Dynamic contrast-enhanced MRI in oncology: how we do it

Innovative Imaging Techniques for Advancing Cancer Diagnosis and Treatment

Traditional oncology image-analysis, using modalities such as echography, X-ray, CT, and MRI, has historically relied on human-defined features to interpret and assess clinical images [...].

Differentiation between primary central nervous system lymphomas and gliomas according to pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging

Purpose

It is difficult to differentiate between primary central nervous system lymphoma and primary glioblastoma due to their similar MRI findings. This study aimed to assess whether pharmacokinetic parameters derived from dynamic contrast-enhanced MRI could provide valuable insights for differentiation.

Methods

Seventeen cases of primary central nervous system lymphoma and twenty-one cases of glioblastoma as confirmed by pathology, were retrospectively analyzed. Pharmacokinetic parameters, including Ktrans, Kep, Ve, and the initial area under the Gd concentration curve, were measured from the enhancing tumor parenchyma, peritumoral parenchyma, and contralateral normal parenchyma. Statistical comparisons were made using Mann-Whitney U tests for Ve and Matrix Metallopeptidase-2, while independent samples t-tests were used to compare pharmacokinetic parameters in the mentioned regions and pathological indicators of enhancing tumor parenchyma, such as vascular endothelial growth factor and microvessel density. The pharmacokinetic parameters with statistical differences were evaluated using receiver-operating characteristics analysis. Except for the Wilcoxon rank sum test for Ve, the pharmacokinetic parameters were compared within the enhancing tumor parenchyma, peritumoral parenchyma, and contralateral normal parenchyma of the primary central nervous system lymphomas and glioblastomas using variance analysis and the least-significant difference method.

Results

Statistical differences were observed in Ktrans and Kep within the enhancing tumor parenchyma and in Kep within the peritumoral parenchyma between these two tumor types. Differences were also found in Matrix Metallopeptidase-2, vascular endothelial growth factor, and microvessel density within the enhancing tumor parenchyma of these tumors. When compared with the contralateral normal parenchyma, pharmacokinetic parameters within the peritumoral parenchyma and enhancing tumor parenchyma exhibited variations in glioblastoma and primary central nervous system lymphoma, respectively. Moreover, the receiver-operating characteristics analysis showed that the diagnostic efficiency of Kep in the peritumoral parenchyma was notably higher.

Conclusion

Pharmacokinetic parameters derived from dynamic contrast-enhanced MRI can differentiate primary central nervous system lymphoma and glioblastoma, especially Kep in the peritumoral parenchyma.

Bi-regional dynamic contrast-enhanced MRI for prediction of microvascular invasion in solitary BCLC stage A hepatocellular carcinoma

OBJECTIVES

To construct a combined model based on bi-regional quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), as well as clinical-radiological (CR) features for predicting microvascular invasion (MVI) in solitary Barcelona Clinic Liver Cancer (BCLC) stage A hepatocellular carcinoma (HCC), and to assess its ability for stratifying the risk of recurrence after hepatectomy.

METHODS

Patients with solitary BCLC stage A HCC were prospective collected and randomly divided into training and validation sets. DCE perfusion parameters were obtained both in intra-tumoral region (ITR) and peritumoral region (PTR). Combined DCE perfusion parameters (CDCE) were constructed to predict MVI. The combined model incorporating CDCE and CR features was developed and evaluated. Kaplan-Meier method was used to investigate the prognostic significance of the model and the survival benefits of different hepatectomy approaches.

RESULTS

A total of 133 patients were included. Total blood flow in ITR and arterial fraction in PTR exhibited the best predictive performance for MVI with areas under the curve (AUCs) of 0.790 and 0.792, respectively. CDCE achieved AUCs of 0.868 (training set) and 0.857 (validation set). A combined model integrated with the α-fetoprotein, corona enhancement, two-trait predictor of venous invasion, and CDCE could improve the discrimination ability to AUCs of 0.966 (training set) and 0.937 (validation set). The combined model could stratify the prognosis of HCC patients. Anatomical resection was associated with a better prognosis in the high-risk group (p < 0.05).

CONCLUSION

The combined model integrating DCE perfusion parameters and CR features could be used for MVI prediction in HCC patients and assist clinical decision-making.

CRITICAL RELEVANCE STATEMENT

The combined model incorporating bi-regional DCE-MRI perfusion parameters and CR features predicted MVI preoperatively, which could stratify the risk of recurrence and aid in optimizing treatment strategies.

KEY POINTS

Microvascular invasion (MVI) is a significant predictor of prognosis for hepatocellular carcinoma (HCC). Quantitative DCE-MRI could predict MVI in solitary BCLC stage A HCC; the combined model improved performance. The combined model could help stratify the risk of recurrence and aid treatment planning.

Evaluation of orbital lesions with DCE-MRI: a literature review

PURPOSE

To provide a major review on the applications of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in evaluating orbital lesions. This review also outlines selected scenarios where DCE-MRI may be helpful.

METHODS

A comprehensive retrospective literature review of all English language publications on PubMed, EMBASE, and Google Scholar between 1994 and 2022. This literature review examined the specific applications and clinical scenarios surrounding the utility of DCE-MRI in orbital lesions and various findings that have been presented in the current literature.

RESULTS

DCE-MRI provides information on tissue physiology and permeability, beyond the anatomical features displayed on static imaging. Various measured parameters (qualitative, semi-quantitative, and quantitative) obtained by DCE-MRI have been used to differentiate between benign and malignant lesions, specific orbital lymphoproliferative diseases (OLPD), lacrimal gland lesions, and various rare orbital tumours. DCE-MRI has a limited role as an initial diagnostic imaging modality. However, DCE-MRI may prove to have benefit in predicting and monitoring treatment response in orbital lymphoma as a critical imaging study, but literature specific to orbital malignancies remains limited.

CONCLUSION

The value of DCE-MRI may be in situations of diagnostic uncertainty, where it may be an additional imaging aid following conventional imaging techniques. It may also act as a critical imaging modality for monitoring of orbital tumour treatment response, but the literature remains limited. Standardisation of imaging protocol, measured parameters, and statistical analysis remain limitations of this imaging technique.

