Perfusion Coefficient Research Articles

Reproducibility of spatial penalty-based methodologies for intravoxel incoherent motion analysis with diffusion MRI

Objective was to assess the precision and reproducibility of spatial penalty-based intravoxel incoherent motion (IVIM) methods in comparison to the conventional bi-exponential (BE) model-based IVIM methods. IVIM-MRI (11 b-values; 0–800 s/mm2) of forty patients (N = 40; Age = 17.7 ± 5.9 years; Male:Female = 30:10) with biopsy-proven osteosarcoma were acquired on a 1.5 Tesla scanner at 3 time-points: (i) baseline, (ii) after 1-cycle and (iii) after 3-cycles of neoadjuvant chemotherapy. Diffusion coefficient (D), Perfusion coefficient (D*) and Perfusion fraction (f) were estimated at three time-points in whole tumor and healthy muscle tissue using five methodologies (1) BE with three-parameter-fitting (BE), (2) Segmented-BE with two-parameter-fitting (BESeg-2), (3) Segmented-BE with one-parameter-fitting (BESeg-1), (4) BE with adaptive Total-Variation-penalty (BE + TV) and (5) BE with adaptive Huber-penalty (BE + HPF). Within-subject coefficient-of-variation (wCV) and between-subject coefficient-of-variation (bCV) of IVIM parameters were measured in healthy and tumor tissue. For precision and reproducibility, intra-scan comparison of wCV and bCV among five IVIM methods were performed using Friedman test followed by Wilcoxon-signed-ranks (WSR) post-hoc test. Experimental results demonstrated that BE + TV and BE + HPF showed significantly (p < 10–3) lower wCV and bCV for D (wCV: 24–32%; bCV: 22–31%) than BE method (wCV: 38–49%; bCV: 36–46%) across three time-points in healthy muscle and tumor. BE + TV and BE + HPF also demonstrated significantly (p < 10–3) lower wCV and bCV for estimating D* (wCV: 89–108%; bCV: 83–102%) and f (wCV: 55–60%; bCV: 56–60%) than BE, BESeg-2 and BESeg-1 methods (D*-wCV: 102–122%; D*-bCV: 98–114% and f-wCV: 96–130%; f-bCV: 94–125%) in both tumor and healthy tissue across three time-points. Spatial penalty based IVIM analysis methods BE + TV and BE + HPF demonstrated lower variability and improved precision and reproducibility in the current clinical settings.

Clinical and perfusion imaging characteristics of acute large vessel occlusion in intracranial atherosclerosis

ObjectivesThis study aimed to compare clinical and perfusion imaging profiles in acute ischemic stroke with large vessel occlusion (AIS-LVO) between patients with intracranial atherosclerotic disease (ICAD) and non-ICAD who underwent endovascular treatment (EVT). MethodsData from AIS-LVO patients over the anterior circulation undergoing EVT across two stroke centers were retrospectively analyzed. Clinical profiles and perfusion parameters from automated processing of perfusion imaging were compared between ICAD and non-ICAD groups. Ischemic core was defined as relative cerebral blood flow < 30 % on CT perfusion or apparent diffusion coefficient ≤ 620 × 10−6 mm2/s on MR diffusion weighted imaging. ResultsA total of 111 patients were included (46 ICAD, 65 non-ICAD). The ICAD group exhibited a higher male proportion (60.9 % vs. 35.4 %), more M1 segment occlusions (78.3 % vs. 56.9 %), lower atrial fibrillation rates (17.4 % vs. 63.1 %), and lower baseline NIH Stroke Scale (NIHSS) scores (median [IQR]: 13 [8.75-18] vs. 15 [10-21]) at presentation compared to non-ICAD (all p < 0.05). However, there was no difference in NIHSS scores at discharge or in good functional outcomes (modified Rankin Scale 0-2) at 3 months between the two groups. ICAD patients also had smaller median ischemic core volumes (0 [IQR 0-9.7] vs. 4.4 [0-21.6] ml, p = 0.038), smaller median Tmax >6s tissue volulmes (89.3 [IQR 51.1-147.1] vs. 124.4 [80.5-178.6] ml, p = 0.017) and lower median HIR (hypoperfusion intensity ratio defined as Tmax >10s divided by Tmax >6s; 0.28 [IQR 0.09-0.42] vs. 0.44 [0.24-0.60], p = 0.003). Higher baseline NIHSS scores correlated with larger Tmax >6s lesion volumes as well as higher HIR value in non-ICAD patients, but not in ICAD patients. ConclusionsIn anterior circulation of AIS-LVO, ICAD patients exhibited distinct clinical presentations and perfusion imaging characteristics when compared to non-ICAD patients. Perfusion imaging profiles may serve as indicators for identifying ICAD patients before EVT.

