scholarly journals Imaging Hallmarks of the Tumor Microenvironment in Glioblastoma Progression

2021 ◽  
Vol 11 ◽  
Author(s):  
John J. Walsh ◽  
Maxime Parent ◽  
Adil Akif ◽  
Lucas C. Adam ◽  
Samuel Maritim ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Tumor Growth ◽  
Aerobic Glycolysis ◽  
Dce Mri ◽  
Cancer Hallmarks ◽  
Longitudinal Measurements ◽  
Tumor Periphery ◽  
Contrast Enhanced ◽  
Apparent Diffusion ◽  
Magnetic Resonance Imaging Mri

Glioblastoma progression involves multifaceted changes in vascularity, cellularity, and metabolism. Capturing such complexities of the tumor niche, from the tumor core to the periphery, by magnetic resonance imaging (MRI) and spectroscopic imaging (MRSI) methods has translational impact. In human-derived glioblastoma models (U87, U251) we made simultaneous and longitudinal measurements of tumor perfusion (Fp), permeability (Ktrans), and volume fractions of extracellular (ve) and blood (vp) spaces from dynamic contrast enhanced (DCE) MRI, cellularity from apparent diffusion coefficient (ADC) MRI, and extracellular pH (pHe) from an MRSI method called Biosensor Imaging of Redundant Deviation in Shifts (BIRDS). Spatiotemporal patterns of these parameters during tumorigenesis were unique for each tumor. While U87 tumors grew faster, Fp, Ktrans, and vp increased with tumor growth in both tumors but these trends were more pronounced for U251 tumors. Perfused regions between tumor periphery and core with U87 tumors exhibited higher Fp, but Ktrans of U251 tumors remained lowest at the tumor margin, suggesting primitive vascularization. Tumor growth was uncorrelated with ve, ADC, and pHe. U87 tumors showed correlated regions of reduced ve and lower ADC (higher cellularity), suggesting ongoing proliferation. U251 tumors revealed that the tumor core had higher ve and elevated ADC (lower cellularity), suggesting necrosis development. The entire tumor was uniformly acidic (pHe 6.1-6.8) early and throughout progression, but U251 tumors were more acidic, suggesting lower aerobic glycolysis in U87 tumors. Characterizing these cancer hallmarks with DCE-MRI, ADC-MRI, and BIRDS-MRSI will be useful for exploring tumorigenesis as well as timely therapies targeted to specific vascular and metabolic aspects of the tumor microenvironment.

scholarly journals The Key Role of the WNT/β-Catenin Pathway in Metabolic Reprogramming in Cancers under Normoxic Conditions

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5557
Author(s):  
Alexandre Vallée ◽  
Yves Lecarpentier ◽  
Jean-Noël Vallée
Keyword(s):  
Tumor Microenvironment ◽  
Tumor Growth ◽  
Warburg Effect ◽  
Target Genes ◽  
Glucose Transporter ◽  
Aerobic Glycolysis ◽  
Lactate Production ◽  
Metabolic Reprogramming ◽  
Pyruvate Dehydrogenase Kinase ◽  
The Warburg Effect

The canonical WNT/β-catenin pathway is upregulated in cancers and plays a major role in proliferation, invasion, apoptosis and angiogenesis. Nuclear β-catenin accumulation is associated with cancer. Hypoxic mechanisms lead to the activation of the hypoxia-inducible factor (HIF)-1α, promoting glycolytic and energetic metabolism and angiogenesis. However, HIF-1α is degraded by the HIF prolyl hydroxylase under normoxia, conditions under which the WNT/β-catenin pathway can activate HIF-1α. This review is therefore focused on the interaction between the upregulated WNT/β-catenin pathway and the metabolic processes underlying cancer mechanisms under normoxic conditions. The WNT pathway stimulates the PI3K/Akt pathway, the STAT3 pathway and the transduction of WNT/β-catenin target genes (such as c-Myc) to activate HIF-1α activity in a hypoxia-independent manner. In cancers, stimulation of the WNT/β-catenin pathway induces many glycolytic enzymes, which in turn induce metabolic reprogramming, known as the Warburg effect or aerobic glycolysis, leading to lactate overproduction. The activation of the Wnt/β-catenin pathway induces gene transactivation via WNT target genes, c-Myc and cyclin D1, or via HIF-1α. This in turn encodes aerobic glycolysis enzymes, including glucose transporter, hexokinase 2, pyruvate kinase M2, pyruvate dehydrogenase kinase 1 and lactate dehydrogenase-A, leading to lactate production. The increase in lactate production is associated with modifications to the tumor microenvironment and tumor growth under normoxic conditions. Moreover, increased lactate production is associated with overexpression of VEGF, a key inducer of angiogenesis. Thus, under normoxic conditions, overstimulation of the WNT/β-catenin pathway leads to modifications of the tumor microenvironment and activation of the Warburg effect, autophagy and glutaminolysis, which in turn participate in tumor growth.

