Evaluation of Six Diffusion-weighted MRI Models for Assessing Effects of Neoadjuvant Chemoradiation in Pancreatic Cancer Patients

Quantitative Magnetic Resonance Imaging for the Pancreas: Current Status

ABSTRACT

Magnetic resonance imaging (MRI) is important for evaluating pancreatic disorders, and anatomical landmarks play a major role in the interpretation of results. Quantitative MRI is an effective diagnostic modality for various pathologic conditions, as it allows the investigation of various physical parameters. Recent advancements in quantitative MRI techniques have significantly improved the accuracy of pancreatic MRI. Consequently, this method has become an essential tool for the diagnosis, treatment, and monitoring of pancreatic diseases. This comprehensive review article presents the currently available evidence on the clinical utility of quantitative MRI of the pancreas.

89Zr-Labeled High-Density Lipoprotein Nanoparticle PET Imaging Reveals Tumor Uptake in Patients with Esophageal Cancer

Nanomedicine holds promise for the delivery of therapeutic and imaging agents to improve cancer treatment outcomes. Preclinical studies have demonstrated that high-density lipoprotein (HDL) nanoparticles accumulate in tumor tissue on intravenous administration. Whether this HDL-based nanomedicine concept is feasible in patients is unexplored. Using a multimodal imaging approach, we aimed to assess tumor uptake of exogenously administered HDL nanoparticles in patients with esophageal cancer. Methods: The HDL mimetic CER-001 was radiolabeled using ⁸⁹Zr to allow for PET/CT imaging. Patients with primary esophageal cancer staged T2 and above were recruited for serial ⁸⁹Zr-HDL PET/CT imaging before starting chemoradiation therapy. In addition, patients underwent routine ¹⁸F-FDG PET/CT and 3-T MRI scanning (diffusion-weighted imaging/intravoxel incoherent motion imaging and dynamic contrast-enhanced MRI) to assess tumor glucose metabolism, tumor cellularity and microcirculation perfusion, and tumor vascular permeability. Tumor biopsies were analyzed for the expression of HDL scavenger receptor class B1 and macrophage marker CD68 using immunofluorescence staining. Results: Nine patients with adenocarcinoma or squamous cell carcinoma underwent all study procedures. After injection of ⁸⁹Zr-HDL (39.2 ± 1.2 [mean ± SD] MBq), blood-pool SUV_mean decreased over time (11.0 ± 1.7, 6.5 ± 0.6, and 3.3 ± 0.5 at 1, 24, and 72 h, respectively), whereas liver and spleen SUV_mean remained relatively constant (4.1 ± 0.6, 4.0 ± 0.8, and 4.3 ± 0.8 at 1, 24, and 72 h, respectively, for the liver; 4.1 ± 0.3, 3.4 ± 0.3, and 3.1 ± 0.4 at 1, 24, and 72 h, respectively, for the spleen) and kidney SUV_mean markedly increased over time (4.1 ± 0.9, 9.3 ± 1.4, and 9.6 ± 2.0 at 1, 24, and 72 h, respectively). Tumor uptake (SUV_peak) increased over time (3.5 ± 1.1 and 5.5 ± 2.1 at 1 and 24 h, respectively [P = 0.016]; 5.7 ± 1.4 at 72 h [P = 0.001]). The effective dose of ⁸⁹Zr-HDL was 0.523 ± 0.040 mSv/MBq. No adverse events were observed after the administration of ⁸⁹Zr-HDL. PET/CT and 3-T MRI measures of tumor glucose metabolism, tumor cellularity and microcirculation perfusion, and tumor vascular permeability did not correlate with tumor uptake of ⁸⁹Zr-HDL, suggesting that a specific mechanism mediated the accumulation of ⁸⁹Zr-HDL. Immunofluorescence staining of clinical biopsies demonstrated scavenger receptor class B1 and CD68 positivity in tumor tissue, establishing a potential cellular mechanism of action. Conclusion: To our knowledge, this was the first ⁸⁹Zr-HDL study in human oncology. ⁸⁹Zr-HDL PET/CT imaging demonstrated that intravenously administered HDL nanoparticles accumulated in tumors of patients with esophageal cancer. The administration of ⁸⁹Zr-HDL was safe. These findings may support the development of HDL nanoparticles as a clinical delivery platform for drug agents. ⁸⁹Zr-HDL imaging may guide drug development and serve as a biomarker for individualized therapy.