3D cine-magnetic resonance imaging using spatial and temporal implicit neural representation learning (STINR-MR)

Objective. 3D cine-magnetic resonance imaging (cine-MRI) can capture images of the human body volume with high spatial and temporal resolutions to study anatomical dynamics. However, the reconstruction of 3D cine-MRI is challenged by highly under-sampled k-space data in each dynamic (cine) frame, due to the slow speed of MR signal acquisition. We proposed a machine learning-based framework, spatial and temporal implicit neural representation learning (STINR-MR), for accurate 3D cine-MRI reconstruction from highly under-sampled data.Approach. STINR-MR used a joint reconstruction and deformable registration approach to achieve a high acceleration factor for cine volumetric imaging. It addressed the ill-posed spatiotemporal reconstruction problem by solving a reference-frame 3D MR image and a corresponding motion model that deforms the reference frame to each cine frame. The reference-frame 3D MR image was reconstructed as a spatial implicit neural representation (INR) network, which learns the mapping from input 3D spatial coordinates to corresponding MR values. The dynamic motion model was constructed via a temporal INR, as well as basis deformation vector fields (DVFs) extracted from prior/onboard 4D-MRIs using principal component analysis. The learned temporal INR encodes input time points and outputs corresponding weighting factors to combine the basis DVFs into time-resolved motion fields that represent cine-frame-specific dynamics. STINR-MR was evaluated using MR data simulated from the 4D extended cardiac-torso (XCAT) digital phantom, as well as two MR datasets acquired clinically from human subjects. Its reconstruction accuracy was also compared with that of the model-based non-rigid motion estimation method (MR-MOTUS) and a deep learning-based method (TEMPEST).Main results. STINR-MR can reconstruct 3D cine-MR images with high temporal (<100 ms) and spatial (3 mm) resolutions. Compared with MR-MOTUS and TEMPEST, STINR-MR consistently reconstructed images with better image quality and fewer artifacts and achieved superior tumor localization accuracy via the solved dynamic DVFs. For the XCAT study, STINR reconstructed the tumors to a mean ± SD center-of-mass error of 0.9 ± 0.4 mm, compared to 3.4 ± 1.0 mm of the MR-MOTUS method. The high-frame-rate reconstruction capability of STINR-MR allows different irregular motion patterns to be accurately captured.Significance. STINR-MR provides a lightweight and efficient framework for accurate 3D cine-MRI reconstruction. It is a 'one-shot' method that does not require external data for pre-training, allowing it to avoid generalizability issues typically encountered in deep learning-based methods.

Quantitative and Qualitative Parameters of DCE-MRI Predict CDKN2A/B Homozygous Deletion in Gliomas

RATIONALE AND OBJECTIVES

Homozygous deletion (HD) of CDKN2A/B holds important prognostic value in gliomas. This study aimed to explore the predictive potential of conventional MRI characteristics combined with dynamic contrast-enhanced MRI parameters in predicting CDKN2A/B HD status in gliomas.

MATERIALS AND METHODS

Preoperative MRI data of 105 patients (69 without CDKN2A/B HD, and 36 with CDKN2A/B homozygous deletion) with gliomas were retrospectively collected. Conventional MRI features and dynamic contrast-enhanced-MRI qualitative parameter time-intensity curve type, quantitative parameters Ktrans, Kep, Ve, Vp, and iAUC were obtained. Logistic regression models for prediction of CDKN2A/B HD status were constructed in all types of gliomas and both subtypes of IDH-mutant and IDH-wild gliomas.

RESULTS

Multivariate analysis for all patients demonstrated that age (OR=1.103, p = 0.002) and Ktrans (OR=1.051, p < 0.001) independently predicted CDKN2A/B HD. In IDH-mutant subgroup, multivariate analysis results indicated that Ktrans (OR=1.098, p = 0.031) emerged as autonomous predictors of CDKN2A/B HD. In IDH-wild subgroup, age (OR=1.111, p = 0.002) and Ktrans (OR=1.032, p = 0.001) were independent predictors of CDKN2A/B HD according to the multivariate analysis. The areas under the receiver operating characteristic curve of the corresponding models were 0.90, 0.95 and 0.84, respectively.

CONCLUSION

Ktrans can serve as valuable predictive parameters for identifying CDKN2A/B HD status in all types of gliomas and both subtypes of IDH-mutant and IDH-wild gliomas. These findings provide a foundation for precise preoperative non-invasive diagnosis and personalized treatment approaches for glioma patients.

Diagnostic value of dynamic contrast enhancement combined with conventional MRI in differentiating benign and malignant lacrimal gland epithelial tumours

AIM

To establish the diagnostic value of the quantitative parameters of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) combined with conventional MRI in differentiating of benign and malignant lacrimal gland epithelial tumours.

MATERIALS AND METHODS

A retrospective analysis of primary lacrimal gland epithelial tumours confirmed by histopathology was conducted. Conventional MRI features and DCE-MRI quantitative parameters were collected and subjected to analysis. The diagnostic value was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

A total of 53 patients were enrolled of which 29 had malignant, whereas 24 had benign tumours. Conventional MRI revealed statistically significant differences between benign and malignant tumours regarding maximum tumour diameter, posterior margin characteristic, bone destruction, and erosion. The Ktrans and Kep values obtained by DCE-MRI were higher in malignant than in benign tumours, with a statistically significant (p<0.001 and p=0.022). A type I time-signal intensity (TIC) curve was more frequent in benign tumours, whereas a type II TIC curve was prevalent in malignant tumours (p=0.001). ROC analysis showed that Ktrans had the best diagnostic value of the DCE-MRI parameters (area under the ROC curve [AUC] of 0.822, 75.9% sensitivity, and 83.3% specificity, p<0.001). The combination of conventional MRI and DCE-MRI factors had the best diagnostic value and balanced sensitivity and specificity (AUC of 0.948, 93.1% sensitivity, and 91.7% specificity, p<0.001).

CONCLUSIONS

The present findings indicate that the combination of quantitative parameters of DCE-MRI and image characteristics of conventional MRI have a high diagnostic value for the diagnosis of benign and malignant lacrimal gland epithelial tumours.

Magnetic Resonance Imaging Biomarkers of Bone and Soft Tissue Tumors

Magnetic resonance imaging (MRI) is essential in the management of musculoskeletal (MSK) tumors. This review delves into the diverse MRI modalities, focusing on anatomical, functional, and metabolic sequences that provide essential biomarkers for tumor detection, characterization, disease extent determination, and assessment of treatment response. MRI's multimodal capabilities offer a range of biomarkers that enhance MSK tumor evaluation, aiding in better patient management.

The role of gadolinium-based contrast agents in magnetic resonance imaging structured reporting and data systems (RADS)

Among the 28 reporting and data systems (RADS) available in the literature, we identified 15 RADS that can be used in Magnetic Resonance Imaging (MRI). Performing examinations without using gadolinium-based contrast agents (GBCA) has benefits, but GBCA administration is often required to achieve an early and accurate diagnosis. The aim of the present review is to summarize the current role of GBCA in MRI RADS. This overview suggests that GBCA are today required in most of the current RADS and are expected to be used in most MRIs performed in patients with cancer. Dynamic contrast enhancement is required for correct scores calculation in PI-RADS and VI-RADS, although scientific evidence may lead in the future to avoid the GBCA administration in these two RADS. In Bone-RADS, contrast enhancement can be required to classify an aggressive lesion. In RADS scoring on whole body-MRI datasets (MET-RADS-P, MY-RADS and ONCO-RADS), in NS-RADS and in Node-RADS, GBCA administration is optional thanks to the intrinsic high contrast resolution of MRI. Future studies are needed to evaluate the impact of the high T1 relaxivity GBCA on the assignment of RADS scores.