Retrieving the time-dependent blood perfusion coefficient in the thermal-wave model of bio-heat transfer

PurposeIn order to include the non-negligible lag relaxation time feature that is characteristic of heat transfer in biological bodies, the classical Fourier's law of heat conduction has to be generalized as the Maxwell–Cattaneo law resulting in the thermal-wave model of bio-heat transfer. The purpose of the paper is to retrieve the unknown time-dependent blood perfusion coefficient in such a thermal-wave model of bio-heat transfer from (non-intrusive) measurements of the temperature on an accessible sub-portion of the boundary that may be taken with an infrared scanner.Design/methodology/approachThe nonlinear and ill-posed problem is reformulated as a nonlinear minimization problem of a Tikhonov regularization functional subject to lower and upper simple bounds on the unknown coefficient. For the numerical discretization, an unconditionally stable direct solver based on the Crank–Nicolson finite-difference scheme is developed. The Tikhonov regularization functional is minimized iteratively by the built-in routine lsqnonlin from the MATLAB optimization toolbox. Numerical results for a benchmark test example are presented and thoroughly discussed, shedding light on the performance and effectiveness of the proposed methodology.FindingsThe inverse problem of obtaining the time-dependent blood perfusion coefficient and the temperature in the thermal-wave model of bio-heat transfer from extra boundary temperature measurement has been solved. In particular, the uniqueness of the solution to this inverse problem has been established. Furthermore, our proposed computational method demonstrated successful attainment of the perfusion coefficient and temperature, even when dealing with noisy data.Originality/valueThe originalities of the present paper are to account for such a more representative thermal-wave model of heat transfer in biological bodies and to investigate the possibility of determining its time-dependent blood perfusion coefficient from non-intrusive boundary temperature measurements.

Intravoxel incoherent motion (IVIM) detects femoral head ischemia in a piglet model of Legg-Calvé-Perthes disease.

There is a clinical need for alternatives to gadolinium contrast-enhanced magnetic resonance imaging (MRI) to facilitate early detection and assessment of femoral head ischemia in pediatric patients with Legg-Calvé-Perthes disease (LCPD), a juvenile form of idiopathic osteonecrosis of the femoral head. The purpose of this study was to determine if intravoxel incoherent motion (IVIM), a noncontrast-enhanced MRI method to simultaneously measure tissue perfusion and diffusion, can detect femoral head ischemia using a piglet model of LCPD. Twelve 6-week-old piglets underwent unilateral hip surgery to induce complete femoral head ischemia. The unoperated, contralateral femoral head served as a perfused control. The bilateral hips of the piglets were imaged in vivo at 3T MRI using IVIM and contrast-enhanced MRI 1 week after surgery. Median apparent diffusion coefficient (ADC) and IVIM parameters (diffusion coefficient: Ds; perfusion coefficient: Df; perfusion fraction: f; and perfusion flux: f*Df) were compared between regions of interest comprising the epiphyseal bone marrow of the ischemic and control femoral heads. Contrast-enhanced MRI confirmed complete femoral head ischemia in 11/12 piglets. IVIM perfusion fraction (f) and flux (f*Df) were significantly decreased in the ischemic versus control femoral heads: on average, f decreased 47 ± 27% (Δf = -0.055 ± 0.034; p = 0.0003) and f*Df decreased 50 ± 27% (Δf*Df = -0.59 ± 0.49 × 10-3 mm2/s; p = 0.0026). In contrast, IVIM diffusion coefficient (Ds) and ADC were significantly increased in the ischemic versus control femoral heads: on average, Ds increased 78 ± 21% (ΔDs = 0.60 ± 0.14 × 10-3 mm2/s; p < 0.0001) and ADC increased 60 ± 36% (ΔADC = 0.50 ± 0.23 × 10-3 mm2/s; p < 0.0001). In conclusion, IVIM is sensitive in detecting bone marrow ischemia in a piglet model of LCPD.

Radiologists' Rating for Comparative Qualitative Assessment of Intravoxel Incoherent Motion Using Novel Analysis Methods.