Added value of 3T MRI and the MRI-halo sign in assessing resectability of locally advanced pancreatic cancer following induction chemotherapy (IMAGE-MRI): prospective pilot study

BACKGROUND

Restaging of locally advanced pancreatic cancer (LAPC) after induction chemotherapy using contrast-enhanced computed tomography (CE-CT) imaging is imprecise in evaluating local tumor response. This study explored the value of 3 Tesla (3 T) contrast-enhanced (CE) and diffusion-weighted (DWI) magnetic resonance imaging (MRI) for local tumor restaging.

METHODS

This is a prospective pilot study including 20 consecutive patients with LAPC with RECIST non-progressive disease on CE-CT after induction chemotherapy. Restaging CE-CT, CE-MRI, and DWI-MRI were retrospectively evaluated by two abdominal radiologists in consensus, scoring tumor size and vascular involvement. A halo sign was defined as replacement of solid perivascular (arterial and venous) tumor tissue by a zone of fatty-like signal intensity.

RESULTS

Adequate MRI was obtained in 19 patients with LAPC after induction chemotherapy. Tumor diameter was non-significantly smaller on CE-MRI compared to CE-CT (26 mm vs. 30 mm; p = 0.073). An MRI-halo sign was seen on CE-MRI in 52.6% (n = 10/19), whereas a CT-halo sign was seen in 10.5% (n = 2/19) of patients (p = 0.016). An MRI-halo sign was not associated with resection rate (60.0% vs. 62.5%; p = 1.000). In the resection cohort, patients with an MRI-halo sign had a non-significant increased R0 resection rate as compared to patients without an MRI-halo sign (66.7% vs. 20.0%; p = 0.242). Positive and negative predictive values of the CE-MRI-halo sign for R0 resection were 66.7% and 66.7%, respectively.

CONCLUSIONS

3 T CE-MRI and the MRI-halo sign might be helpful to assess the effect of induction chemotherapy in patients with LAPC, but its diagnostic accuracy has to be evaluated in larger series.

Evaluation of Monoexponential, Stretched-Exponential and Intravoxel Incoherent Motion MRI Diffusion Models in Early Response Monitoring to Neoadjuvant Chemotherapy in Patients With Breast Cancer-A Preliminary Study

BACKGROUND

There has been a growing interest in exploring the applications of stretched-exponential (SEM) and intravoxel incoherent motion (IVIM) models of diffusion-weighted imaging (DWI) in breast imaging, with the focus on differentiation of breast lesions. However, the use of SEM and IVIM models to predict early response to neoadjuvant chemotherapy (NACT) has received less attention.

PURPOSE

To investigate the value of monoexponential, SEM, and IVIM models to predict early response to NACT in patients with primary breast cancer.

STUDY TYPE

Prospective.

POPULATION

Thirty-seven patients with primary breast cancer (aged 46 ± 11 years) due to undergo NACT.

FIELD STRENGTH/SEQUENCES

A 1.5-T MR scanner, T1 -weighted three-dimensional spoiled gradient-echo, two-dimensional single-shot spin-echo echo-planar imaging sequence (DWI) at six b-values (0-800 s mm-2 ).

ASSESSMENT

Tumor volume, apparent diffusion coefficient, tissue diffusion (Dt ), pseudo-diffusion coefficient (Dp ), perfusion fraction (f), distributed diffusion coefficient, and alpha (α) were extracted, following volumetric sampling of the tumors, at three time-points: pretreatment, post one and three cycles of NACT.

STATISTICAL TESTS

Mann-Whitney test, receiver operating characteristic (ROC) curve. Statistical significance level was P < 0.05.

RESULTS

Following NACT, 17 patients were determined to be pathological responders and 20 nonresponders. Tumor volume was significantly larger in nonresponders at each MRI time-point and demonstrated reasonable performance in predicting response (area under the ROC curve [AUC] = 0.83-0.87). No significant differences between groups were found in the diffusion coefficients at each time-point (P = 0.09-1). The parameters α (SEM), f, and f × Dp (IVIM) were able to differentiate between response groups after one cycle of NACT (AUC = 0.73, 0.72, and 0.74, respectively).