Performance of node reporting and data system (node-RADS): a preliminary study in cervical cancer

BACKGROUND

Node Reporting and Data System (Node-RADS) was proposed and can be applied to lymph nodes (LNs) across all anatomical sites. This study aimed to investigate the diagnostic performance of Node-RADS in cervical cancer patients.

METHODS

A total of 81 cervical cancer patients treated with radical hysterectomy and LN dissection were retrospectively enrolled. Node-RADS evaluations were performed by two radiologists on preoperative MRI scans for all patients, both at the LN level and patient level. Chi-square and Fisher's exact tests were employed to evaluate the distribution differences in size and configuration between patients with and without LN metastasis (LNM) in various regions. The receiver operating characteristic (ROC) and the area under the curve (AUC) were used to explore the diagnostic performance of the Node-RADS score for LNM.

RESULTS

The rates of LNM in the para-aortic, common iliac, internal iliac, external iliac, and inguinal regions were 7.4%, 9.3%, 19.8%, 21.0%, and 2.5%, respectively. At the patient level, as the NODE-RADS score increased, the rate of LNM also increased, with rates of 26.1%, 29.2%, 42.9%, 80.0%, and 90.9% for Node-RADS scores 1, 2, 3, 4, and 5, respectively. At the patient level, the AUCs for Node-RADS scores > 1, >2, > 3, and > 4 were 0.632, 0.752, 0.763, and 0.726, respectively. Both at the patient level and LN level, a Node-RADS score > 3 could be considered the optimal cut-off value with the best AUC and accuracy.

CONCLUSIONS

Node-RADS is effective in predicting LNM for scores 4 to 5. However, the proportions of LNM were more than 25% at the patient level for scores 1 and 2, which does not align with the expected very low and low probability of LNM for these scores.

Predicting intraoperative hemorrhage during curettage treatment of cesarean scar pregnancy using free-breathing GRASP DCE-MRI

OBJECTIVE

To explore the feasibility of the golden-angle radial sparse parallel (GRASP) dynamic magnetic resonance imaging (MRI) technique in predicting the intraoperative bleeding risk of scar pregnancy.

METHODS

A total of 49 patients with cesarean scar pregnancy (CSP) who underwent curettage and GRASP-MRI imaging were retrospectively selected between January 2021 and July 2022. The pharmacokinetic parameters, including Wash-in, Wash-out, time to peck (TTP), initial area under the curve (iAUC), the transfer rate constant (Ktrans), constant flow rate (Kep), and volume of extracellular space (Ve), were calculated. The amount of intraoperative bleeding was recorded by a gynecologist who performed surgery, after which patients were divided into non-hemorrhage (blood loss ≤ 200 mL) and hemorrhage (blood loss > 200 mL) groups. The measured pharmacokinetic parameters were statistically compared using the t-test or Mann-Whitney U test with a significant level set to be p < 0.05. The receiver operating characteristic (ROC) curve was constructed, and the area under the curve (AUC) was calculated to evaluate each parameter's capability in intraoperative hemorrhage subgroup classification.

RESULTS

Twenty patients had intraoperative hemorrhage (blood loss > 200 mL) during curettage. The hemorrhage group had larger Wash-in, iAUC, Ktrans, Ve, and shorter TTP than the non-hemorrhage group (all P > 0.05). Wash-in had the highest AUC value (0.90), while Ktrans had the lowest value (0.67). Wash-out and Kep were not significantly different between the two groups.

CONCLUSION

GRASP DCE-MRI has the potential to forecast intraoperative hemorrhage during curettage treatment of CSP, with Wash-in exhibiting the highest predictive performance. This data holds promise for advancing personalized treatment. However, further study is required to compare its effectiveness with other risk factors identified through anatomical MRI and ultrasound.

Towards detection of early response in neoadjuvant chemotherapy of breast cancer using Bayesian intravoxel incoherent motion

Introduction

The early identification of good responders to neoadjuvant chemotherapy (NACT) holds a significant potential in the optimal treatment of breast cancer. A recent Bayesian approach has been postulated to improve the accuracy of the intravoxel incoherent motion (IVIM) model for clinical translation. This study examined the prediction and early sensitivity of Bayesian IVIM to NACT response.

Materials and methods

Seventeen female patients with breast cancer were scanned at baseline and 16 patients were scanned after Cycle 1. Tissue diffusion and perfusion from Bayesian IVIM were calculated at baseline with percentage change at Cycle 1 computed with reference to baseline. Cellular proliferative activity marker Ki-67 was obtained semi-quantitatively with percentage change at excision computed with reference to core biopsy.

Results

The perfusion fraction showed a significant difference (p = 0.042) in percentage change between responder groups at Cycle 1, with a decrease in good responders [-7.98% (-19.47-1.73), n = 7] and an increase in poor responders [10.04% (5.09-28.93), n = 9]. There was a significant correlation between percentage change in perfusion fraction and percentage change in Ki-67 (p = 0.042). Tissue diffusion and pseudodiffusion showed no significant difference in percentage change between groups at Cycle 1, nor was there a significant correlation against percentage change in Ki-67. Perfusion fraction, tissue diffusion, and pseudodiffusion showed no significant difference between groups at baseline, nor was there a significant correlation against Ki-67 from core biopsy.

Conclusion

The alteration in tumour perfusion fraction from the Bayesian IVIM model, in association with cellular proliferation, showed early sensitivity to good responders in NACT.

Clinical trial registration

https://clinicaltrials.gov/ct2/show/NCT03501394, identifier NCT03501394.

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.

New Approaches and Recommendations for Risk-Adapted Breast Cancer Screening

Population-based breast cancer screening using mammography as the gold standard imaging modality has been in clinical practice for over 40 years. However, the limitations of mammography in terms of sensitivity and high false-positive rates, particularly in high-risk women, challenge the indiscriminate nature of population-based screening. Additionally, in light of expanding research on new breast cancer risk factors, there is a growing consensus that breast cancer screening should move toward a risk-adapted approach. Recent advancements in breast imaging technology, including contrast material-enhanced mammography (CEM), ultrasound (US) (automated-breast US, Doppler, elastography US), and especially magnetic resonance imaging (MRI) (abbreviated, ultrafast, and contrast-agent free), may provide new opportunities for risk-adapted personalized screening strategies. Moreover, the integration of artificial intelligence and radiomics techniques has the potential to enhance the performance of risk-adapted screening. This review article summarizes the current evidence and challenges in breast cancer screening and highlights potential future perspectives for various imaging techniques in a risk-adapted breast cancer screening approach. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 5.

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.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.

Assessment of Meningeal Lymphatics in the Parasagittal Dural Space: A Prospective Feasibility Study Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging

OBJECTIVE

Meningeal lymphatic vessels are predominantly located in the parasagittal dural space (PSD); these vessels drain interstitial fluids out of the brain and contribute to the glymphatic system. We aimed to investigate the ability of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing the dynamic changes in the meningeal lymphatic vessels in PSD.

