Association between Dynamic Contrast-Enhanced MRI Parameters and Prognostic Factors in Patients with Primary Rectal Cancer

BACKGROUND

To evaluate the association between perfusion parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with prognostic factors in primary rectal cancer patients.

METHODS

A sample of 51 patients with pathologically proven rectal adenocarcinoma through surgery were retrospectively enrolled. All the patients underwent preoperative DCE-MRI including 3D-spoiled gradient echo. Two radiologists determined the tumor border after radiologic-pathologic correlation and drew regions of interest. The perfusion parameters, including the volume transfer constant (K^trans), were calculated under the extended Toft model. The prognostic factors included TN stage, circumferential resection margin, extramural venous invasion, Kirsten-ras mutation, tumor size, carcinoembryonic antigen, and tumor differentiation. The association was assessed via correlation or t-test. For significant prognostic factors, receiver operating characteristic (ROC) curve analyses were performed to estimate the diagnostic predictive values.

RESULTS

K^trans only showed a significant difference according to tumor differentiation, between the well-differentiated (n = 6) and moderately differentiated (n = 45) groups (0.127 ± 0.032, 0.084 ± 0.036, p = 0.036). The AUC was 0.838 (95% CI, 0.702-0.929), and the estimated accuracy, sensitivity, and specificity were 87%, 90%, and 60%, respectively.

CONCLUSIONS

K^trans showed a significant difference based on tumor differentiation, which may be conducive to prediction of prognosis in primary rectal cancer.

Multitasking dynamic contrast enhanced magnetic resonance imaging can accurately differentiate chronic pancreatitis from pancreatic ductal adenocarcinoma

Background and aims

Accurate differentiation of chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC) is an area of unmet clinical need. In this study, a novel Multitasking dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) technique was used to quantitatively evaluate the microcirculation properties of pancreas in CP and PDAC and differentiate between them.

Methods

The Multitasking DCE technique was able to acquire one 3D image per second during the passage of MRI contrast agent, allowing the quantitative estimation of microcirculation properties of tissue, including blood flow F_p, plasma volume fraction v_p, transfer constant K^trans, and extravascular extracellular volume fraction v_e. Receiver operating characteristic (ROC) analysis was performed to differentiate the CP pancreas, PDAC pancreas, normal control pancreas, PDAC tumor, PDAC upstream, and PDAC downstream. ROCs from quantitative analysis and conventional analysis were compared.

Results

Fourteen PDAC patients, 8 CP patients and 20 healthy subjects were prospectively recruited. The combination of F_p, v_p, K^trans, and v_e can differentiate CP versus PDAC pancreas with good AUC (AUC [95% CI] = 0.821 [0.654 - 0.988]), CP versus normal pancreas with excellent AUC (1.000 [1.000 - 1.000]), PDAC pancreas versus normal pancreas with excellent AUC (1.000 [1.000 - 1.000]), CP versus PDAC tumor with excellent AUC (1.000 [1.000 - 1.000]), CP versus PDAC downstream with excellent AUC (0.917 [0.795 - 1.000]), and CP versus PDAC upstream with fair AUC (0.722 [0.465 - 0.980]). This quantitative analysis outperformed conventional analysis in differentiation of each pair.

Conclusion

Multitasking DCE MRI is a promising clinical tool that is capable of unbiased quantitative differentiation between CP from PDAC.

Clinical application and progress of quantitative functional magnetic resonance imaging in prostate cancer

Magnetic resonance imaging (MRI) is a very important imaging method for diagnosis and treatment of prostate cancer (PCa) in clinical practice. As functional MRI is growing and maturing, its quantitative parameters are expected to enhance the clinical value of MRI furtherly. Intravoxel incoherent motion diffusion imaging, diffusion tensor imaging, and diffusion kurtosis imaging, which were derived from diffusion weighted imaging, have provided richer and more accurate parameters. The newly-developed magnetic resonance elastography can complement the mechanical characteristics of PCa.