CONCLUSION

Diffusion coefficients derived from the monoexponential, SEM, and IVIM models did not predict pathological response. However, the IVIM-derived parameters f and f × Dp and the SEM-derived parameter α were able to predict response to NACT in breast cancer patients following one cycle of NACT.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.

Application of Magnetic Resonance Imaging in Neoadjuvant Treatment of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignant tumors of the human digestive system. Due to its insidious onset, many patients have already lost the opportunity for radical resection upon tumor diagnosis. In recent years, neoadjuvant treatment for patients with borderline resectable PDAC has been recommended by multiple guidelines to increase the resection rate of radical surgery and improve the postoperative survival. However, further developments are required to accurately assess the tumor response to neoadjuvant therapy and to select the population suitable for such treatment. Reductions in drug toxicity and the number of neoadjuvant cycles are also critical. At present, the clinical evaluation of neoadjuvant treatment is mainly based on several serological and imaging indicators; however, the unique characteristics of PDAC and the insufficient sensitivity and specificity of the markers render this system ineffective. The imaging evaluation system, magnetic resonance imaging (MRI), has its own unique imaging advantages compared with computed tomography (CT) and other imaging examinations. One key advantage is the ability to reflect the changes more rapidly in tumor tissue components, such as the degree of fibrosis, microvessel density, and tissue hypoxia. It can also perform multiparameter quantitative analysis of tumor tissue and changes, attributing to its increasingly important role in imaging evaluation, and potentially the evaluation of neoadjuvant treatment of pancreatic cancer, as several current articles have studied. At the same time, owing to the complexity of MRI and some of its limitations, its wider application is limited. Compared with CT imaging, few relevant studies have been conducted. In this review article, we will investigate and summarize the advantages, limitations, and future development of MRI in the evaluation of neoadjuvant treatment of PDAC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Tumor Microenvironment Modifications Recorded With IVIM Perfusion Analysis and DCE-MRI After Neoadjuvant Radiotherapy: A Preclinical Study

PURPOSE

Neoadjuvant radiotherapy (NeoRT) improves tumor local control and facilitates tumor resection in many cancers. Some clinical studies demonstrated that both timing of surgery and RT schedule influence tumor dissemination, and subsequently patient overall survival. Previously, we developed a pre-clinical model demonstrating the impact of NeoRT schedule and timing of surgery on metastatic spreading. We report on the impact of NeoRT on tumor microenvironment by MRI.

METHODS

According to our NeoRT model, MDA-MB 231 cells were implanted in the flank of SCID mice. Tumors were locally irradiated (PXI X-Rad SmART) with 2x5Gy and then surgically removed at different time points after RT. Diffusion-weighted (DW) and Dynamic contrast enhancement (DCE) MRI images were acquired before RT and every 2 days between RT and surgery. IntraVoxel Incoherent Motion (IVIM) analysis was used to obtain information on intravascular diffusion, related to perfusion (F: perfusion factor) and subsequently tumor vessels perfusion. For DCE-MRI, we performed semi-quantitative analyses.

RESULTS

With this experimental model, a significant and transient increase of the perfusion factor F [50% of the basal value (n=16, p<0.005)] was observed on day 6 after irradiation as well as a significant increase of the WashinSlope with DCE-MRI at day 6 (n=13, p<0.05). Using immunohistochemistry, a significant increase of perfused vessels was highlighted, corresponding to the increase of perfusion in MRI at this same time point. Moreover, Tumor surgical resection during this peak of vascularization results in an increase of metastasis burden (n=10, p<0.05).

CONCLUSION

Significant differences in perfusion-related parameters (F and WashinSlope) were observed on day 6 in a neoadjuvant radiotherapy model using SCID mice. These modifications are correlated with an increase of perfused vessels in histological analysis and also with an increase of metastasis spreading after the surgical procedure. This experimental observation could potentially result in a way to personalize treatment, by modulating the time of surgery guided on MRI functional data, especially tumor perfusion.

Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients

PURPOSE

Earlier work showed that IVIM-NETorig , an unsupervised physics-informed deep neural network, was faster and more accurate than other state-of-the-art intravoxel-incoherent motion (IVIM) fitting approaches to diffusion-weighted imaging (DWI). This study presents a substantially improved version, IVIM-NEToptim , and characterizes its superior performance in pancreatic cancer patients.

