the future. At the same, these results need to be validated in prospective and multicenter trials.

Preoperative histogram parameters of dynamic contrast-enhanced MRI as a potential imaging biomarker for assessing the expression of Ki-67 in prostate cancer

Purpose

To investigate whether preoperative histogram parameters of dynamic contrast‐enhanced MRI (DCE‐MRI) can assess the expression of Ki‐67 in prostate cancer (PCa).

Materials and methods

A consecutive series of 76 patients with pathology‐proven PCa who underwent routine DCE‐MRI scans were retrospectively recruited. Quantitative parameters including the volume transfer constant (K^trans), rate contrast (K_ep), extracellular‐extravascular volume fraction (V_e), and plasma volume (V_p) by outlining the three‐dimensional volume of interest (VOI) of all lesions were processed. Then, the histogram analyses of these quantitative parameters were performed. The Spearman rank correlation analysis was used to evaluate the correlation of these parameters and Ki‐67 expression of PCa. Receiver operating characteristic (ROC) curve analysis was adopted to evaluate the efficacy of these quantitative histogram parameters in identifying high Ki‐67 expression from low Ki‐67 expression of PCa.

Results

Eighty‐eight PCa lesions were enrolled in this study, including 31 lesions with high Ki‐67 expression and 57 lesions with low Ki‐67 expression. The median, mean, 75th percentile, and 90th percentile derived from K^trans and K_ep had a moderately positive correlation with Ki‐67 expression (r = 0.361–0.450, p < 0.05), in which both the median and mean of K^trans had the highest positive correlation (r = 0.450, p < 0.05). The diagnostic efficacy of the K^trans median, mean, 75th percentile, and 90th percentile, along with the K_ep‐based median and mean was assessed by the ROC curve. The area under the curve (AUC) of the mean for K^trans was the highest (0.826). When the cut‐off of the mean for K^trans was ≥0.47/min, its Youden index, sensitivity, and specificity were 0.625, 0.871, and 0.754, respectively. The AUC of the median of K_ep was the lowest (0.772).

Conclusion

The histogram of DCE‐MRI quantitative parameters is correlated with Ki‐67 expression, which has the potential to noninvasively assess the expression of Ki‐67 with patients of PCa.

Imaging side effects and complications of chemotherapy and radiation therapy: a pictorial review from head to toe

Newer biologic drugs and immunomodulatory agents, as well as more tolerated and effective radiation therapy schemes, have reduced treatment toxicity in oncology patients. However, although imaging assessment of tumor response is adapting to atypical responses like tumor flare, expected changes and complications of chemo/radiotherapy are still routinely encountered in post-treatment imaging examinations. Radiologists must be aware of old and newer therapeutic options and related side effects or complications to avoid a misinterpretation of imaging findings. Further, advancements in oncology research have increased life expectancy of patients as well as the frequency of long-term therapy-related side effects that once could not be observed. This pictorial will help radiologists tasked to detect therapy-related complications and to differentiate expected changes of normal tissues from tumor relapse.