The objective was to assess qualitative interpretability and quantitative precision and reproducibility of intravoxel incoherent motion ( IVIM) parametric images evaluated using novel IVIM analysis methods for diagnostic accuracy. Intravoxel incoherent motion datasets of 55 patients (male/female = 41:14; age = 17.8 ± 5.5 years) with histopathology-proven osteosarcoma were analyzed. Intravoxel incoherent motion parameters-diffusion coefficient ( D ), perfusion fraction ( f ), and perfusion coefficient ( D* )-were estimated using 5 IVIM analysis methods-(i) biexponential (BE) model, (ii) BE-segmented fitting 2-parameter (BESeg-2), (iii) BE-segmented fitting 1-parameter (BESeg-1), (iv) BE model with total variation penalty function (BE + TV), and (v) BE model with Huber penalty function (BE + HPF). Qualitative scoring in a 5-point Likert scale (uninterpretable: 1; poor: 2; fair: 3; good: 4; excellent: 5) was performed by 2 radiologists for 4 criteria: (a) tumor shape and margin, (b) morphologic correlation, (c) noise suppression, and (d) overall interpretability. Interobserver agreement was evaluated using Spearman rank-order correlation ( rs ). Precision and reproducibility were evaluated using within-subject coefficient of variation (wCV) and between-subject coefficient of variation (bCV). BE + TV and BE + HPF produced significantly ( P < 10 -3 ) higher qualitative scores for D (fair-good [3.3-3.8]) than BE (poor [2.3]) and for D* (poor-fair [2.2-2.7]) and f (fair-good [3.2-3.8]) than BE, BESeg-2, and BESeg-1 ( D* : uninterpretable-poor [1.3-1.9] and f : poor-fair [1.5-3]). Interobserver agreement for qualitative scoring was rs = 0.48-0.59, P < 0.009. BE + TV and BE + HPF showed significantly ( P < 0.05) improved reproducibility in estimating D (wCV: 24%-31%, bCV: 21%-31% improvement) than the BE method and D* (wCV: 4%-19%, bCV: 5%-19% improvement) and f (wCV: 25%-49%, bCV: 25%-47% improvement) than BE, BESeg-2, and BESeg-1 methods. BE + TV and BE + HPF demonstrated qualitatively and quantitatively improved IVIM parameter estimation and may be considered for clinical use further.

Modified Pennes bioheat equation with heterogeneous blood perfusion: A newer perspective

The Pennes bioheat equation is a widely used mathematical model for predicting temperature distribution in biological tissues. However, it assumes homogeneous blood perfusion throughout the tissue, which may not accurately represent the complex perfusion patterns observed in tumors. In this study, we propose modification to traditional Pennes bioheat equation that incorporates the effects of perfusion heterogeneity by introducing a spatially varying perfusion term, represented by a perfusion coefficient, ωb(x,y,z) to account for local variations in blood flow at each spatial location within the biological tissue. Therefore, heterogeneous blood perfusion at each tumor tissue voxel location relax the uniform blood perfusion assumption. By incorporating these modifications, the model allows for a more realistic representation of the heat exchange between the biological tissue and blood flow, by predicting the non-uniform temperature distribution particularly in tumors with irregular blood vessel growth and organization, thereby facilitating treatment planning and optimization of thermal therapies, and leading to more effective therapeutic outcomes. The spatially varying perfusion coefficient can be obtained through advanced imaging techniques such as dynamic contrast-enhanced MRI or Doppler ultrasound enabling the assessment of perfusion heterogeneity in biological tissues. In conclusion, the modified Pennes bioheat equation offers a valuable tool for understanding the intricate relationship between with heterogeneous blood perfusion and temperature distribution in biological tissues, providing important insights to the thermal response of tumors and guiding the development of improved therapeutic strategies in optimizing cancer treatments.

Improved reliability of perfusion estimation in dynamic susceptibility contrast MRI by using the arterial input function from dynamic contrast enhanced MRI.

The arterial input function (AIF) plays a crucial role in estimating quantitative perfusion properties from dynamic susceptibility contrast (DSC) MRI. An important issue, however, is that measuring the AIF in absolute contrast-agent concentrations is challenging, due to uncertainty in relation to the measured -weighted signal, signal depletion at high concentration, and partial-volume effects. A potential solution could be to derive the AIF from separately acquired dynamic contrast enhanced (DCE) MRI data. We aim to compare the AIF determined from DCE MRI with the AIF from DSC MRI, and estimated perfusion coefficients derived from DSC data using a DCE-driven AIF with perfusion coefficients determined using a DSC-based AIF. AIFs were manually selected in branches of the middle cerebral artery (MCA) in both DCE and DSC data in each patient. In addition, a semi-automatic AIF-selection algorithm was applied to the DSC data. The amplitude and full width at half-maximum of the AIFs were compared statistically using the Wilcoxon rank-sum test, applying a 0.05 significance level. Cerebral blood flow (CBF) was derived with different AIF approaches and compared further. The results showed that the AIFs extracted from DSC scans yielded highly variable peaks across arteries within the same patient. The semi-automatic DSC-AIF had significantly narrower width compared with the manual AIFs, and a significantly larger peak than the manual DSC-AIF. Additionally, the DCE-based AIF provided a more stable measurement of relative CBF and absolute CBF values estimated with DCE-AIFs that were compatible with previously reported values. In conclusion, DCE-based AIFs were reproduced significantly better across vessels, showed more realistic profiles, and delivered more stable and reasonable CBF measurements. The DCE-AIF can, therefore, be considered as an alternative AIF source for quantitative perfusion estimations in DSC MRI.