METHOD

In simulations (signal-to-noise ratio [SNR] = 20), the accuracy, independence, and consistency of IVIM-NET were evaluated for combinations of hyperparameters (fit S0, constraints, network architecture, number of hidden layers, dropout, batch normalization, learning rate), by calculating the normalized root-mean-square error (NRMSE), Spearman's ρ, and the coefficient of variation (CVNET ), respectively. The best performing network, IVIM-NEToptim was compared to least squares (LS) and a Bayesian approach at different SNRs. IVIM-NEToptim 's performance was evaluated in an independent dataset of 23 patients with pancreatic ductal adenocarcinoma. Fourteen of the patients received no treatment between two repeated scan sessions and nine received chemoradiotherapy between the repeated sessions. Intersession within-subject standard deviations (wSD) and treatment-induced changes were assessed.

RESULTS

In simulations (SNR = 20), IVIM-NEToptim outperformed IVIM-NETorig in accuracy (NRMSE(D) = 0.177 vs 0.196; NMRSE(f) = 0.220 vs 0.267; NMRSE(D*) = 0.386 vs 0.393), independence (ρ(D*, f) = 0.22 vs 0.74), and consistency (CVNET (D) = 0.013 vs 0.104; CVNET (f) = 0.020 vs 0.054; CVNET (D*) = 0.036 vs 0.110). IVIM-NEToptim showed superior performance to the LS and Bayesian approaches at SNRs < 50. In vivo, IVIM-NEToptim showed significantly less noisy parameter maps with lower wSD for D and f than the alternatives. In the treated cohort, IVIM-NEToptim detected the most individual patients with significant parameter changes compared to day-to-day variations.

CONCLUSION

IVIM-NEToptim is recommended for accurate, informative, and consistent IVIM fitting to DWI data.

Phase I/II Study of LDE225 in Combination with Gemcitabine and Nab-Paclitaxel in Patients with Metastatic Pancreatic Cancer

BACKGROUND

Desmoplasia is a central feature of the tumor microenvironment in pancreatic ductal adenocarcinoma (PDAC). LDE225 is a pharmacological Hedgehog signaling pathway inhibitor and is thought to specifically target tumor stroma. We investigated the combined use of LDE225 and chemotherapy to treat PDAC patients.

METHODS

This was a multi-center, phase I/II study for patients with metastatic PDAC establishing the maximum tolerated dose of LDE225 co-administered with gemcitabine and nab-paclitaxel (phase I) and evaluating the efficacy and safety of the treatment combination after prior FOLFIRINOX treatment (phase II). Tumor microenvironment assessment was performed with quantitative MRI using intra-voxel incoherent motion diffusion weighted MRI (IVIM-DWI) and dynamic contrast-enhanced (DCE) MRI.

RESULTS

The MTD of LDE225 was 200 mg once daily co-administered with gemcitabine 1000 mg/m2 and nab-paclitaxel 125 mg/m2. In phase II, six therapy-related grade 4 adverse events (AE) and three grade 5 were observed. In 24 patients, the target lesion response was evaluable. Three patients had partial response (13%), 14 patients showed stable disease (58%), and 7 patients had progressive disease (29%). Median overall survival (OS) was 6 months (IQR 3.9-8.1). Blood plasma fraction (DCE) and diffusion coefficient (IVIM-DWI) significantly increased during treatment. Baseline perfusion fraction could predict OS (>222 days) with 80% sensitivity and 85% specificity.

CONCLUSION

LDE225 in combination with gemcitabine and nab-paclitaxel was well-tolerated in patients with metastatic PDAC and has promising efficacy after prior treatment with FOLFIRINOX. Quantitative MRI suggested that LDE225 causes increased tumor diffusion and works particularly well in patients with poor baseline tumor perfusion.

Application Value of Mathematical Models of Diffusion-Weighted Magnetic Resonance Imaging in Differentiating Breast Cancer Lesions

Objective

To determine the application value of the mono-exponential model, dual-exponential model, and stretched-exponential model of MRI with diffusion-weighted imaging (DWI) in breast cancer (BC) lesions.