Single-Cell Reconstruction of Human Basal Cell Diversity in Normal and Idiopathic Pulmonary Fibrosis Lungs

Rationale: Declining lung function in patients with interstitial lung disease is accompanied by epithelial remodeling and progressive scarring of the gas-exchange region. There is a need to better understand the contribution of basal cell hyperplasia and associated mucosecretory dysfunction to the development of idiopathic pulmonary fibrosis (IPF).Objectives: We sought to decipher the transcriptome of freshly isolated epithelial cells from normal and IPF lungs to discern disease-dependent changes within basal stem cells.Methods: Single-cell RNA sequencing was used to map epithelial cell types of the normal and IPF human airways. Organoid and air-liquid interface cultures were used to investigate functional properties of basal cell subtypes.Measurements and Main Results: We found that basal cells included multipotent and secretory primed subsets in control adult lung tissue. Secretory primed basal cells include an overlapping molecular signature with basal cells obtained from the distal lung tissue of IPF lungs. We confirmed that NOTCH2 maintains undifferentiated basal cells and restricts basal-to-ciliated differentiation, and we present evidence that NOTCH3 functions to restrain secretory differentiation.Conclusions: Basal cells are dynamically regulated in disease and are specifically biased toward the expansion of the secretory primed basal cell subset in IPF. Modulation of basal cell plasticity may represent a relevant target for therapeutic intervention in IPF.

Motion Artifact Reduction Using a Convolutional Neural Network for Dynamic Contrast Enhanced MR Imaging of the Liver

Purpose:

To improve the quality of images obtained via dynamic contrast enhanced MRI (DCE-MRI), which contain motion artifacts and blurring using a deep learning approach.

Materials and Methods:

A multi-channel convolutional neural network-based method is proposed for reducing the motion artifacts and blurring caused by respiratory motion in images obtained via DCE-MRI of the liver. The training datasets for the neural network included images with and without respiration-induced motion artifacts or blurring, and the distortions were generated by simulating the phase error in k-space. Patient studies were conducted using a multi-phase T₁-weighted spoiled gradient echo sequence for the liver, which contained breath-hold failures occurring during data acquisition. The trained network was applied to the acquired images to analyze the filtering performance, and the intensities and contrast ratios before and after denoising were compared via Bland–Altman plots.

Results:

The proposed network was found to be significantly reducing the magnitude of the artifacts and blurring induced by respiratory motion, and the contrast ratios of the images after processing via the network were consistent with those of the unprocessed images.

Conclusion:

A deep learning-based method for removing motion artifacts in images obtained via DCE-MRI of the liver was demonstrated and validated.

Texture features and pharmacokinetic parameters in differentiating benign and malignant breast lesions by dynamic contrast enhanced magnetic resonance imaging

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has become a powerful tool for the diagnosis of breast cancer in the clinical setting due to its high sensitivity and specificity. Pharmacokinetic parameters, including Ktrans and area under the curve (AUC), and texture features derived from DCE-MRI have been used to specify the characteristics inside tumors. In the present study, 56 patients (average age 45.3±11.1; range 25-69 years) with histopathologically proved breast tumors were analyzed using the pharmacokinetic parameters and texture features. Malignant tumors displayed higher Ktrans and AUC values than the benign, Ktrans exhibited a significantly difference between the malignant and benign tumors (P=0.001) compared with the AUC values (P=0.029); texture features from DCE-MRI images and pharmacokinetic parameter maps also showed a good diagnostic ability. Alongside the routine method, principal components analysis (PCA) and Fisher discriminant analysis (FDA) were employed on these texture features to differentiate the breast lesions automatically. The Factor-1 scores of PCA were used to divide the patients into two groups, and the diagnosing accuracies of the FDA method on the texture features from DCE-MRI images, Ktrans maps, AUC maps were 93, 98 and 98%, with a cross validation accuracies of 82, 77 and 77%, respectively. To conclude, pharmacokinetic parameters, texture features and the combined computer-assisted classification method were discussed. All method involved in this study may be a potential assisted tool for radiological analysis on breast.

Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis

Purpose

This study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis.