Pharmacokinetic (PK) and pharmacodynamic (PD) study of the effect of imatinib (Ima) on tumor (T) vascularity (V) and on gemcitabine (Ge) uptake (U) using non-invasive dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) and spectroscopy (MRS)—Study BUS228

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 12006-12006
Author(s):  
W. Wolf ◽  
C. A. Presant ◽  
V. Waluch ◽  
E. J. Chen
Keyword(s):  
Accumulation Rate ◽  
Phase 1 ◽  
Fluid Pressure ◽  
Post Contrast ◽  
Dce Mri ◽  
Chemotherapy Drugs ◽  
Non Invasive ◽  
Contrast Enhanced ◽  
Magnetic Resonance Imaging Mri ◽  
Moderate Nausea

12006 Background: Ima has been reported to increase T U of other chemotherapy drugs and to reduce interstitial fluid pressure (IFP) in experimental animals. Poplin et al performed a phase 1 analysis of Ima plus Ge in solid tumors (AACR 95:405, 2004). We tested ImaGe to determine the T PK and PD effects of Ima, Ge, and the ImaGe combination using DCE-MRI and MRS. Methods: Patients (pt) with measurable and MRI-imagible refractory solid T possibly responsive to Ge were randomized to receive either: one course of Ima with PK/PD, followed by one course of Ge with PK/PD, followed by the combination ImaGe; or one course of Ge with PK/PD followed by one course of Ima with PK/PD, followed by ImaGe. Ge was given at 900 mg/m2 IV over 30 min. for PK/PD and at 10 mg/m2/min. for continued therapy. Ima was given at 400 mg daily for 5 d. with Ge given on day 3. Doses were adjusted for toxicity. T V was measured by the use of DCE-MRI, as described previously (AACR 95:490,2004), where the initial contrast accumulation rate (ICAR) was calculated as the slope of the influx curve, and the delayed contrast accumulation rate (DCAR), measured between 2–20 min post contrast administration, as an approximation of IFP. Ge U was measured by serial 19F-MRS for ∼ 1hr post Ge administration. Results: To date 7 pts have been evaluated for the trial. Two pts have entered the trial and completed one cycle of therapy for PK/PD evaluation. Ima produced moderate nausea in both pts. Other toxicity was negligible. In the first pt Ima produced an 18% increase in the ICAR and a 72% increase in the DCAR but there was no significant change observed in the Ge uptake. In the second pt, Ima produced a 60% increase in the ICAR and a 21% increase in the DCAR. Neither of the 2 pts responded to treatment. Further pts are under study and their PK/PD results will be presented. Conclusions: PK and PD can be measured using DCE MRI together with MRS to determine the clinical affects of Ima, Ge, and the Ima-Ge combination. Current results indicate that Ima has a measurable effect on T V, but its relation to drug U and pt response require further pt evaluations to be definitive. [Table: see text]

scholarly journals The Role of Advanced MRI in the Development of Treat-to-Target Therapeutic Strategies, Patient Stratification and Phenotyping in Rheumatoid Arthritis

2019 ◽  
Author(s):  
Ali Mobasheri ◽  
Mark Hinton ◽  
Olga Kubassova
Keyword(s):  
Rheumatoid Arthritis ◽  
Bone Marrow Edema ◽  
Objective Assessment ◽  
Treat To Target ◽  
Resonance Imaging ◽  
Advanced Imaging ◽  
Dce Mri ◽  
Contrast Enhanced ◽  
Magnetic Resonance Imaging Mri

Abstract In this commentary we discuss the potential of advanced imaging, particularly Dynamic Contrast Enhanced (DCE) magnetic resonance imaging (MRI) for the objective assessment of disease progression in rheumatoid arthritis (RA). We emphasise the potential DCE-MRI in advancing the field and exploring new areas of research and development in RA. We believe that different grades of bone marrow edema (BME) and synovitis in RA can be examined and monitored in a more sensitive manner with DCE-MRI. Future treatments for RA will be significantly improved by enhanced imaging of BMEs and synovitis. DCE-MRI will also facilitate enhanced stratification and phenotyping of patients enrolled in clinical trials.

