The Role of T2 Mapping in Cardiac Amyloidosis.

Cardiac amyloidosis (CA) is an infiltrative cardiomyopathy divided into two types: light-chain (LA) and transthyretin (ATTR) CA. Cardiac magnetic resonance (CMR) has emerged as an important diagnostic tool in CA. While late gadolinium enhancement (LGE), T1 mapping and extracellular volume (ECV) have a consolidate role in the assessment of CA, T2 mapping has been less often evaluated. We aimed to test the value of T2 mapping in the evaluation of CA. This study recruited 70 patients with CA (51 ATTR, 19 AL). All the subjects underwent 1.5 T CMR with T1 and T2 mapping and cine and LGE imaging. Their QALE scores were evaluated. The myocardial T2 values were significantly (p < 0.001) increased in both types of CA compared to the controls. In the AL-CA group, increased T2 values were associated with a higher QALE score. The myocardial native T1 values and ECV were significantly (p < 0.001) higher in the CA patients than in the healthy subjects. Left ventricular (LV) mass, QALE score and ECV were higher in ATTR amyloidosis compared with AL amyloidosis, while the LV ejection fraction was lower (p < 0.001). These results support the concept of the presence of myocardial edema in CA. Therefore, a CMR evaluation including not only myocardial T1 imaging but also myocardial T2 imaging allows for more comprehensive tissue characterization in CA.

Focal Lesions of the Liver and Radiomics: What Do We Know?

Despite differences in pathological analysis, focal liver lesions are not always distinguishable in contrast-enhanced magnetic resonance imaging (MRI), contrast-enhanced computed tomography (CT), and positron emission tomography (PET). This issue can cause problems of differential diagnosis, treatment, and follow-up, especially in patients affected by HBV/HCV chronic liver disease or fatty liver disease. Radiomics is an innovative imaging approach that extracts and analyzes non-visible quantitative imaging features, supporting the radiologist in the most challenging differential diagnosis when the best-known methods are not conclusive. The purpose of this review is to evaluate the most significant CT and MRI texture features, which can discriminate between the main benign and malignant focal liver lesions and can be helpful to predict the response to pharmacological or surgical therapy and the patient's prognosis.

Local Recurrences in Rectal Cancer: MRI vs. CT.

Rectal cancers are often considered a distinct disease from colon cancers as their survival and management are different. Particularly, the risk for local recurrence (LR) is greater than in colon cancer. There are many factors predisposing to LR such as postoperative histopathological features or the mesorectal plane of surgical resection. In addition, the pattern of LR in rectal cancer has a prognostic significance and an important role in the choice of operative approach and. Therefore, an optimal follow up based on imaging is critical in rectal cancer. The aim of this review is to analyse the risk and the pattern of local recurrences in rectal cancer and to provide an overview of the role of imaging in early detection of LRs. We performed a literature review of studies published on Web of Science and MEDLINE up to January 2023. We also reviewed the current guidelines of National Comprehensive Cancer Network (NCCN) and the European Society for Medical Oncology (ESMO). Although the timing and the modality of follow-up is not yet established, the guidelines usually recommend a time frame of 5 years post surgical resection of the rectum. Computed Tomography (CT) scans and/or Magnetic Resonance Imaging (MRI) are the main imaging techniques recommended in the follow-up of these patients. PET-CT is not recommended by guidelines during post-operative surveillance and it is generally used for problem solving.

Practical Guide to Interpreting Cardiac Magnetic Resonance in Patients with Cardiac Masses.

It is common for a cardiac mass to be discovered accidentally during an echocardiographic examination. Following the relief of a cardiac mass, being able to evaluate and characterize it using non-invasive imaging methods is critical. Echocardiography, computed tomography (CT), cardiac magnetic resonance imaging (CMR), and positron emission tomography (PET) are the main imaging modalities used to evaluate cardiac masses. Although multimodal imaging often allows for a better assessment, CMR is the best technique for the non-invasive characterization of tissues, as the different MR sequences help in the diagnosis of cardiac masses. This article provides detailed descriptions of each CMR sequence employed in the evaluation of cardiac masses, underlining the potential information it can provide. The description in the individual sequences provides useful guidance to the radiologist in performing the examination.

