Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate cancer

Background and Objective

In recent years, magnetic resonance imaging (MRI) has shown excellent results in the study of the prostate gland. MRI has indeed shown to be advantageous in the prostate cancer (PCa) detection, as in guiding targeting biopsy, improving its diagnostic yield. Although current acquisition protocols provide for multiparametric acquisition, recent evidence has shown that biparametric protocols can be non-inferior in PCa detection. Diffusion-weighted imaging (DWI) sequence, in particular, plays a key role, particularly in the peripheral zone which accounts for the larger part of the prostate. High b-values are generally recommended, although with the possibility of obtaining non-Gaussian diffusion effects, which requires a more sophisticated model for the analysis, namely through the diffusion kurtosis imaging (DKI). Purpose of this narrative review was to analyze the current applications and clinical evidence regarding the use of DKI with a main focus on PCa detection, also in comparison with DWI.

Methods

This narrative review synthesized the findings of literature retrieved from main researches, narrative and systematic reviews, and meta-analyses obtained from PubMed.

Key Content and Findings

DKI analyses the non-Gaussian water diffusivity and describe the effect of signal intensity decay related to high b-value through two main metrics (Dapp and Kapp). Differently from DWI-apparent diffusion coefficient (DWI-ADC) which reflects only water restriction outside of cells, DKI metrics are supposed to represent also the direct interaction of water molecules with cell membranes and intracellular compounds. This review describes current evidence on ADC and DKI metrics in clinical imaging, and finally collect the results derived from the main articles focused on DWI and DKI models in detecting PCa.

Conclusions

DKI advantages, compared to conventional ADC analysis, still remain controversial. Wider application and greater technical knowledge of DKI, however, may help in proving its intrinsic validity in the field of oncology and therefore in the study of clinically significant PCa. Finally, a deep understanding of DKI is important for radiologists to better understand what Kapp and Dapp mean in the context of different cancer and how these metrics may vary specifically in PCa imaging.

Imaging of human papilloma virus (HPV) related oropharynx tumour: what we know to date

The tumours of head and neck district are around 3% of all malignancies and squamous cell carcinoma is the most frequent histotype, with rapid increase during the last two decades because of the increment of the infection due to human papilloma virus (HPV). Even if the gold standard for the diagnosis is histological examination, including the detection of viral DNA and transcription products, imaging plays a fundamental role in the detection and staging of HPV + tumours, in order to assess the primary tumour, to establish the extent of disease and for follow-up. The main diagnostic tools are Computed Tomography (CT), Positron Emission Tomography-Computed Tomography (PET-CT) and Magnetic Resonance Imaging (MRI), but also Ultrasound (US) and the use of innovative techniques such as Radiomics have an important role. Aim of our review is to illustrate the main imaging features of HPV + tumours of the oropharynx, in US, CT and MRI imaging. In particular, we will outline the main limitations and strengths of the various imaging techniques, the main uses in the diagnosis, staging and follow-up of disease and the fundamental differential diagnoses of this type of tumour. Finally, we will focus on the innovative technique of texture analysis, which is increasingly gaining importance as a diagnostic tool in aid of the radiologist.

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.

Radiomic Features Are Predictive of Response in Rectal Cancer Undergoing Therapy

BACKGROUND

Rectal cancer is a major mortality cause in the United States (US), and its treatment is based on individual risk factors for recurrence in each patient. In patients with rectal cancer, accurate assessment of response to chemoradiotherapy has increased in importance as the variety of treatment options has grown. In this scenario, a controversial non-operative approach may be considered in some patients for whom complete tumor regression is believed to have occurred. The recommended treatment for locally advanced rectal cancer (LARC, T3-4 ± N+) is total mesorectal excision (TME) after neoadjuvant chemoradiotherapy (nCRT). Magnetic resonance imaging (MRI) has become a standard technique for local staging of rectal cancer (tumor, lymph node, and circumferential resection margin [CRM] staging), in both the US and Europe, and it is getting widely used for restaging purposes.

AIM

In our study, we aimed to use an MRI radiomic model to identify features linked to the different responses of chemoradiotherapy of rectal cancer before surgery, and whether these features are helpful to understand the effectiveness of the treatments.