scholarly journals Improving Automatic Renal Segmentation in Clinically Normal and Abnormal Paediatric DCE-MRI via Contrast Maximisation and Convolutional Networks for Computing Markers of Kidney Function

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7942
Author(s):  
Hykoush Asaturyan ◽  
Barbara Villarini ◽  
Karen Sarao ◽  
Jeanne S. Chow ◽  
Onur Afacan ◽  
...  
Keyword(s):  
Kidney Function ◽  
Contextual Information ◽  
Support Vector ◽  
Clinical Markers ◽  
Dce Mri ◽  
Convolutional Networks ◽  
Clinically Normal ◽  
Contrast Enhanced ◽  
Dual Stage ◽  
Magnetic Resonance Imaging Mri

There is a growing demand for fast, accurate computation of clinical markers to improve renal function and anatomy assessment with a single study. However, conventional techniques have limitations leading to overestimations of kidney function or failure to provide sufficient spatial resolution to target the disease location. In contrast, the computer-aided analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) could generate significant markers, including the glomerular filtration rate (GFR) and time–intensity curves of the cortex and medulla for determining obstruction in the urinary tract. This paper presents a dual-stage fully modular framework for automatic renal compartment segmentation in 4D DCE-MRI volumes. (1) Memory-efficient 3D deep learning is integrated to localise each kidney by harnessing residual convolutional neural networks for improved convergence; segmentation is performed by efficiently learning spatial–temporal information coupled with boundary-preserving fully convolutional dense nets. (2) Renal contextual information is enhanced via non-linear transformation to segment the cortex and medulla. The proposed framework is evaluated on a paediatric dataset containing 60 4D DCE-MRI volumes exhibiting varying conditions affecting kidney function. Our technique outperforms a state-of-the-art approach based on a GrabCut and support vector machine classifier in mean dice similarity (DSC) by 3.8% and demonstrates higher statistical stability with lower standard deviation by 12.4% and 15.7% for cortex and medulla segmentation, respectively.

The value of dynamic contrast-enhanced magnetic resonance imaging combined with apparent diffusion coefficient in the differentiation of benign and malignant diseases of the breast

2021 ◽  
pp. 028418512110240
Author(s):  
Feng Ao ◽  
Yi Yan ◽  
Zi-Li Zhang ◽  
Sheng Li ◽  
Wen-Jing Li ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Lesion Group ◽  
Breast Lesions ◽  
Resonance Imaging ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Apparent Diffusion ◽  
Malignant Breast ◽  
Diagnostic Criterion

Background The value of combined dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and apparent diffusion coefficient (ADC) histogram analysis for the diagnosis of breast cancer has not been evaluated in previous studies. Purpose To investigate the diagnostic value of DCE-MRI combined with ADC in benign and malignant breast lesions. Material and Methods The clinicopathological imaging data included 168 patients (177 lesions) with breast lesions who underwent convention breast MRI, DCE-MRI, and diffusion-weighted imaging (DWI); they were divided into the benign lesion group (n = 39) and malignant lesion group (n = 129) based on pathology. Results Using the type III outflow curve as a diagnostic criterion for malignant breast lesions, the diagnostic sensitivity was 76.9%, the specificity was 80%, the correct rate was 72.2%, and its area under the curve (AUC) was 0.823. Using an enhancement ratio > 100% as a diagnostic criterion for malignant breast lesions, the sensitivity was 61.5%, specificity was 80%, and AUC was 0.723. Using > 3 ipsilateral vessels as a diagnostic criterion for malignant lesions in the breast resulted in a diagnostic sensitivity of 81.6%, a specificity of 80.8%, and an AUC of 0.805. Conclusion The type of time intensity curve DCE-MRI, the early enhancement rate in the first phase, the number of ipsilateral vessels, and the ADC full volume histogram of the blood supply score and DWI are valuable in the diagnosis of benign and malignant breast lesions.

scholarly journals Role of DWI in evaluation of HCC after radiofrequency ablation compared to dynamic MRI using MRI (3 T)

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Bahaa Mohamed Elrefaey Hasan ◽  
Hanaa Abd ElKader Abd ElHamid ◽  
Nivan Hany Khater ◽  
Waseem ElGendy ◽  
Ahmed S. Abdelrahman
Keyword(s):  
Radiofrequency Ablation ◽  
Dynamic Mri ◽  
Reliable Technique ◽  
Adc Value ◽  
Cutoff Value ◽  
Dce Mri ◽  
Apparent Diffusion ◽  
Magnetic Resonance Imaging Mri ◽  
Sensitivity Specificity ◽  
A Prospective Study