MATERIALS AND METHODS

Eighteen participants (26-71 years; male:female, 10:8), without neurological or psychiatric diseases, were prospectively enrolled and underwent DCE-MRI. Three regions of interests (ROIs) were placed on the PSD, superior sagittal sinus (SSS), and cortical vein. Early and delayed enhancement patterns and six kinetic curve-derived parameters were obtained and compared between the three ROIs. Moreover, the participants were grouped into the young (< 65 years; n = 9) or older (≥ 65 years; n = 9) groups. Enhancement patterns and kinetic curve-derived parameters in the PSD were compared between the two groups.

RESULTS

The PSD showed different enhancement patterns than the SSS and cortical veins (P < 0.001 and P < 0.001, respectively) in the early and delayed phases. The PSD showed slow early enhancement and a delayed wash-out pattern. The six kinetic curve-derived parameters of PSD was significantly different than that of the SSS and cortical vein. The PSD wash-out rate of older participants was significantly lower (median, 0.09; interquartile range [IQR], 0.01-0.15) than that of younger participants (median, 0.32; IQR, 0.07-0.45) (P = 0.040).

CONCLUSION

This study shows that the dynamic changes of meningeal lymphatic vessels in PSD can be assessed with DCE-MRI, and the results are different from those of the venous structures. Our finding that delayed wash-out was more pronounced in the PSD of older participants suggests that aging may disturb the meningeal lymphatic drainage.

Impact of DWI and ADC values in Ovarian-Adnexal Reporting and Data System (O-RADS) MRI score

PURPOSE

Introduce DWI and quantitative ADC evaluation in O-RADS MRI system and observe how diagnostic performance changes. Assess its validity and reproducibility between readers with different experience in female pelvic imaging. Finally, evaluate any correlation between ADC value and histotype in malignant lesions.

MATERIALS AND METHODS

In total, 173 patients with 213 indeterminate adnexal masses (AMs) on ultrasound were subjected to MRI examination, from which 140 patients with 172 AMs were included in the final analysis. Standardised MRI sequences were used, including DWI and DCE sequences. Two readers, blinded to histopathological data, retrospectively classified AMs according to the O-RADS MRI scoring system. A quantitative analysis method was applied by placing a ROI on the ADC maps obtained from single-exponential DWI sequences. AMs considered benign (O-RADS MRI score 2) were excluded from the ADC analysis.

RESULTS

Excellent inter-reader agreement was found in the classification of lesions according to the O-RADS MRI score (K = 0.936; 95% CI). Two ROC curves were created to determine the optimal cut-off value for the ADC variable between O-RADS MRI categories 3-4 and 4-5, respectively, 1.411 × 10^-3 mm²/sec and 0.849 × 10^-3 mm²/sec. Based on these ADC values, 3/45 and 22/62 AMs were upgraded, respectively, to score 4 and 5, while 4/62 AMs were downgraded to score 3. ADC values correlated significantly with the ovarian carcinoma histotype (p value < 0.001).

CONCLUSION

Our study demonstrates the prognostic potential of DWI and ADC values in the O-RADS MRI classification for better radiological standardisation and characterisation of AMs.

Multiparametric MRI of Solid Renal Masses: Principles and Applications of Advanced Quantitative and Functional Methods for Tumor Diagnosis and Characterization

Solid renal masses (SRMs) are increasingly detected and encompass both benign and malignant masses, with renal cell carcinoma (RCC) being the most common malignant SRM. Most patients with SRMs will undergo management without a priori pathologic confirmation. There is an unmet need to noninvasively diagnose and characterize RCCs, as significant variability in clinical behavior is observed and a wide range of differing management options exist. Cross-sectional imaging modalities, including magnetic resonance imaging (MRI), are increasingly used for SRM characterization. Multiparametric (mp) MRI techniques can provide insight into tumor biology by probing different physiologic/pathophysiologic processes noninvasively. These include sequences that probe tissue microstructure, including intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and T₁ relaxometry; oxygen metabolism (blood oxygen level dependent [BOLD-MRI]); as well as vascular flow and perfusion (dynamic contrast-enhanced MRI [DCE-MRI] and arterial spin labeling [ASL]). In this review, we will discuss each mpMRI method in terms of its principles, roles, and discuss the results of human studies for SRM assessment. Future validation of these methods may help to enable a personalized management approach for patients with SRM in the emerging era of precision medicine. EVIDENCE LEVEL: 5. TECHNICAL EFFICACY: 2.

Non-invasive imaging in the diagnosis of combined hepatocellular carcinoma and cholangiocarcinoma

Combined hepatocellular-cholangiocarcinoma (cHCC-CC) is a rare type of primary liver cancer. It is a complex "biphenotypic" tumor type consisting of bipotential hepatic progenitor cells that can differentiate into cholangiocytes subtype and hepatocytes subtype. The prognosis of patients with cHCC-CC is quite poor with its specific and more aggressive nature. Furthermore, there are no definite demographic or clinical features of cHCC-CC, thus a clear preoperative identification and accurate non-invasive imaging diagnostic analysis of cHCC-CC are of great value. In this review, we first summarized the epidemiological features, pathological findings, molecular biological information and serological indicators of cHCC-CC disease. Then we reviewed the important applications of non-invasive imaging modalities-particularly ultrasound (US)-in cHCC-CC, covering both diagnostic and prognostic assessment of patients with cHCC-CC. Finally, we presented the shortcomings and potential outlooks for imaging studies in cHCC-CC.

Intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging for neoadjuvant chemotherapy response evaluation in patients with osteosarcoma

OBJECTIVES

This study aims to explore the role of quantitative intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters in characterizing changes in osteosarcoma (OS) patients receiving neoadjuvant chemotherapy (NACT).

MATERIAL AND METHODS

Twenty-seven patients with histologically proven OS were examined prospectively and divided into good-response group (n = 14) and poor-response group (n = 13). IVIM and DCE-MRI sequences were performed at baseline (pre-NACT) and after three cycles of NACT (post-NACT). Apparent diffusion coefficient (ADC) and IVIM bi-exponential model parameters, including diffusion coefficient (D-Bi), perfusion coefficient (D*-Bi), and perfusion fraction (f-Bi), were evaluated. DCE-MRI parameters, including quantitative parameters (volume transfer constant [K^trans], elimination rate constant [Kep], and extravascular extracellular space volume ratio [Ve]) and semi-quantitative parameters (initial area under the gadolinium curve [IAUGC] and contrast enhancement rate [CER]), were also measured.