Methods

Totally 64 cases with BC admitted to our hospital between June 2019 and October 2020 were enrolled in this study. They had 71 lesions in total, including 40 benign tumor lesions (including 9 breast cyst lesions) and 31 malignant tumor lesions. After DWI examination, with normal glands as control, mono-exponential model (ADC) map, dual-exponential model (Standard-ADC) map, slow apparent diffusion coefficient (Slow-ADC) map, fast-apparent diffusion coefficient (Fast-ADC) map, and stretched-exponential model (DDC) map were processed, and corresponding values were generated. Then, the situation and significance of each parameter in breast cysts, benign breast tumor lesions, and malignant tumor lesions were analyzed.

Results

The values of ADC, Standard-ADC, and DDC of breast cysts were higher than those of normal glands (all P < 0.05), and the values of ADC and DDC of benign breast tumor lesions were lower than those of normal glands (P < 0.05). In addition, malignant breast tumor lesions had lower values of ADC, Standard-ADC, Slow-ADC, and DDC and a higher Fast-ADC value compared to normal glands (all P < 0.05). Compared with benign tumor lesions, malignant tumor lesions had lower values of ADC, Standard-ADC, Slow-ADC, and DDC and a higher value of Fast-ADC (all P < 0.05). Moreover, the receiver operating characteristic (ROC) curve-based analysis revealed that all the above models could be adopted to effectively evaluate the deterioration of benign breast tumor lesions (all P < 0.05), and DDC value had the most significant diagnostic effect on malignant tumor lesions (P < 0.05).

Conclusion

Both dual-exponential model and stretched-exponential model of DWI can help effectively evaluate the progression of benign breast tumors, and the stretched-exponential model is more effective in the diagnosis of malignant breast tumors. These models are of great help to the future clinical diagnosis of BC.

Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.

Evaluating the Histopathology of Pancreatic Ductal Adenocarcinoma by Intravoxel Incoherent Motion-Diffusion Weighted Imaging Comparing With Diffusion-Weighted Imaging

Objectives

To explore the differences between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion-weighted imaging (DWI) in evaluating the histopathological characters of pancreatic ductal adenocarcinoma (PDAC).

Methods

This retrospective study enrolled 50 patients with PDAC confirmed by pathology from December 2018 to May 2020. All patients underwent DWI and IVIM-DWI before surgeries. Patients were classified into low- and high-fibrosis groups. Apparent diffusion coefficient (ADC), diffusion coefficient (D), false diffusion coefficient (D*), and perfusion fraction (f) were measured by two radiologists, respectively in GE AW 4.7 post-processing station, wherein ADC values were derived by mono-exponential fits and f, D, D* values were derived by biexponential fits. The tumor tissue was stained with Sirius red, CD34, and CK19 to evaluate fibrosis, microvascular density (MVD), and tumor cell density. Furthermore, the correlation between ADC, D, D*, and f values and histopathological results was analyzed.

Results

The D values were lower in the high-fibrosis group than in the low-fibrosis group, while the f values were opposite. Further, no statistically significant differences were detected in ADC and D* values between the high- and low-fibrosis groups. The AUC of D and f values had higher evaluation efficacy in the high- and low-fibrosis groups than ADC values. A significant negative correlation was established between D values, and fibrosis and a significant positive correlation were observed between f values and fibrosis. No statistical difference was detected between DWI/IVIM parameters values and MVD or tumor cell density except for the positive correlation between D* values and tumor cell density.

Conclusions

D and f values derived from the IVIM model had higher sensitivity and diagnostic performance for grading fibrosis in PDAC compared to the conventional DWI model. IVIM-DWI may have the potential as an imaging biomarker for predicting the fibrosis grade of PDAC.

Assessment of Imaging Modalities Against Liver Biopsy in Nonalcoholic Fatty Liver Disease: The Amsterdam NAFLD-NASH Cohort

Background

Noninvasive diagnostic methods are urgently required in disease stratification and monitoring in nonalcoholic fatty liver disease (NAFLD). Multiparametric magnetic resonance imaging (MRI) is a promising technique to assess hepatic steatosis, inflammation, and fibrosis, potentially enabling noninvasive identification of individuals with active and advanced stages of NAFLD.

Purpose

To examine the diagnostic performance of multiparametric MRI for the assessment of disease severity along the NAFLD disease spectrum with comparison to histological scores.

Study Type

Prospective, cohort.

Population

Thirty‐seven patients with NAFLD.