Abstract Background The purpose of this study was to investigate the diagnostic performance of diffusion weight imaging (DWI), apparent diffusion coefficient (ADC) map, normalized ADC liver, and normalized ADC spleen compared to the dynamic contrast-enhanced MRI (DCE-MRI) in the evaluation of residual hepatocellular carcinoma (HCC) after radiofrequency ablation (RFA) using 3 T (T) magnetic resonance imaging (MRI). Results A prospective study was performed on 40 patients with radiofrequency-ablated HCC, and 15 (37.5%) patients had viable lesion post-RFA, while 25 (62.5%) had non-viable lesions. DCE-MRI had a sensitivity, specificity, and accuracy of 100%, 100%, and 100%, respectively, compared to DWI which had a sensitivity, specificity, and accuracy of 80%, 88%, and 85%, respectively, for identifying post-RFA viable HCC. The sensitivity, specificity, and accuracy of ADC at a cutoff value of 1.01 × 10−3 mm2/s were 80%, 100%, and 97.1%, respectively. The optimal cutoff value of normalized ADC liver was 0.81 with a sensitivity of 73.3%, specificity of 96%, and accuracy of 92.8%. The sensitivity, specificity, and accuracy of normalized ADC spleen at a cutoff value of 1.22 were 80%, 92%, and 91.1%, respectively. Conclusions DWI-MRI is a reliable technique for assessing HCC after radiofrequency ablation. DWI-MRI with ADC may be used as an alternate sequence for assessing radiofrequency-ablated lesions in individuals who have a contraindication to the contrast media, and the normalized ADC value may be of additional benefit.

Role of MRI in osteosarcoma for chemotherapy response evaluation and prediction: Correlation with histological necrosis

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 10540-10540
Author(s):  
J. Bajpai ◽  
S. Gamnagatti ◽  
V. Sreenivas ◽  
R. Phulia ◽  
M. Sharma ◽  
...  
Keyword(s):  
Multivariable Analysis ◽  
Relative Size ◽  
Chemotherapy Response ◽  
Response Evaluation ◽  
Time Intensity Curve ◽  
Dce Mri ◽  
Receiver Operating Characteristic Curves ◽  
Apparent Diffusion ◽  
Treatment Naïve ◽  
Magnetic Resonance Imaging Mri

10540 Background:Histologic necrosis (HN), the current gold standard for response evaluation in osteosarcoma (OS), is accessible only after neoadjuvant chemotherapy (NACT) and may get affected by confounding factors. Thus, it would be useful to have surrogate markers of response evaluation and prognostication using magnetic resonance imaging (MRI) to individualize therapy. Method:Thirty-one treatment naïve OS patients received 3 cycles of NACT followed by surgery during 2006–2008. All patients underwent baseline and post-NACT conventional(C), diffusion-weighted (DW) and dynamic contrast enhanced (DCE) MRI. Taking ‘Huvos grading’ (good response >/= 90% HN) as reference standard, various parameters of MRI were compared with it. Tumor considered as ellipsoidal; volume (V), average tumor plane (ATP) and relative(r)-ATP (ATP/body surface area) were calculated using standard formula for ellipse. Receiver operating characteristic curves were generated to assess the best threshold and predictability. Sensitivity and specificity were calculated along with 95% confidence limits. After deriving thresholds for each parameter in univariable analysis, multivariable analysis was carried out. Results: Both pre-and post NACT, absolute and relative size parameters were well correlated with HN, though post NACT change in parameters did not. Apparent diffusion coefficient (ADC), either pre-and post NACT measurements or change following chemotherapy were not correlating well. However, on adjusting for volume, significant correlation was found. Thus, we could derive a new parameter diffusion per unit volume (DV= ADC /V). Change in shape of time intensity curve did not show significant correlation. Conclusions: In OS, NACT response can be assessed and predicted by conventional and DW- MRI early in the disease course which correlates well with HN. DV seems to be a sensitive substitute for response evaluation. For DCE-MRI, more sophisticated models in future studies might be useful. [Table: see text] No significant financial relationships to disclose.

scholarly journals Evaluation of a multiparametric MRI radiomic-based approach for stratification of equivocal PI-RADS 3 and upgraded PI-RADS 4 prostatic lesions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Valentina Brancato ◽  
Marco Aiello ◽  
Luca Basso ◽  
Serena Monti ◽  
Luigi Palumbo ◽  
...  
Keyword(s):  
Characteristic Curve ◽  
Multiparametric Mri ◽  
Order Model ◽  
Diagnostic Efficacy ◽  
Dce Mri ◽  
Contrast Enhanced ◽  
Before And After ◽  
Apparent Diffusion ◽  
Adc Map