Materials and Methods

Approval from the institutional review board and informed consent were acquired for this study. The MR images of 104 patients with pathologically proven breast cancer (104 lesions) were prospectively analyzed. All of included patients were Chinese woman. The DCE-MRI morphologic findings, apparent diffusion coefficient (ADC) values, quantitative DCE-MRI parameters, and pathological biomarkers between the two subtypes of breast cancer were compared. The quantitative DCE-MRI parameters and ADC values were added to the morphologic features in multivariate models to evaluate diagnostic performance in predicting low-risk breast cancer. The values were further subjected to the receiver operating characteristic (ROC) curve analysis.

Results

Low-risk tumors showed significantly lower K^trans and K_epvalues (t = 2.065, P = 0.043 and t = 3.548, P = 0.001, respectively) and higher ADC value (t = 4.713, P = 0.000) than non-low-risk breast cancers. Our results revealed no significant differences in clinic data and conventional imaging findings between the two breast cancer subtypes. Adding the quantitative DCE-MRI parameters and ADC values to conventional MRI improved the diagnostic performance of MRI: The area under the ROC improved from 0.63 to 0.91. Low-risk breast cancers showed significantly lower matrix metalloproteinase (MMP)-2 expression (P = 0.000), lower MMP-9 expression (P = 0.001), and lower microvessel density (MVD) values (P = 0.008) compared with non-low-risk breast cancers. K^trans and K_ep values were positively correlated with pathological biomarkers. The ADC value showed a significant inverse correlation with pathological biomarkers.

Conclusions

The prediction parameter using K^trans, K_ep, and ADC obtained on DCE-MRI and diffusion-weighted imaging could facilitate the identification of low-risk breast cancers. Decreased biological factors, including MVD, vascular endothelial growth factor, MMP-2, and MMP-9, may explain the possible pathological basis.

Visualizing the antivascular effect of bortezomib on the hypoxic tumor microenvironment

Bortezomib, a novel proteasome inhibitor, has been approved for treating multiple myeloma and mantle cell lymphoma and studied pre-clinically and clinically for solid tumors. Preferential cytotoxicity of bortezomib was found toward hypoxic tumor cells and endothelial cells in vitro. The purpose of this study is to investigate the role of a pretreatment hypoxic tumor microenvironment on the effects of bortezomib in vitro and ex vivo, and explore the feasibility of dynamic contrast enhanced magnetic resonance imaging (DCE MRI) to noninvasively evaluate the biological effects of bortezomib. It was shown in vitro by Western blot, flow cytometry, and ELISA that bortezomib accumulated HIF-1α in non-functional forms and blocks its hypoxia response in human colorectal cancer cell lines. Ex vivo experiments were performed with fluorescent immunohistochemical staining techniques using multiple endogenous and exogenous markers to identify hypoxia (pimonidazole, HRE-TKeGFP), blood flow/permeability (Hoechst 33342), micro-vessels (CD31 and SMA), apoptosis (cleaved caspase 3) and hypoxia response (CA9). After bortezomib administration, overall apoptosis index was significantly increased and blood perfusion was dramatically decreased in tumor xenografts. More importantly, apoptosis signals were found preferentially located in moderate and severe pretreatment hypoxic regions in both tumor and endothelial cells. Meanwhile, DCE MRI examinations showed that the tumor blood flow and permeability decreased significantly after bortezomib administration. The present study revealed that bortezomib reduces tumor hypoxia response and blood perfusion, thus, presenting antivascular properties. It will be important to determine the hypoxic/perfusion status pre- and during treatment at further translational studies.

Diagnostic imaging of psoriatic arthritis. Part II: magnetic resonance imaging and ultrasonography

Plain radiography reveals specific, yet late changes of advanced psoriatic arthritis. Early inflammatory changes are seen both on magnetic resonance imaging and ultrasound within peripheral joints (arthritis, synovitis), tendons sheaths (tenosynovitis, tendovaginitis) and entheses (enthesitis, enthesopathy). In addition, magnetic resonance imaging enables the assessment of inflammatory features in the sacroiliac joints (sacroiliitis), and the spine (spondylitis). In this article, we review current opinions on the diagnostics of some selective, and distinctive features of psoriatic arthritis concerning magnetic resonance imaging and ultrasound and present some hypotheses on psoriatic arthritis etiopathogenesis, which have been studied with the use of magnetic resonance imaging. The following elements of the psoriatic arthritis are discussed: enthesitis, extracapsular inflammation, dactylitis, distal interphalangeal joint and nail disease, and the ability of magnetic resonance imaging to differentiate undifferentiated arthritis, the value of whole-body magnetic resonance imaging and dynamic contrast-enhanced magnetic resonance imaging.