Imaging in Hepatocellular Carcinoma: What's New?

Hepatocellular carcinoma (HCC) is the most common liver cancer and is one of the uppermost 2 causes of cancer death. About 70%-90% of HCCs develop within a cirrhotic liver. According to the most recent guidelines, the imaging characteristics of HCC on contrast-enhanced Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) are generally satisfactory to make a diagnosis. Recently, new advanced techniques such as contrast-enhanced ultrasound, CT perfusion, Dynamic Contrast-enhanced MRI, diffusion weighted imaging and radiomics have increased the diagnostic accuracy and characterization of HCC. This review illustrates the state of the art and recent advances in non-invasive imaging evaluation of HCC.

Branch duct-intraductal papillary mucinous neoplasms (BD-IPMNs): an MRI-based radiomic model to determine the malignant degeneration potential.

BACKGROUND: Branch duct-intraductal papillary mucinous neoplasms (BD-IPMNs) are the most common pancreatic cystic tumors and have a low risk of malignant transformation. Features able to early identify high-risk BD-IPMNs are lacking, and guidelines currently rely on the occurrence of worrisome features (WF) and high-risk stigmata (HRS). AIM: In our study, we aimed to use a magnetic resonance imaging (MRI) radiomic model to identify features linked to a higher risk of malignant degeneration, and whether these appear before the occurrence of WF and HRS. METHODS: We retrospectively evaluated adult patients with a known BD-IPMN who had had at least two contrast-enhanced MRI studies at our center and a 24-month minimum follow-up time. MRI acquisition protocol for the two examinations included pre- and post-contrast phases and diffusion-weighted imaging (DWI)/apparent diffusion coefficient (ADC) map. Patients were divided into two groups according to the development of WF or HRS at the end of the follow-up (Group 0 = no WF or HRS; Group 1 = WF or HRS). We segmented the MRI images and quantitative features were extracted and compared between the two groups. Features that showed significant differences (SF) were then included in a LASSO regression method to build a radiomic-based predictive model. RESULTS: We included 50 patients: 31 in Group 0 and 19 in Group 1. No patients in this cohort developed HRS. At baseline, 47, 67, 38, and 68 SF were identified for pre-contrast T1-weighted (T1-W) sequence, post-contrast T1-W sequence, T2-weighted (T2- W) sequence, and ADC map, respectively. At the end of follow-up, we found 69, 78, 53, and 91 SF, respectively. The radiomic-based predictive model identified 16 SF: more particularly, 5 SF for pre-contrast T1-W sequence, 6 for post-contrast T1-W sequence, 3 for T2-W sequence, and 2 for ADC. CONCLUSION: We identified radiomic features that correlate significantly with WF in patients with BD-IPMNs undergoing contrast-enhanced MRI. Our MRI-based radiomic model can predict the occurrence of WF.

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 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.

Imaging of metabolic and overload disorders in tissues and organs.

Metabolic and overload disorders are a heterogeneous group of relatively uncommon but important diseases. While imaging plays a key role in the early detection and accurate diagnosis in specific organs with a pivotal role in several metabolic pathways, most of these diseases affect different tissues as part of a systemic syndromes. Moreover, since the symptoms are often vague and phenotypes similar, imaging alterations can present as incidental findings, which must be recognized and interpreted in the light of further biochemical and histological investigations. Among imaging modalities, MRI allows, thanks to its multiparametric properties, to obtain numerous information on tissue composition, but many metabolic and accumulation alterations require a multimodal evaluation, possibly using advanced imaging techniques and sequences, not only for the detection but also for accurate characterization and quantification. The purpose of this review is to describe the different alterations resulting from metabolic and overload pathologies in organs and tissues throughout the body, with particular reference to imaging findings.

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs): a radiomic model to predict tumor grade.