Field Strength/Sequence

Multiparametric MRI at 3.0 T consisted of magnetic resonance (MR) spectroscopy (MRS) with multi‐echo stimulated‐echo acquisition mode, magnitude‐based and three‐point Dixon using a two‐dimensional multi‐echo gradient echo, MR elastography (MRE) using a generalized multishot gradient‐recalled echo sequence and intravoxel incoherent motion (IVIM) using a multislice diffusion weighted single‐shot echo‐planar sequence.

Assessment

Histological steatosis grades were compared to proton density fat fraction measured by MRS (PDFF_MRS), magnitude‐based MRI (PDFF_MRI‐M), and three‐point Dixon (PDFF_Dixon), as well as FibroScan® controlled attenuation parameter (CAP). Fibrosis and disease activity were compared to IVIM and MRE. FibroScan® liver stiffness measurements were compared to fibrosis levels. Diagnostic performance of all imaging parameters was determined for distinction between simple steatosis and nonalcoholic steatohepatitis (NASH).

Statistical Tests

Spearman's rank test, Kruskal–Wallis test, Dunn's post‐hoc test with Holm‐Bonferroni P‐value adjustment, receiver operating characteristic curve analysis. A P‐value <0.05 was considered statistically significant.

Results

Histological steatosis grade correlated significantly with PDFF_MRS (r_s = 0.66, P < 0.001), PDFF_MRI‐M (r_s = 0.68, P < 0.001), and PDFF_Dixon (r_s = 0.67, P < 0.001), whereas no correlation was found with CAP. MRE and IVIM diffusion and perfusion significantly correlated with disease activity (r_s = 0.55, P < 0.001, r_s = −0.40, P = 0.016, r_s = −0.37, P = 0.027, respectively) and fibrosis (r_s = 0.55, P < 0.001, r_s = −0.46, P = 0.0051; r_s = −0.53, P < 0.001, respectively). MRE and IVIM diffusion had the highest area‐under‐the‐curve for distinction between simple steatosis and NASH (0.79 and 0.73, respectively).

Data Conclusion

Multiparametric MRI is a promising method for noninvasive, accurate, and sensitive distinction between simple hepatic steatosis and NASH, as well as for the assessment of steatosis and fibrosis severity.

Level of Evidence

2

Technical Efficacy

2

Assessment of tissue perfusion of pancreatic cancer as potential imaging biomarker by means of Intravoxel incoherent motion MRI and CT perfusion: correlation with histological microvessel density as ground truth

Background/objectives

The aim of this study was to compare intravoxel incoherent motion (IVIM) diffusion weighted (DW) MRI and CT perfusion to assess tumor perfusion of pancreatic ductal adenocarcinoma (PDAC).

Methods

In this prospective study, DW-MRI and CT perfusion were conducted in nineteen patients with PDAC on the day before surgery. IVIM analysis of DW-MRI was performed and the parameters perfusion fraction f, pseudodiffusion coefficient D*, and diffusion coefficient D were extracted for tumors, upstream, and downstream parenchyma. With a deconvolution-based analysis, the CT perfusion parameters blood flow (BF) and blood volume (BV) were estimated for tumors, upstream, and downstream parenchyma. In ten patients, intratumoral microvessel density (MVD_tumor) and microvessel area (MVA_tumor) were analyzed microscopically in resection specimens. Correlation coefficients between IVIM parameters, CT perfusion parameters, and histological microvessel parameters in tumors were calculated. Receiver operating characteristic (ROC) analysis was performed for differentiation of tumors and upstream parenchyma.

Results

f_tumor significantly positively correlated with BF_tumor (r = 0.668, p = 0.002) and BV_tumor (r = 0.672, p = 0.002). There were significant positive correlations between f_tumor and MVD_tumor/ MVA_tumor (r ≥ 0.770, p ≤ 0.009) as well as between BF_tumor and MVD_tumor/ MVA_tumor (r ≥ 0.697, p ≤ 0.025). Correlation coefficients between f_tumor and MVD_tumor/ MVA_tumor were not significantly different from correlation coefficients between BF_tumor and MVD_tumor/ MVA_tumor (p ≥ 0.400). Moreover, f, BF, BV, and permeability values (PEM) showed excellent performance in distinguishing tumors from upstream parenchyma (area under the ROC curve ≥0.874).