METHODS

We retrospectively evaluated adult patients diagnosed with LARC who were subjected to at least 2 MRI examinations in 10-12 weeks at our hospital, before and after nCRT. The MRI acquisition protocol for the 2 exams included T2 sequence and apparent diffusion coefficient (ADC) map. The patients were divided into 2 groups according to the treatment response: complete or good responders (Group 1) and incomplete or poor responders (Group 2). MRI images were segmented, 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 38 patients (26 males and 12 females), who are classified from T2 and T4 stages in the rectal cancer TNM. After the nCRT, the patients were divided into Group 1 (13 patients), complete or good responders, and Group 2 (25 patients), incomplete or poor responders. Analysis at baseline generated the following significant features for the Mann-Whitney test (out of a total of 107) for each sequence. Also, the analysis at the end of the follow-up yielded a high number of significant features for the Mann-Whitney test (out of a total of 107) for each image. Features selected by the LASSO regression method for each image analyzed; ROC curves relative to each model are represented.

CONCLUSION

We developed an MRI-based radiomic model that is able to differentiate and predict between responders and non-responders who went through nCRT for rectal cancer. This approach might identify early lesions with high surgical potential from lesions potentially resolving after medical treatment.

Magnetic resonance imaging in naso-oropharyngeal carcinoma: role of texture analysis in the assessment of response to radiochemotherapy, a preliminary study

OBJECTIVE

Identifying MRI texture parameters able to distinguish inflammation, fibrosis, and residual cancer in patients with naso-oropharynx carcinoma after radiochemotherapy (RT-CHT).

MATERIAL AND METHODS

In this single-centre, observational, retrospective study, texture analysis was performed on ADC maps and post-gadolinium T1 images of patients with histological diagnosis of naso-oropharyngeal carcinoma treated with RT-CHT. An initial cohort of 99 patients was selected; 57 of them were later excluded. The final cohort of 42 patients was divided into 3 groups (inflammation, fibrosis, and residual cancer) according to MRI, 18F-FDG-PET/CT performed 3-4 months after RT-CHT, and biopsy. Pre-RT-CHT lesions and the corresponding anatomic area post-RT-CHT were segmented with 3D slicer software from which 107 textural features were derived. T-Student and Wilcoxon signed-rank tests were performed, and features with p-value < 0.01 were considered statistically significant. Cut-off values-obtained by ROC curves-to discriminate post-RT-CHT non-tumoural changes from residual cancer were calculated for the parameters statistically associated to the diseased status at follow-up.

RESULTS

Two features-Energy and Grey Level Non-Uniformity-were statistically significant on T1 images in the comparison between 'positive' (residual cancer) and 'negative' patients (inflammation and fibrosis). Energy was also found to be statistically significant in both patients with fibrosis and residual cancer. Grey Level Non-Uniformity was significant in the differentiation between residual cancer and inflammation. Five features were statistically significant on ADC maps in the differentiation between 'positive' and 'negative' patients. The reduction in values of such features between pre- and post-RT-CHT was correlated with a good response to therapy.

CONCLUSIONS

Texture analysis on post-gadolinium T1 images and ADC maps can differentiate residual cancer from fibrosis and inflammation in early follow-up of naso-oropharyngeal carcinoma treated with RT-CHT.

Tips and Tricks in Thoracic Radiology for Beginners: A Findings-Based Approach

This review has the purpose of illustrating schematically and comprehensively the key concepts for the beginner who approaches chest radiology for the first time. The approach to thoracic imaging may be challenging for the beginner due to the wide spectrum of diseases, their overlap, and the complexity of radiological findings. The first step consists of the proper assessment of the basic imaging findings. This review is divided into three main districts (mediastinum, pleura, focal and diffuse diseases of the lung parenchyma): the main findings will be discussed in a clinical scenario. Radiological tips and tricks, and relative clinical background, will be provided to orient the beginner toward the differential diagnoses of the main thoracic diseases.

A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia

BACKGROUND

The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widely recognized. We evaluated the performance of a software for quantitative analysis of chest CT, the LungQuant system, by comparing its results with independent visual evaluations by a group of 14 clinical experts. The aim of this work is to evaluate the ability of the automated tool to extract quantitative information from lung CT, relevant for the design of a diagnosis support model.