RESULTS

D-Bi, D*-Bi, and f-Bi post-NACT and ΔD-Bi were statistically different between the good- and poor-response groups (Z₁ =  - 3.348, Z₂ =  - 2.572, Z₃ =  - 2.378, t = 2.235, P < 0.05). ADC, f-Bi, K^trans, IAUGC, Kep, and CER post-NACT were statistically different from those at pre-NACT (P < 0.05). The receiver operating characteristic curve showed that f-Bi post-NACT had the best performance among all parameters, with area under the curve of 0.769, sensitivity of 1, and specificity of 0.538. The correlation analysis showed that the efficacy of NACT was negatively correlated with D-Bi, D*-Bi post-NACT, and ΔD-Bi (r₁ =  - 0.530, r₂ =  - 0.411, r₃ =  - 0.434, P₁ = 0.008, P₂ = 0.046, P₃ = 0.034) and significantly positively correlated with f-Bi post-NACT (r = 0.482, P = 0.017).

CONCLUSIONS

The IVIM quantitative parameters D-Bi, D*-Bi, and f-Bi post-NACT and ΔD-Bi could be used as noninvasive imaging biomarkers for early response assessment of NACT in OS.

Smart Biomimetic Nanozymes for Precise Molecular Imaging: Application and Challenges

New nanotechnologies for imaging molecules are widely being applied to visualize the expression of specific molecules (e.g., ions, biomarkers) for disease diagnosis. Among various nanoplatforms, nanozymes, which exhibit enzyme-like catalytic activities in vivo, have gained tremendously increasing attention in molecular imaging due to their unique properties such as diverse enzyme-mimicking activities, excellent biocompatibility, ease of surface tenability, and low cost. In addition, by integrating different nanoparticles with superparamagnetic, photoacoustic, fluorescence, and photothermal properties, the nanoenzymes are able to increase the imaging sensitivity and accuracy for better understanding the complexity and the biological process of disease. Moreover, these functions encourage the utilization of nanozymes as therapeutic agents to assist in treatment. In this review, we focus on the applications of nanozymes in molecular imaging and discuss the use of peroxidase (POD), oxidase (OXD), catalase (CAT), and superoxide dismutase (SOD) with different imaging modalities. Further, the applications of nanozymes for cancer treatment, bacterial infection, and inflammation image-guided therapy are discussed. Overall, this review aims to provide a complete reference for research in the interdisciplinary fields of nanotechnology and molecular imaging to promote the advancement and clinical translation of novel biomimetic nanozymes.

Preliminary MRI Study of Extracellular Volume Fraction for Identification of Lymphovascular Space Invasion of Cervical Cancer

BACKGROUND

Lymphovascular space invasion (LVSI) is a risk factor for poor prognosis of cervical cancer. Preoperative identification of LVSI is very difficult.

PURPOSE

To evaluate the potential of extracellular volume (ECV) fraction based on T1 mapping in preoperative identification of LVSI in cervical cancer compared with dynamic contrast-enhanced MRI (DCE-MRI).

STUDY TYPE

Retrospective.

SUBJECTS

A total of 79 patients (median age 54 years) with cervical cancer were classified into LVSI group (n = 29) and without LVSI group (n = 50) according to postoperative pathology.

FIELD STRENGTH/SEQUENCE

A 3-T, noncontrast and contrast-enhanced T1 mapping performed with volume interpolated breath hold examination (VIBE) sequence, DCE-MRI applied with 3D T1-weighted VIBE sequence.

ASSESSMENT

Regions of interest along the medial edge of the lesion were drawn on slices depicting the maximum cross-section of the tumor. The noncontrast and contrast-enhanced T1 value of the tumor and arteries in the same slice were measured, and ECV was calculated from T1 values. The parametric maps (K^trans , k_ep , and v_e ) derived from DCE-MRI standard Toft's model were evaluated.

STATISTICAL TESTS

ECV, K^trans , k_ep , and v_e between groups with and without LVSI were compared using Student's t-test. The receiver operating characteristic (ROC) curve and DeLong test were used to evaluate and compare the diagnostic performance of ECV, K^trans , k_ep , and v_e for differentiating LVSI. P < 0.05 was considered statistically significant.

RESULTS

The ECV and K^trans of the LVSI group were significantly higher than that of non-LVSI group (52.86% vs. 36.77%, 0.239 vs. 0.176, respectively), and no significant differences in K_ep or v_e values were observed (P = 0.071 and P = 0.168, respectively). The ECV fraction showed significantly higher area under ROC curve than K^trans for differentiating LVSI (0.874 vs. 0.655, respectively).

DATA CONCLUSION

ECV measurements based on T1 mapping might improve the discrimination between patients with and without LVSI in cervical cancer, showing better performance for this purpose than DCE-MRI.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Structured Reporting in Radiological Settings: Pitfalls and Perspectives

Objective: The aim of this manuscript is to give an overview of structured reporting in radiological settings. Materials and Method: This article is a narrative review on structured reporting in radiological settings. Particularly, limitations and future perspectives are analyzed. RESULTS: The radiological report is a communication tool for the referring physician and the patients. It was conceived as a free text report (FTR) to allow radiologists to have their own individuality in the description of the radiological findings. However, this form could suffer from content, style, and presentation discrepancies, with a probability of transferring incorrect radiological data. Quality, datafication/quantification, and accessibility represent the three main goals in moving from FTRs to structured reports (SRs). In fact, the quality is related to standardization, which aims to improve communication and clarification. Moreover, a “structured” checklist, which allows all the fundamental items for a particular radiological study to be reported and permits the connection of the radiological data with clinical features, allowing a personalized medicine. With regard to accessibility, since radiological reports can be considered a source of research data, SR allows data mining to obtain new biomarkers and to help the development of new application domains, especially in the field of radiomics. Conclusions: Structured reporting could eliminate radiologist individuality, allowing a standardized approach.

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.

Precision Imaging Guidance in the Era of Precision Oncology: An Update of Imaging Tools for Interventional Procedures

Interventional oncology (IO) procedures have become extremely popular in interventional radiology (IR) and play an essential role in the diagnosis, treatment, and supportive care of oncologic patients through new and safe procedures. IR procedures can be divided into two main groups: vascular and non-vascular. Vascular approaches are mainly based on embolization and concomitant injection of chemotherapeutics directly into the tumor-feeding vessels. Percutaneous approaches are a type of non-vascular procedures and include percutaneous image-guided biopsies and different ablation techniques with radiofrequency, microwaves, cryoablation, and focused ultrasound. The use of these techniques requires precise imaging pretreatment planning and guidance that can be provided through different imaging techniques: ultrasound, computed tomography, cone-beam computed tomography, and magnetic resonance. These imaging modalities can be used alone or in combination, thanks to fusion imaging, to further improve the confidence of the operators and the efficacy and safety of the procedures. This article aims is to provide an overview of the available IO procedures based on clinical imaging guidance to develop a targeted and optimal approach to cancer patients.