Conclusions

The study shows that IVIM derived f_tumor and CT perfusion derived BF_tumor similarly reflect vascularity of PDAC and seem to be comparably applicable for the evaluation of tumor perfusion for tumor characterization and as potential quantitative imaging biomarker.

Trial registration

DRKS, DRKS00022227, Registered 26 June 2020, retrospectively registered. https://www.drks.de/drks_web/navigate.do?navigationId=trial. HTML&TRIAL_ID=DRKS00022227.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-021-00382-x.

Pathological validation and prognostic potential of quantitative MRI in the characterization of pancreas cancer: preliminary experience

Patient stratification based on biological variation in pancreatic ductal adenocarcinoma (PDAC) subtypes could help to improve clinical outcome. However, noninvasive assessment of the entire tumor microenvironment remains challenging. In this study, we investigate the biological basis of dynamic contrast-enhanced (DCE), intravoxel incoherent motion (IVIM), and R2*-derived magnetic resonance imaging (MRI) parameters for the noninvasive characterization of the PDAC tumor microenvironment and evaluate their prognostic potential in PDAC patients. Patients diagnosed with treatment-naïve resectable PDAC underwent MRI. After resection, a whole-mount tumor slice was analyzed for collagen fraction, vessel density, and hypoxia and matched to the MRI parameter maps. MRI parameters were correlated to immunohistochemistry-derived tissue characteristics and evaluated for prognostic potential. Thirty patients were included of whom 21 underwent resection with whole-mount histology available in 15 patients. DCE Ktrans and ve , ADC, and IVIM D correlated with collagen fraction. DCE kep and IVIM f correlated with vessel density and R2* with tissue hypoxia. Based on MRI, two main PDAC phenotypes could be distinguished; a stroma-high phenotype demonstrating high vessel density and high collagen fraction and a stroma-low phenotype demonstrating low vessel density and low collagen fraction. Patients with the stroma-high phenotype (high kep and high IVIM D, n = 8) showed longer overall survival (not reached vs. 14 months, P = 0.001, HR = 9.1, P = 0.004) and disease-free survival (not reached vs. 2 months, P < 0.001, HR 9.3, P = 0.003) compared to the other patients (n = 22). Median follow-up was 41 (95% CI: 36-46) months. MRI was able to accurately characterize tumor collagen fraction, vessel density, and hypoxia in PDAC. Based on imaging parameters, a subgroup of patients with significantly better prognosis could be identified. These first results indicate that stratification-based MRI-derived biomarkers could help to tailor treatment and improve clinical outcome and warrant further research.

Novel strategies using modern radiotherapy to improve pancreatic cancer outcomes: toward a new standard?

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive solid tumours with an estimated 5-year overall survival rate of 7% for all stages combined. In this highly resistant disease that is located in the vicinity of many radiosensitive organs, the role of radiotherapy (RT) and indications for its use in this setting have been debated for a long time and are still under investigation. Although a survival benefit has yet to be clearly demonstrated for RT, it is the only technique, other than surgery, that has been demonstrated to lead to local control improvement. The adjuvant approach is now strongly challenged by neoadjuvant treatments that could spare patients with rapidly progressive systemic disease from unnecessary surgery and may increase free margin (R0) resection rates for those eligible for surgery. Recently developed dose-escalated RT treatments, designed either to maintain full-dose chemotherapy or to deliver a high biologically effective dose, particularly to areas of contact between the tumour and blood vessels, such as hypofractionated ablative RT (HFA-RT) or stereotactic body RT (SBRT), are progressively changing the treatment landscape. These modern strategies are currently being tested in prospective clinical trials with encouraging preliminary results, paving the way for more effective treatment combinations using novel targeted therapies. This review summarizes the current literature regarding the use of RT for the treatment of primary PDAC, describes the limitations of conventional RT, and discusses the emerging role of dose-escalated RT and heavy-particle RT.

Differentiation of high-grade from low-grade diffuse gliomas using diffusion-weighted imaging: a comparative study of mono-, bi-, and stretched-exponential diffusion models

Purpose

Diffusion-weighted imaging (DWI) plays an important role in the preoperative assessment of gliomas; however, the diagnostic performance of histogram-derived parameters from mono-, bi-, and stretched-exponential DWI models in the grading of gliomas has not been fully investigated. Therefore, we compared these models’ ability to differentiate between high-grade and low-grade gliomas.