METHODS

LungQuant segments both the lungs and lesions associated with COVID-19 pneumonia (ground-glass opacities and consolidations) and computes derived quantities corresponding to qualitative characteristics used to clinically assess COVID-19 lesions. The comparison was carried out on 120 publicly available CT scans of patients affected by COVID-19 pneumonia. Scans were scored for four qualitative metrics: percentage of lung involvement, type of lesion, and two disease distribution scores. We evaluated the agreement between the LungQuant output and the visual assessments through receiver operating characteristics area under the curve (AUC) analysis and by fitting a nonlinear regression model.

RESULTS

Despite the rather large heterogeneity in the qualitative labels assigned by the clinical experts for each metric, we found good agreement on the metrics compared to the LungQuant output. The AUC values obtained for the four qualitative metrics were 0.98, 0.85, 0.90, and 0.81.

CONCLUSIONS

Visual clinical evaluation could be complemented and supported by computer-aided quantification, whose values match the average evaluation of several independent clinical experts.

KEY POINTS

We conducted a multicenter evaluation of the deep learning-based LungQuant automated software. We translated qualitative assessments into quantifiable metrics to characterize coronavirus disease 2019 (COVID-19) pneumonia lesions. Comparing the software output to the clinical evaluations, results were satisfactory despite heterogeneity of the clinical evaluations. An automatic quantification tool may contribute to improve the clinical workflow of COVID-19 pneumonia.

Reproducibility of CT radiomic features in lung neuroendocrine tumours (NETs) patients: analysis in a heterogeneous population

BACKGROUND

The aim is to find a correlation between texture features extracted from neuroendocrine (NET) lung cancer subtypes, both Ki-67 index and the presence of lymph-nodal mediastinal metastases detected while using different computer tomography (CT) scanners.

METHODS

Sixty patients with a confirmed pulmonary NET histological diagnosis, a known Ki-67 status and metastases, were included. After subdivision of primary lesions in baseline acquisition and venous phase, 107 radiomic features of first and higher orders were extracted. Spearman's correlation matrix with Ward's hierarchical clustering was applied to confirm the absence of bias due to the database heterogeneity. Nonparametric tests were conducted to identify statistically significant features in the distinction between patient groups (Ki-67 < 3-Group 1; 3 ≤ Ki-67 ≤ 20-Group 2; and Ki-67 > 20-Group 3, and presence of metastases).

RESULTS

No bias arising from sample heterogeneity was found. Regarding Ki-67 groups statistical tests, seven statistically significant features (p value < 0.05) were found in post-contrast enhanced CT; three in baseline acquisitions. In metastasis classes distinction, three features (first-order class) were statistically significant in post-contrast acquisitions and 15 features (second-order class) in baseline acquisitions, including the three features distinguishing between Ki-67 groups in baseline images (MCC, ClusterProminence and Strength).

CONCLUSIONS

Some radiomic features can be used as a valid and reproducible tool for predicting Ki-67 class and hence the subtype of lung NET in baseline and post-contrast enhanced CT images. In particular, in baseline examination three features can establish both tumour class and aggressiveness.

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.

Technological advances in body CT: a primer for beginners

Many technological advances have entered the clinical routine of Computed Tomography (CT) imaging. The new CT scanners have specific solutions in gantry design to bear the mechanical solicitations. The X-ray tubes have been improved for faster acquisitions at low radiation exposure, while the innovations in CT detectors provide a better image quality. The optimization of image quality and contrast, and the reduction of radiation dose, cannot be achieved without the implementation of adequate reconstruction software, such as Iterative Reconstructions (IR) and Artificial Intelligence (AI). In recent years, dual-energy (DECT) technology has expanded the indications of CT. In this narrative review, a panoramic overview of the technological novelties in CT imaging will be provided for optimal utilization of CT technology.