A Narrative Review on LI-RADS Algorithm in Liver Tumors: Prospects and Pitfalls

Liver cancer is the sixth most detected tumor and the third leading cause of tumor death worldwide. Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with specific risk factors and a targeted population. Imaging plays a major role in the management of HCC from screening to post-therapy follow-up. In order to optimize the diagnostic-therapeutic management and using a universal report, which allows more effective communication among the multidisciplinary team, several classification systems have been proposed over time, and LI-RADS is the most utilized. Currently, LI-RADS comprises four algorithms addressing screening and surveillance, diagnosis on computed tomography (CT)/magnetic resonance imaging (MRI), diagnosis on contrast-enhanced ultrasound (CEUS) and treatment response on CT/MRI. The algorithm allows guiding the radiologist through a stepwise process of assigning a category to a liver observation, recognizing both major and ancillary features. This process allows for characterizing liver lesions and assessing treatment. In this review, we highlighted both major and ancillary features that could define HCC. The distinctive dynamic vascular pattern of arterial hyperenhancement followed by washout in the portal-venous phase is the key hallmark of HCC, with a specificity value close to 100%. However, the sensitivity value of these combined criteria is inadequate. Recent evidence has proven that liver-specific contrast could be an important tool not only in increasing sensitivity but also in diagnosis as a major criterion. Although LI-RADS emerges as an essential instrument to support the management of liver tumors, still many improvements are needed to overcome the current limitations. In particular, features that may clearly distinguish HCC from cholangiocarcinoma (CCA) and combined HCC-CCA lesions and the assessment after locoregional radiation-based therapy are still fields of research.

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.

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.

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

PURPOSE

The purpose of this study is to evaluate the Radiomics and Machine Learning Analysis based on MRI in the assessment of Liver Mucinous Colorectal Metastases.Query METHODS: The cohort of patients included a training set (121 cases) and an external validation set (30 cases) with colorectal liver metastases with pathological proof and MRI study enrolled in this approved study retrospectively. About 851 radiomics features were extracted as median values by means of the PyRadiomics tool on volume on interest segmented manually by two expert radiologists. Univariate analysis, linear regression modelling and pattern recognition methods were used as statistical and classification procedures.

RESULTS

The best results at univariate analysis were reached by the wavelet_LLH_glcm_JointEntropy extracted by T2W SPACE sequence with accuracy of 92%. Linear regression model increased the performance obtained respect to the univariate analysis. The best results were obtained by a linear regression model of 15 significant features extracted by the T2W SPACE sequence with accuracy of 94%, a sensitivity of 92% and a specificity of 95%. The best classifier among the tested pattern recognition approaches was k-nearest neighbours (KNN); however, KNN achieved lower precision than the best linear regression model.

CONCLUSIONS

Radiomics metrics allow the mucinous subtype lesion characterization, in order to obtain a more personalized approach. We demonstrated that the best performance was obtained by T2-W extracted textural metrics.

Diagnosis and differential diagnosis of dermatofibrosarcoma protuberans: Utility of high-resolution dynamic contrast-enhanced (DCE) MRI

BACKGROUND

Dermatofibrosarcoma protuberans (DFSP) is a kind of low-grade malignant spindle cell neoplasm, the diagnosis, and treatment, which have markedly attracted clinicians' attention for its repeated recurrence. High-resolution magnetic resonance imaging (HR-MRI) has shown unique capabilities in diagnosis of various cutaneous tumors.

MATERIALS AND METHODS

Data of 29 patients with clinically suspected DFSPs and undergoing dynamic contrast-enhanced (DCE) HR-MRI preoperatively were prospectively collected. The HR-MRI qualitative features were evaluated and compared. The DCE-associated quantitative parameters and the time-signal intensity curve (TIC) types were provided using DCE sequences.

RESULTS

A total of 7 DFSPs, nine dermatofibromas (DF, including four cases of cellular variant [CDF]), 12 keloids, and one nodular fasciitis were enrolled. DFSP showed the largest major diameter and the deepest depth. Five DFSPs (71.4%) showed ill-defined margins as well as infiltration of peripheral adipose. All DFSPs showed irregular shape. Most DFSPs presented hyperintensity on T₂ WI (71.4%) and iso-intensity on T₁ WI (85.7%). Six cases (85.7%) had significant enhancement, and six cases (85.7%) had homogeneous enhancement. There were significant differences of K^trans , K_ep , V_e and iAUC values among DFSPs, DFs, and keloids, and DFSP had the highest values for these parameters. Six DFSPs (85.7%) and four CDFs (100%) showed type-III TICs, while the other lesions showed type-Ⅰor type-Ⅱ TICs.

CONCLUSIONS

DCE-HR-MRI could show the growth characteristics of DFSPs, which was of great value for the diagnosis and differential diagnosis of DFSPs and was helpful for the determination of treatment options, thereby to improve the prognosis of patients.

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.

Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature

Simple Summary

The incidence of squamous cell carcinomas of the oropharynx has rapidly increased in the last two decades due to human papilloma virus infection (HPV). HPV-positive and HPV-negative squamous cell tumours differ in radiological imaging, treatment, and prognosis; therefore, differential diagnosis is mandatory. Radiomics with texture analysis is an innovative technique that has been used increasingly in recent years to characterise the tissue heterogeneity of certain structures such as neoplasms or organs by measuring the spatial distribution of pixel values on radiological imaging. This review delineates the application of texture analysis in oropharyngeal tumours and explores how radiomics may potentially improve clinical decision-making.

Abstract

Human papilloma virus infection (HPV) is associated with the development of lingual and palatine tonsil carcinomas. Diagnosing, differentiating HPV-positive from HPV-negative cancers, and assessing the presence of lymph node metastases or recurrences by the visual interpretation of images is not easy. Texture analysis can provide structural information not perceptible to human eyes. A systematic literature search was performed on 16 February 2022 for studies with a focus on texture analysis in oropharyngeal cancers. We conducted the research on PubMed, Scopus, and Web of Science platforms. Studies were screened for inclusion according to the preferred reporting items for systematic reviews. Twenty-six studies were included in our review. Nineteen articles related specifically to the oropharynx and seven articles analysed the head and neck area with sections dedicated to the oropharynx. Six, thirteen, and seven articles used MRI, CT, and PET, respectively, as the imaging techniques by which texture analysis was performed. Regarding oropharyngeal tumours, this review delineates the applications of texture analysis in (1) the diagnosis, prognosis, and assessment of disease recurrence or persistence after therapy, (2) early differentiation of HPV-positive versus HPV-negative cancers, (3) the detection of cancers not visualised by imaging alone, and (4) the assessment of lymph node metastases from unknown primary carcinomas.

The Role of Magnetic Resonance Enterography in Crohn’s Disease: A Review of Recent Literature

Inflammatory bowel disease (IBD) is the term used to identify a form of chronic inflammation of the gastrointestinal tract that primarily contemplates two major entities: ulcerative colitis (UC) and Crohn’s disease (CD). The classic signs are abdominal pain and diarrhoea that correlate with the localization of gastro-enteric disease, although in this pathology extraintestinal symptoms may coexist. The diagnosis of CD relies on a synergistic combination of clinical, laboratory (stool and biochemical), cross-sectional imaging evaluation, as well as endoscopic and histologic assessments. The purpose of this paper is to prove the role of imaging in the diagnosis and follow-up of patients with CD with particular focus on recent innovations of magnetic resonance enterography (MRE) as a pivotal diagnostic tool, analysing the MRE study protocol and imaging features during the various phases of disease activity and its complications.