Added value of DCE-MRI in the management of cystic-cavitary lung lesions

BACKGROUND AND OBJECTIVE

We evaluated the added value of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) to CT in the evaluation of cystic-cavitary lung lesions. We aimed to compare morphological parameters, including wall thickness and inner wall irregularity, and to determine whether DCE-MRI with morphological and dynamic parameters was useful in indeterminate lesions. We also aimed to investigate the added value of DCE-MRI in terms of whether to biopsy, and if so the site of biopsy.

METHODS

This prospective study included 39 consecutive patients with cystic and/or cavitary lung lesions detected by CT who then underwent additional DCE-MRI. After initial evaluation, the lesions were classified as benign, indeterminate or malignant and the findings of CT and DCE-MRI compared with each other by considering the final diagnosis that was determined by histopathological findings and clinical evaluation and follow up.

RESULTS

The mean values for wall thickness obtained by DCE-MRI were lower and the range of wall thickness for indeterminate lesions was narrower than those obtained by CT (5.50-11.50 mm and 5.75-13.50 mm for DCE-MRI and CT), and inner wall irregularity on DCE-MRI was more sensitive in malignant lesions. Also, DCE-MRI obviated biopsy in three benign patients and changed the biopsy site in two patients.

CONCLUSION

Our study suggests that DCE-MRI is helpful in indeterminate cystic-cavitary lung lesions, with morphological and dynamic features. It narrowed the range of wall thickness used for indeterminate lesions, was more sensitive than CT in determining malignant inner wall irregularity, and was also useful in determining the need for and appropriate site of biopsy. See article, page 576.

Automatic detection of arterial input function in dynamic contrast enhanced MRI based on affinity propagation clustering

PURPOSE

To automatically and robustly detect the arterial input function (AIF) with high detection accuracy and low computational cost in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

MATERIALS AND METHODS

In this study, we developed an automatic AIF detection method using an accelerated version (Fast-AP) of affinity propagation (AP) clustering. The validity of this Fast-AP-based method was proved on two DCE-MRI datasets, i.e., rat kidney and human head and neck. The detailed AIF detection performance of this proposed method was assessed in comparison with other clustering-based methods, namely original AP and K-means, as well as the manual AIF detection method.

RESULTS

Both the automatic AP- and Fast-AP-based methods achieved satisfactory AIF detection accuracy, but the computational cost of Fast-AP could be reduced by 64.37-92.10% on rat dataset and 73.18-90.18% on human dataset compared with the cost of AP. The K-means yielded the lowest computational cost, but resulted in the lowest AIF detection accuracy. The experimental results demonstrated that both the AP- and Fast-AP-based methods were insensitive to the initialization of cluster centers, and had superior robustness compared with K-means method.

CONCLUSION

The Fast-AP-based method enables automatic AIF detection with high accuracy and efficiency.

Tumor characterization in small animals using magnetic resonance-guided dynamic contrast enhanced diffuse optical tomography

We present a magnetic resonance (MR)-guided near-infrared dynamic contrast enhanced diffuse optical tomography (DCE-DOT) system for characterization of tumors using an optical contrast agent (ICG) and a MR contrast agent [Gd-diethylenetriaminepentaacetic acid (DTPA)] in a rat model. Both ICG and Gd-DTPA are injected and monitored simultaneously using a combined MRI-DOT system, resulting in accurate co-registration between two imaging modalities. Fisher rats bearing R3230 breast tumor are imaged using this hybrid system. For the first time, enhancement kinetics of the exogenous contrast ICG is recovered from the DCE-DOT data using MR anatomical a priori information. As tumors grow, they undergo necrosis and the tissue transforms from viable to necrotic. The results show that the physiological changes between viable and necrotic tissue can be differentiated more accurately based on the ICG enhancement kinetics when MR anatomical information is utilized.