PURPOSE: The aim of this single-center retrospective study is to assess whether contrast-enhanced computed tomography (CECT) radiomics analysis is predictive of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) grade based on the 2019 World Health Organization (WHO) classification and to establish a tumor grade (G) prediction model. MATERIAL AND METHODS: Preoperative CECT images of 78 patients with GEP-NENs were retrospectively reviewed and divided in two groups (G1-G2 in class 0, G3-NEC in class 1). A total of 107 radiomics features were extracted from each neoplasm ROI in CT arterial and venous phases acquisitions with 3DSlicer. Mann-Whitney test and LASSO regression method were performed in R for feature selection and feature reduction, in order to build the radiomic-based predictive model. The model was developed for a training cohort (75% of the total) and validated on the independent validation cohort (25%). ROC curves and AUC values were generated on training and validation cohorts. RESULTS: 40 and 24 features, for arterial phase and venous phase, respectively, were found to be significant in class distinction. From the LASSO regression 3 and 2 features, for arterial phase and venous phase, respectively, were identified as suitable for groups classification and used to build the tumor grade radiomic-based prediction model. The prediction of the arterial model resulted in AUC values of 0.84 (95% CI 0.72-0.97) and 0.82 (95% CI 0.62-1) for the training cohort and validation cohort, respectively, while the prediction of the venous model yielded AUC values of 0.7877 (95% CI 0.6416-0.9338) and 0.6813 (95% CI 0.3933-0.9693) for the training cohort and validation cohort, respectively. CONCLUSIONS: CT-radiomics analysis may aid in differentiating the histological grade for GEP-NENs.

Combined Hepatocellular-Cholangiocarcinoma: What the Multidisciplinary Team Should Know.

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare type of primary liver malignancy. Among the risk factors, hepatitis B and hepatitis C virus infections, cirrhosis, and male gender are widely reported. The clinical appearance of cHCC-CCA is similar to that of HCC and iCCA and it is usually silent until advanced states, causing a delay of diagnosis. Diagnosis is mainly based on histology from biopsies or surgical specimens. Correct pre-surgical diagnosis during imaging studies is very problematic and is due to the heterogeneous characteristics of the lesion in imaging, with overlapping features of HCC and CCA. The predominant histological subtype within the lesion establishes the predominant imaging findings. Therefore, in this scenario, the radiological findings characteristic of HCC show an overlap with those of CCA. Since cHCC-CCAs are prevalent in patients at high risk of HCC and there is a risk that these may mimic HCC, it is currently difficult to see a non-invasive diagnosis of HCC. Surgery is the only curative treatment of HCC-CCA. The role of liver transplantation (LT) in the treatment of cHCC-CCA remains controversial, as is the role of ablative or systemic therapies in the treatment of this tumour. These lesions still remain challenging, both in diagnosis and in the treatment phase. Therefore, a pre-treatment imaging diagnosis is essential, as well as the identification of prognostic factors that could stratify the risk of recurrence and the most adequate therapy according to patient characteristics.

FLORA software: semi-automatic LGE-CMR analysis tool for cardiac lesions identification and characterization.

PURPOSE: Today there is a growing interest in the quantification of late gadolinium enhancement (LGE) in ischemic and non-ischemic cardiac pathologies. We build an automatic self-made free software FLORA (For Late gadOlinium enhanced aReas clAssification) for the recognition, classification and quantification of LGE areas that allows to improve the observer's performances and that homogenizes the evaluations between different operators. MATERIAL AND METHODS: We have retrospectively selected 120 CMR exams: 40-ischemic with evident scar tissue on LGE sequences; 40-non-ischemic cardiomyopathy; 40-any myocardial alteration on CMR, especially on LGE sequences. FLORA's performance was compared to the radiologist's evaluation. RESULTS: FLORA identified both ischemic and non-ischemic myocardial lesions in almost all cases (80/80 and 79/80 for the double-Gaussian fit method and fixed-shift method, respectively, with sensitivity and specificity of 100%/98.8% and 55%/50%, respectively). The best results were obtained from the classification of ischemic myocardial damage, which was correctly identified in 85%-95% of cases. FLORA also increases the agreement between observers and allows a quantitative evaluation of transmurality. CONCLUSIONS: FLORA has proven to be an applicable tool that improves and facilitates the classification of LGE areas allowing their quantification.