AbstractDespite the key-role of the Prostate Imaging and Reporting and Data System (PI-RADS) in the diagnosis and characterization of prostate cancer (PCa), this system remains to be affected by several limitations, primarily associated with the interpretation of equivocal PI-RADS 3 lesions and with the debated role of Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI), which is only used to upgrade peripheral PI-RADS category 3 lesions to PI-RADS category 4 if enhancement is focal. We aimed at investigating the usefulness of radiomics for detection of PCa lesions (Gleason Score ≥ 6) in PI-RADS 3 lesions and in peripheral PI-RADS 3 upgraded to PI-RADS 4 lesions (upPI-RADS 4). Multiparametric MRI (mpMRI) data of patients who underwent prostatic mpMRI between April 2013 and September 2018 were retrospectively evaluated. Biopsy results were used as gold standard. PI-RADS 3 and PI-RADS 4 lesions were re-scored according to the PI-RADS v2.1 before and after DCE-MRI evaluation. Radiomic features were extracted from T2-weighted MRI (T2), Apparent diffusion Coefficient (ADC) map and DCE-MRI subtracted images using PyRadiomics. Feature selection was performed using Wilcoxon-ranksum test and Minimum Redundancy Maximum Relevance (mRMR). Predictive models were constructed for PCa detection in PI-RADS 3 and upPI-RADS 4 lesions using at each step an imbalance-adjusted bootstrap resampling (IABR) on 1000 samples. 41 PI-RADS 3 and 32 upPI-RADS 4 lesions were analyzed. Among 293 radiomic features, the top selected features derived from T2 and ADC. For PI-RADS 3 stratification, second order model showed higher performances (Area Under the Receiver Operating Characteristic Curve—AUC— = 80%), while for upPI-RADS 4 stratification, first order model showed higher performances respect to superior order models (AUC = 89%). Our results support the significant role of T2 and ADC radiomic features for PCa detection in lesions scored as PI-RADS 3 and upPI-RADS 4. Radiomics models showed high diagnostic efficacy in classify PI-RADS 3 and upPI-RADS 4 lesions, outperforming PI-RADS v2.1 performance.

scholarly journals Advanced Imaging Analysis in Prostate MRI: Building a Radiomic Signature to Predict Tumor Aggressiveness

Diagnostics ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 594
Author(s):  
Anna Damascelli ◽  
Francesca Gallivanone ◽  
Giulia Cristel ◽  
Claudia Cava ◽  
Matteo Interlenghi ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Imaging Biomarkers ◽  
Gleason Grade ◽  
Imaging Features ◽  
Resonance Imaging ◽  
Grade Group ◽  
Contrast Enhanced ◽  
Apparent Diffusion ◽  
Magnetic Resonance Imaging Mri

Radiomics allows the extraction quantitative features from imaging, as imaging biomarkers of disease. The objective of this exploratory study is to implement a reproducible radiomic-pipeline for the extraction of a magnetic resonance imaging (MRI) signature for prostate cancer (PCa) aggressiveness. One hundred and two consecutive patients performing preoperative prostate multiparametric magnetic resonance imaging (mpMRI) and radical prostatectomy were enrolled. Multiparametric images, including T2-weighted (T2w), diffusion-weighted and dynamic contrast-enhanced images, were acquired at 1.5 T. Ninety-three imaging features (Ifs) were extracted from segmentation of index lesion. Ifs were ranked based on a stability rank and redundant Ifs were excluded. Using unsupervised hierarchical clustering, patients were grouped on the basis of similar radiomic patterns, whose association with Gleason Grade Group (GGG), extracapsular extension (ECE), and nodal involvement (pN) was tested. Signatures composed by IFs from T2w-images and Apparent Diffusion Coefficient (ADC) maps were tested for the prediction of GGG, ECE, and pN. T2w radiomic pattern was associated with pN, ECE, and GGG (p = 0.027, 0.05, 0.03) and ADC radiomic pattern was associated with GGG (p = 0.004). The best performance was reached by the signature combing IFs from multiparametric images (0.88, 0.89, and 0.84 accuracy for GGG, pN, and ECE). A reliable multiparametric MRI radiomic signature was extracted, potentially able to predict PCa aggressiveness, to be further validated on an independent sample.

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