Diffusion weighted imaging and diffusion kurtosis imaging in abdominal oncological setting: why and when

This article provides an overview of diffusion kurtosis (DKI) imaging in abdominal oncology. DKI allows for more data on tissue structures than the conventional diffusion model (DWI). However, DKI requires high quality images at b-values greater than 1000 s/mm² and high signal-to-noise ratio (SNR) that traditionally MRI systems are not able to acquire and therefore there are generally amplified anatomical distortions on the images due to less homogeneity of the field. Advances in both hardware and software on modern MRI scanners have currently enabled ultra-high b-value imaging and offered the ability to apply DKI to multiple extracranial sites. Previous studies have evaluated the ability of DKI to characterize and discriminate tumor grade compared to conventional DWI. Additionally, in several studies the DKI sequences used were based on planar echo (EPI) acquisition, which is susceptible to motion, metal and air artefacts and prone to low SNRs and distortions, leading to low quality images for some small lesions, which may affect the accuracy of the results. Another problem is the optimal b-value of DKI, which remains to be explored and not yet standardized, as well as the manual selection of the ROI, which could affect the accuracy of some parameters.

Non-traumatic non-cardiovascular thoracic emergencies: role of imaging

Patients presenting to the emergency with thoracic symptoms could have a wide variety of causes, even if the traumatic and vascular causes are excluded. Therefore, the diagnosis is often a challenge for emergency physicians. Anamnesis, physical examination and laboratory testing need to be integrated with imaging to get a rapid diagnosis and to distinguish among the potential causes. This review discusses the role of diagnostic imaging studies in the emergency setting in patients with non-traumatic non-cardiovascular thoracic symptoms. The use of chest x-ray, bedside lung Ultrasound and Computed Tomography in the diagnosis and care of these patients have been reviewed as well as the common findings on imaging.

Dual-Energy CT applications in urinary tract cancers: an update

Urothelial tumours are the fourth most common cancer in the world and account for the majority of tumours involving the bladder. The symptom that often leads to diagnosis is the presence of haematuria. Diagnosis is made by cystoscopy, which is currently the gold standard in bladder cancer. Computed tomography (CT) performed with pre- and post-contrastographic phases is essential in order to assess the loco-regional and distant extension of disease. The diagnosis and staging of upper tract urothelial cancer (UTUC) are best done with computed tomography urography and flexible ureteroscopy (URS). In the acquisition protocol of this type of tumour, a urographic phase is mandatory, which allows for an accurate diagnostic assessment of the renal pelvis, ureter and bladder, especially in papillary forms. The use of multiple acquisition phases, especially in this type of patient who will have to perform follow-up CTs, leads to the problem of overexposure to ionising radiation, as well as the frequent administration of iodinated contrast medium. For this reason, in recent year, the focus has been put on advanced technologies such as dual-energy CT (DECT), that is a method that can offer some advantages for both radiologist and patient, in the diagnosis of cancer and, in particular, urinary tract disease.

Pancreatic neuroendocrine tumours: spectrum of imaging findings

Pancreatic neuroendocrine tumours (pNETs) are rare and heterogeneous group of neoplasms presenting with a wide variety of symptoms and biological behaviour, from indolent to aggressive ones. pNETs are stratified into functional or non-functional, because of their ability to produce metabolically active hormones. pNETs can be an isolate phenomenon or a part of a hereditary syndrome like von Hippel-Lindau syndrome or neurofibromatosis-1. The incidence has increased in the last years, also because of the improvement of cross-sectional imaging. Computed tomography (CT), magnetic resonance imaging (MRI) and functional imaging are the mainstay imaging modalities used for tumour detection and disease extension assessment, due to easy availability and better contrast/spatial resolution. Radiological imaging plays a fundamental role in detection, characterization and surveillance of pNETs and is involved in almost every stage of patients' management. Moreover, with specific indications and techniques, interventional radiology can also play a role in therapeutic management. Surgery is the treatment of choice, consisting of either partial pancreatectomy or enucleation of the primary tumour. This article reviews the radiologic features of different pNETs as well as imaging mimics, in order to help radiologists to avoid potential pitfalls, to reach the correct diagnosis and to support the multidisciplinary team in establishing the right treatment.

SARS-CoV-2 in upper and lower airway samples of a laryngectomized patient: New insights and many lessons

• We report the presence of SARS-CoV-2 in the nasopharyngeal swab of a laryngectomee. • Viral nasal priming might modulate the systemic inflammatory response. • Smoking exposure is a risk factor for SARS-CoV-2 infection and multiple malignancies.