Methods

This retrospective study included 22 patients with diffuse gliomas (age, 23–74 years; 12 males; 11 high-grade and 11 low-grade gliomas) who underwent preoperative 3 T-magnetic resonance imaging from October 2014 to August 2019. The apparent diffusion coefficient was calculated from the mono-exponential model. Using 13 b-values, the true-diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction were obtained from the bi-exponential model, and the distributed-diffusion coefficient and heterogeneity index were obtained from the stretched-exponential model. Region-of-interests were drawn on each imaging parameter map for subsequent histogram analyses.

Results

The skewness of the apparent diffusion, true-diffusion, and distributed-diffusion coefficients was significantly higher in high-grade than in low-grade gliomas (0.67 ± 0.67 vs. − 0.18 ± 0.63, 0.68 ± 0.74 vs. − 0.08 ± 0.66, 0.63 ± 0.72 vs. − 0.15 ± 0.73; P = 0.0066, 0.0192, and 0.0128, respectively). The 10th percentile of the heterogeneity index was significantly lower (0.77 ± 0.08 vs. 0.88 ± 0.04; P = 0.0004), and the 90th percentile of the perfusion fraction was significantly higher (12.64 ± 3.44 vs. 7.14 ± 1.70%: P < 0.0001), in high-grade than in low-grade gliomas. The combination of the 10th percentile of the true-diffusion coefficient and 90th percentile of the perfusion fraction showed the best area under the receiver operating characteristic curve (0.96).

Conclusion

The bi-exponential model exhibited the best diagnostic performance for differentiating high-grade from low-grade gliomas.

Electronic supplementary material

The online version of this article (10.1007/s00234-020-02456-2) contains supplementary material, which is available to authorized users.

Quantitative imaging for radiotherapy purposes

Quantitative imaging biomarkers show great potential for use in radiotherapy. Quantitative images based on microscopic tissue properties and tissue function can be used to improve contouring of the radiotherapy targets. Furthermore, quantitative imaging biomarkers might be used to predict treatment response for several treatment regimens and hence be used as a tool for treatment stratification, either to determine which treatment modality is most promising or to determine patient-specific radiation dose. Finally, patient-specific radiation doses can be further tailored to a tissue/voxel specific radiation dose when quantitative imaging is used for dose painting. In this review, published standards, guidelines and recommendations on quantitative imaging assessment using CT, PET and MRI are discussed. Furthermore, critical issues regarding the use of quantitative imaging for radiation oncology purposes and resultant pending research topics are identified.

Principal component analysis fosr fast and model-free denoising of multi b-value diffusion-weighted MR images

Despite the utility of tumour characterisation using quantitative parameter maps from multi-b-value diffusion-weighted MRI (DWI), clinicians often prefer the use of the image with highest diffusion-weighting (b-value), for instance for defining regions of interest (ROIs). However, these images are typically degraded by noise, as they do not utilize the information from the full acquisition. We present a principal component analysis (PCA) approach for model-free denoising of DWI data. PCA-denoising was compared to synthetic MRI, where a diffusion model is fitted for each voxel and a denoised image at a given b-value is generated from the model fit. A quantitative comparison of systematic and random errors was performed on data simulated using several diffusion models (mono-exponential, bi-exponential, stretched-exponential and kurtosis). A qualitative visual comparison was also performed for in vivo images in six healthy volunteers and three pancreatic cancer patients. In simulations, the reduction in random errors from PCA-denoising was substantial (up to 55%) and similar to synthetic MRI (up to 53%). Model-based synthetic MRI denoising resulted in substantial (up to 29% of signal) systematic errors, whereas PCA-denoising was able to denoise without introducing systematic errors (less than 2%). In vivo, the signal-to-noise ratio (SNR) and sharpness of PCA-denoised images were superior to synthetic MRI, resulting in clearer tumour boundaries. In the presence of motion, PCA-denoising did not cause image blurring, unlike image averaging or synthetic MRI. Multi-b-value MRI can be denoised model-free with our PCA-denoising strategy that reduces noise to a level similar to synthetic MRI, but without introducing systematic errors associated with the synthetic MRI method.