Electrochemotherapy of Primary Colon Rectum Cancer and Local Recurrence: Case Report and Prospective Analysis

Purpose: Surgery, radiotherapy, and oncological treatment (chemotherapy and antineoplastic antibodies) are standard treatments of rectal cancer. ECT has shown its effectiveness and suitability in deep solid tumors conducted in both preclinical and clinical studies. We show here an update and preliminary results with locally advanced rectum cancer (LARC) treated with ECT. Methods: Two patients with major clinical response to restaging after neoadjuvant treatment for LARC were subjected to ECT 12 weeks after completing chemo-radiation therapy. One patient was subjected to ECT on a colorectal local recurrence formed after neoadjuvant treatment for LARC and surgery. Computed Tomography and Magnetic Resonance Imaging were used to assess ECT response. Results: The results showed stable disease in two of the three patients treated, while one patient achieved a complete response. The local control of disease is maintained in the patient follow-up. For each patient, a reduction in pain was observed and for the patient with local recurrence, a reduction in bleeding present before ECT was also achieved. Conclusion: Preliminary results showed that ECT is a safe and effective treatment in patients with a major clinical response or local recurrence after neoadjuvant therapy for LARC and allows a reduction in pain and bleeding with a consequent improvement to quality of life.

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.

Radiomics and Machine Learning Analysis Based on Magnetic Resonance Imaging in the Assessment of Colorectal Liver Metastases Growth Pattern

To assess Radiomics and Machine Learning Analysis in Liver Colon and Rectal Cancer Metastases (CRLM) Growth Pattern, we evaluated, retrospectively, a training set of 51 patients with 121 liver metastases and an external validation set of 30 patients with a single lesion. All patients were subjected to MRI studies in pre-surgical setting. For each segmented volume of interest (VOI), 851 radiomics features were extracted using PyRadiomics package. Nonparametric test, univariate, linear regression analysis and patter recognition approaches were performed. The best results to discriminate expansive versus infiltrative front of tumor growth with the highest accuracy and AUC at univariate analysis were obtained by the wavelet_LHH_glrlm_ShortRunLowGray Level Emphasis from portal phase of contrast study. With regard to linear regression model, this increased the performance obtained respect to the univariate analysis for each sequence except that for EOB-phase sequence. The best results were obtained by a linear regression model of 15 significant features extracted by the T2-W SPACE sequence. Furthermore, using pattern recognition approaches, the diagnostic performance to discriminate the expansive versus infiltrative front of tumor growth increased again and the best classifier was a weighted KNN trained with the 9 significant metrics extracted from the portal phase of contrast study, with an accuracy of 92% on training set and of 91% on validation set. In the present study, we have demonstrated as Radiomics and Machine Learning Analysis, based on EOB-MRI study, allow to identify several biomarkers that permit to recognise the different Growth Patterns in CRLM.

Magnetic Resonance Features of Liver Mucinous Colorectal Metastases: What the Radiologist Should Know

Purpose: The aim of this study is to assess MRI features of mucinous liver metastases compared to non-mucinous metastases and hepatic hemangioma. Methods: A radiological archive was assessed from January 2017 to June 2021 to select patients subjected to liver resection for CRCLM and MRI in the staging phase. We selected 20 patients with hepatic hemangioma (study group B). We evaluated (a) the maximum diameter of the lesions, in millimeters, on T1-W flash 2D in phase and out phase, on axial HASTE T2-W and on portal phase axial VIBE T1 W; and (b) the signal intensity (SI) in T1-W sequences, in T2-W sequences, Diffusion-Weighted Imaging (DWI) sequences and apparent diffusion coefficient (ADC) maps so as to observe (c) the presence and the type of contrast enhancement during the contrast study. The chi-square test was employed to analyze differences in percentage values of the categorical variable, while the non-parametric Kruskal−Wallis test was used to test for statistically significant differences between the median values of the continuous variables. A p-value < 0.05 was considered statistically significant. Results: The final study population included 52 patients (33 men and 19 women) with 63 years of median age (range 37−82 years) and 157 metastases. In 35 patients, we found 118 non-mucinous type metastases (control group), and in 17 patients, we found 39 mucinous type metastases (study group A). During follow-up, recurrence occurred in 12 patients, and three exhibited mucinous types among them. In the study group, all lesions (100%) showed hypointense SI on T1-W, very high SI (similar to hepatic hemangioma) in T2-W with restricted diffusion and iso-hypointense signals in the ADC map. During the contrast study, the main significant feature is the peripheral progressive enhancement.

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.

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.

CT-Based Radiomics Analysis to Predict Histopathological Outcomes Following Liver Resection in Colorectal Liver Metastases

Simple Summary

The objective of the study was to assess the radiomic features obtained by computed tomography (CT) examination as prognostic biomarkers in patients with colorectal liver metastases, in order to predict histopathological outcomes following liver resection. We obtained good performance considering the single significant textural metric in the identification of the front of tumor growth (expansive versus infiltrative) and tumor budding (high grade versus low grade or absent), in the recognition of mucinous type, and in the detection of recurrences.

Abstract

Purpose: We aimed to assess the efficacy of radiomic features extracted by computed tomography (CT) in predicting histopathological outcomes following liver resection in colorectal liver metastases patients, evaluating recurrence, mutational status, histopathological characteristics (mucinous), and surgical resection margin. Methods: This retrospectively approved study included a training set and an external validation set. The internal training set included 49 patients with a median age of 60 years and 119 liver colorectal metastases. The validation cohort consisted of 28 patients with single liver colorectal metastasis and a median age of 61 years. Radiomic features were extracted using PyRadiomics on CT portal phase. Nonparametric Kruskal–Wallis tests, intraclass correlation, receiver operating characteristic (ROC) analyses, linear regression modeling, and pattern recognition methods (support vector machine (SVM), k-nearest neighbors (KNN), artificial neural network (NNET), and decision tree (DT)) were considered. Results: The median value of intraclass correlation coefficients for the features was 0.92 (range 0.87–0.96). The best performance in discriminating expansive versus infiltrative front of tumor growth was wavelet_HHL_glcm_Imc2, with an accuracy of 79%, a sensitivity of 84%, and a specificity of 67%. The best performance in discriminating expansive versus tumor budding was wavelet_LLL_firstorder_Mean, with an accuracy of 86%, a sensitivity of 91%, and a specificity of 65%. The best performance in differentiating the mucinous type of tumor was original_firstorder_RobustMeanAbsoluteDeviation, with an accuracy of 88%, a sensitivity of 42%, and a specificity of 100%. The best performance in identifying tumor recurrence was the wavelet_HLH_glcm_Idmn, with an accuracy of 85%, a sensitivity of 81%, and a specificity of 88%. The best linear regression model was obtained with the identification of recurrence considering the linear combination of the 16 significant textural metrics (accuracy of 97%, sensitivity of 94%, and specificity of 98%). The best performance for each outcome was reached using KNN as a classifier with an accuracy greater than 86% in the training and validation sets for each classification problem; the best results were obtained with the identification of tumor front growth considering the seven significant textural features (accuracy of 97%, sensitivity of 90%, and specificity of 100%). Conclusions: This study confirmed the capacity of radiomics data to identify several prognostic features that may affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach.