An update on radiomics techniques in primary liver cancers.

BACKGROUND: Radiomics is a progressing field of research that deals with the extraction of quantitative metrics from medical images. Radiomic features detention indirectly tissue features such as heterogeneity and shape and can, alone or in combination with demographic, histological, genomic, or proteomic data, be used for decision support system in clinical setting. METHODS: This article is a narrative review on Radiomics in Primary Liver Cancers. Particularly, limitations and future perspectives are discussed. RESULTS: In oncology, assessment of tissue heterogeneity is of particular interest: genomic analysis have demonstrated that the degree of tumour heterogeneity is a prognostic determinant of survival and an obstacle to cancer control. Therefore, that Radiomics could support cancer detection, diagnosis, evaluation of prognosis and response to treatment, so as could supervise disease status in hepatocellular carcinoma (HCC) and Intrahepatic Cholangiocarcinoma (ICC) patients. Radiomic analysis is a convenient radiological image analysis technique used to support clinical decisions as it is able to provide prognostic and / or predictive biomarkers that allow a fast, objective and repeatable tool for disease monitoring. CONCLUSIONS: Although several studies have shown that this analysis is very promising, there is little standardization and generalization of the results, which limits the translation of this method into the clinical context. The limitations are mainly related to the evaluation of data quality, repeatability, reproducibility, overfitting of the model. TRIAL REGISTRATION: Not applicable.

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.

Acute Pulmonary Embolism: Prognostic Role of Computed Tomography Pulmonary Angiography (CTPA).

Computed Tomography Pulmonary Angiography (CTPA) is considered the gold standard diagnostic technique in patients with suspected acute pulmonary embolism in emergency departments. Several studies have been conducted on the predictive value of CTPA on the outcomes of pulmonary embolism (PE). The purpose of this article is to provide an updated review of the literature reporting imaging parameters and quantitative CT scores to predict the severity of PE.

Errors in MDCT diagnosis of acute mesenteric ischemia.

The causes of diagnostic errors during daily medical practice can be several, mainly attributable to perceptual, interpretive and communication factors. The eventuality of radiological error is much more amplified in the emergency setting where a high number of complex multidetector-row computed tomography (MDCT) images must be evaluated quickly and critical time decisions need to be taken. In particular, in this context, the diagnosis of vascular intestinal diseases represents a crucial and difficult challenge in case of acute abdominal pain given the importance of being able to identify patient with high suspicious for intestinal ischemia and for a specific patient to judge if his ischemia is reversible or irreversible. Awareness of potential biases which can lead to diagnostic errors together with an extensive knowledge of the imaging features of these pathologies can lead to promptly recognize them with fewer mistakes, improving patients' outcome. This article reviews the MDCT findings of acute intestinal ischemia and acute colonic ischemia and analyzes the main types of diagnostic errors, underlining the importance of being familiarized with them to avoid misdiagnosis.

Structured reporting of computed tomography in the staging of colon cancer: a Delphi consensus proposal.

BACKGROUND: Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports in colon cancer during the staging phase in order to improve communication between the radiologist, members of multidisciplinary teams and patients. MATERIALS AND METHODS: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. RESULTS: The final SR version was built by including n = 18 items in the "Patient Clinical Data" section, n = 7 items in the "Clinical Evaluation" section, n = 9 items in the "Imaging Protocol" section and n = 29 items in the "Report" section. Overall, 63 items were included in the final version of the SR. Both in the first and second round, all sections received a higher than good rating: a mean value of 4.6 and range 3.6-4.9 in the first round; a mean value of 5.0 and range 4.9-5 in the second round. In the first round, Cronbach's alpha (Cα) correlation coefficient was a questionable 0.61. In the first round, the overall mean score of the experts and the sum of scores for the structured report were 4.6 (range 1-5) and 1111 (mean value 74.07, STD 4.85), respectively. In the second round, Cronbach's alpha (Cα) correlation coefficient was an acceptable 0.70. In the second round, the overall mean score of the experts and the sum of score for structured report were 4.9 (range 4-5) and 1108 (mean value 79.14, STD 1.83), respectively. The overall mean score obtained by the experts in the second round was higher than the overall mean score of the first round, with a lower standard deviation value to underline greater agreement among the experts for the structured report reached in this round. CONCLUSIONS: A wide implementation of SR is of critical importance in order to offer referring physicians and patients optimum quality of service and to provide researchers with the best quality data in the context of big data exploitation of available clinical data. Implementation is a complex procedure, requiring mature technology to successfully address the multiple challenges of user-friendliness, organization and interoperability.

Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging.

Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.

Structured Reporting of Computed Tomography in the Staging of Neuroendocrine Neoplasms: A Delphi Consensus Proposal.

Background: Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports in Neuroendocrine Neoplasms during the staging phase in order to improve communication between the radiologist and members of multidisciplinary teams. Materials and Methods: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A Modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. Results: The final SR version was built by including n=16 items in the "Patient Clinical Data" section, n=13 items in the "Clinical Evaluation" section, n=8 items in the "Imaging Protocol" section, and n=17 items in the "Report" section. Overall, 54 items were included in the final version of the SR. Both in the first and second round, all sections received more than a good rating: a mean value of 4.7 and range of 4.2-5.0 in the first round and a mean value 4.9 and range of 4.9-5 in the second round. In the first round, the Cα correlation coefficient was a poor 0.57: the overall mean score of the experts and the sum of scores for the structured report were 4.7 (range 1-5) and 728 (mean value 52.00 and standard deviation 2.83), respectively. In the second round, the Cα correlation coefficient was a good 0.82: the overall mean score of the experts and the sum of scores for the structured report were 4.9 (range 4-5) and 760 (mean value 54.29 and standard deviation 1.64), respectively. Conclusions: The present SR, based on a multi-round consensus-building Delphi exercise following in-depth discussion between expert radiologists in gastro-enteric and oncological imaging, derived from a multidisciplinary agreement between a radiologist, medical oncologist and surgeon in order to obtain the most appropriate communication tool for referring physicians.

Structured Reporting of Computed Tomography and Magnetic Resonance in the Staging of Pancreatic Adenocarcinoma: A Delphi Consensus Proposal.

BACKGROUND: Structured reporting (SR) in radiology has been recognized recently by major scientific societies. This study aims to build structured computed tomography (CT) and magnetic resonance (MR)-based reports in pancreatic adenocarcinoma during the staging phase in order to improve communication between the radiologist and members of multidisciplinary teams. MATERIALS AND METHODS: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi process was used to develop the CT-SR and MRI-SR, assessing a level of agreement for all report sections. Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. RESULTS: The final CT-SR version was built by including n = 16 items in the "Patient Clinical Data" section, n = 11 items in the "Clinical Evaluation" section, n = 7 items in the "Imaging Protocol" section, and n = 18 items in the "Report" section. Overall, 52 items were included in the final version of the CT-SR. The final MRI-SR version was built by including n = 16 items in the "Patient Clinical Data" section, n = 11 items in the "Clinical Evaluation" section, n = 8 items in the "Imaging Protocol" section, and n = 14 items in the "Report" section. Overall, 49 items were included in the final version of the MRI-SR. In the first round for CT-SR, all sections received more than a good rating. The overall mean score of the experts was 4.85. The Cα correlation coefficient was 0.85. In the second round, the overall mean score of the experts was 4.87, and the Cα correlation coefficient was 0.94. In the first round, for MRI-SR, all sections received more than a good rating. The overall mean score of the experts was 4.73. The Cα correlation coefficient was 0.82. In the second round, the overall mean score of the experts was 4.91, and the Cα correlation coefficient was 0.93. CONCLUSIONS: The CT-SR and MRI-SR are based on a multi-round consensus-building Delphi exercise derived from the multidisciplinary agreement of expert radiologists in order to obtain more appropriate communication tools for referring physicians.