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.

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.

EOB-MR Based Radiomics Analysis to Assess Clinical Outcomes following Liver Resection in Colorectal Liver Metastases

Simple Summary

The aim of this study was to assess the efficacy of radiomics features obtained by EOB-MRI phase in order to predict clinical outcomes following liver resection in Colorectal Liver Metastases Patients, and evaluate recurrence, mutational status, pathological characteristic (mucinous) and surgical resection margin. Ours results confirmed the capacity of radiomics to identify, as biomarkers, several prognostic features that could affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach. These results were confirmed by external validation dataset. We obtained a good performance considering the single textural significant metric in the identification of front of tumor growth (expansive versus infiltrative) and tumor budding (high grade versus low grade or absent), in the recognition of mucinous type and in the detection of recurrences.

Abstract

The aim of this study was to assess the efficacy of radiomics features obtained by EOB-MRI phase in order to predict clinical outcomes following liver resection in Colorectal Liver Metastases Patients, and evaluate recurrence, mutational status, pathological characteristic (mucinous) and surgical resection margin. This retrospective analysis was approved by the local Ethical Committee board of National Cancer of Naples, IRCCS “Fondazione Pascale”. Radiological databases were interrogated from January 2018 to May 2021 in order to select patients with liver metastases with pathological proof and EOB-MRI study in pre-surgical setting. The cohort of patients included a training set (51 patients with 61 years of median age and 121 liver metastases) and an external validation set (30 patients with single lesion with 60 years of median age). For each segmented volume of interest by 2 expert radiologists, 851 radiomics features were extracted as median values using PyRadiomics. non-parametric test, intraclass correlation, receiver operating characteristic (ROC) analysis, linear regression modelling and pattern recognition methods (support vector machine (SVM), k-nearest neighbors (KNN), artificial neural network (NNET), and decision tree (DT)) were considered. The best predictor to discriminate expansive versus infiltrative front of tumor growth was HLH_glcm_MaximumProbability extraxted on VIBE_FA30 with an accuracy of 84%, a sensitivity of 83%, and a specificity of 82%. The best predictor to discriminate tumor budding was Inverse Variance obtained by the original GLCM matrix extraxted on VIBE_FA30 with an accuracy of 89%, a sensitivity of 96% and a specificity of 65%. The best predictor to differentiate the mucinous type of tumor was the HHL_glszm_ZoneVariance extraxted on VIBE_FA30 with an accuracy of 85%, a sensitivity of 46% and a specificity of 95%. The best predictor to identify tumor recurrence was the LHL_glcm_Correlation extraxted on VIBE_FA30 with an accuracy of 86%, a sensitivity of 52% and a specificity of 97%. The best linear regression model was obtained in the identification of the tumor growth front considering the height textural significant metrics by VIBE_FA10 (an accuracy of 89%; sensitivity of 93% and a specificity of 82%). Considering significant texture metrics tested with pattern recognition approaches, the best performance for each outcome was reached by a KNN in the identification of recurrence with the 3 textural significant features extracted by VIBE_FA10 (AUC of 91%, an accuracy of 93%; sensitivity of 99% and a specificity of 77%). Ours results confirmed the capacity of radiomics to identify as biomarkers, several prognostic features that could affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach.

Contrast MR-Based Radiomics and Machine Learning Analysis to Assess Clinical Outcomes following Liver Resection in Colorectal Liver Metastases: A Preliminary Study

Simple Summary

The objective of the study was to evaluate the radiomics features obtained by contrast MRI studies as prognostic biomarkers in colorectal liver metastases patients to predict clinical outcomes following liver resection. We demonstrated a good performance considering the single textural significant metric in the identification of front of tumor growth (expansive versus infiltrative) and tumor budding (high grade versus low grade or absent), in the recognition of mucinous type and in the detection of recurrences. Moreover, considering linear regression models or neural network classifiers in a multivariate approach was possible to increase the performance in terms of accuracy, sensitivity, and specificity.

Abstract

Purpose: To assess radiomics features efficacy obtained by arterial and portal MRI phase in the prediction of clinical outcomes in the colorectal liver metastases patients, evaluating recurrence, mutational status, pathological characteristic (mucinous and tumor budding) and surgical resection margin. Methods: This retrospective analysis was approved by the local Ethical Committee board, and radiological databases were used to select patients with colorectal liver metastases with pathological proof and MRI study in a pre-surgical setting after neoadjuvant chemotherapy. The cohort of patients included a training set (51 patients with 61 years of median age and 121 liver metastases) and an external validation set (30 patients with single lesion with 60 years of median age). For each segmented volume of interest on MRI by two expert radiologists, 851 radiomics features were extracted as median values using the PyRadiomics tool. Non-parametric Kruskal-Wallis test, intraclass correlation, receiver operating characteristic (ROC) analysis, linear regression modelling and pattern recognition methods (support vector machine (SVM), k-nearest neighbors (KNN), artificial neural network (NNET), and decision tree (DT)) were considered. Results: The best predictor to discriminate expansive versus infiltrative tumor growth front was wavelet_LHH_glrlm_ShortRunLowGrayLevelEmphasis extracted on portal phase with accuracy of 82%, sensitivity of 84%, and specificity of 77%. The best predictor to discriminate tumor budding was wavelet_LLH_firstorder_10Percentile extracted on portal phase with accuracy of 92%, a sensitivity of 96%, and a specificity of 81%. The best predictor to differentiate the mucinous type of tumor was the wavelet_LLL_glcm_ClusterTendency extracted on portal phase with accuracy of 88%, a sensitivity of 38%, and a specificity of 100%. The best predictor to identify the recurrence was the wavelet_HLH_ngtdm_Complexity extracted on arterial phase with accuracy of 90%, a sensitivity of 71%, and a specificity of 95%. The best linear regression model was obtained in the identification of mucinous type considering the 13 textural significant metrics extracted by arterial phase (accuracy of 94%, sensitivity of 77% and a specificity of 99%). The best results were obtained in the identification of tumor budding with the eleven textural significant features extracted by arterial phase using a KNN (accuracy of 95%, sensitivity of 84%, and a specificity of 99%). Conclusions: Our results confirmed the capacity of radiomics to identify as biomarkers and several prognostic features that could affect the treatment choice in patients with liver metastases in order to obtain a more personalized approach.

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.