Type 2 diabetes mellitus and coronary artery disease: features of perfusion volume computed tomography of the heart in a pharmacological test with adenosine triphosphate

To study myocardial perfusion in patients with coronary artery disease (CAD) with and without type 2 diabetes mellitus (DM) using volumetric computed tomography (VCT) of the heart with a pharmacological test with adenosine triphosphate (ATP). The study included 93 patients, of which 18 had CAD with DM, and 50 had CAD without DM. All patients underwent one of the stress tests, cardiac VCT with ATP test, invasive coronary angiography, or CT coronary angiography. Left ventricle (LV) myocardial perfusion was evaluated for hypoperfusion zones and the calculation of semi-quantitative indices: decrease of LV myocardial density, LV myocardial perfusion index, transmural perfusion coefficient, and our proposed new indicator - myocardial perfusion reserve (MPR). The MPR index value in the hypoperfusion zones in patients with CAD and DM was 0.64 [0.62-0.66], in patients with CAD without diabetes 0.65 [0.63-0.66]; p=0.4; the value of the transmural perfusion coefficient in the areas of abnormal LV myocardial perfusion in patients with CAD and DM was 0.81 [0.80-0.86] versus 0.83 [0.80-0.85] in patients with CAD without DM (p=0.6). More hypoperfusion segments were observed in patients with CAD and DM (33.3%) compared to those without DM (14%; p=0.029). The MPR index in the hypoperfusion zones in patients with CAD with intact coronary arteries (CA) and DM was 0.56 [0.54-0.60] versus 0.55 [0.54-0.62] in patients with CAD with intact CA without DM; p=0.2. In patients with CAD and type 2 DM, according to the VCT with ATP test, more foci hypoperfusion areas were detected, regardless of the severity of coronary artery involvement, compared with patients with CAD without DM, which may be due to the microangiopathy in the myocardium. The similarity of the MPR parameters in the hypoperfusion zones associated with hemodynamic stenosis of the CA and with intact CAs indicates the ischemic genesis of these zones. For citation: Soboleva GN, Minasyan AA, Gaman SA, Rogoza AN, Molina LP, Soboleva TV, Shariya MA, Ternovoy SK, Karpov YuA. Type 2 diabetes mellitus and coronary artery disease: features of perfusion volume computed tomography of the heart in a pharmacological test with adenosine triphosphate. Terapevticheskii Arkhiv (Ter. Arkh.). 2023;95(4):309-315. DOI: 10.26442/00403660.2023.04.202158.

Predicting lymphovascular invasion in rectal cancer: evaluating the performance of golden-angle radial sparse parallel MRI for rectal perfusion assessment

This study aims to determine whether the dual-parameter approach combined with either time-resolved angiography with stochastic trajectories (TWIST) or golden-angle radial sparse parallel (GRASP) and diffusion-weighted imaging (DWI) has superior diagnostic performance in predicting pathological lymphovascular invasion (pLVI) rectal cancer when compared with traditional single-parameter evaluations using DWI alone. Patients with pathologically confirmed rectal cancer were enrolled. Perfusion (influx forward volume transfer constant [Ktrans] and rate constant [Kep]) and apparent diffusion coefficient (ADC) were measured by two researchers. For both sequences, areas under receiver operating characteristic (ROCs) to predict pLVI-positive rectal cancer were compared. A total of 179 patients were enrolled in our study. A combined analysis of ADC and perfusion parameters (Ktrans) acquired with GRASP yielded a higher diagnostic performance compared with diffusion parameters alone (area under the curve, 0.91 ± 0.03 vs. 0.71 ± 0.06, P < 0.001); However, ADC with GRASP-acquired Kep and ADC with TWIST-acquired perfusion parameters (Ktrans or Kep) did not offer any additional benefit. The Ktrans of the GRASP technique improved the diagnostic performance of multiparametric MRI to predict rectal cancers with pLVI-positive. In contrast, TWIST did not achieve this effect.

Inverse problems of damped wave equations with Robin boundary conditions: an application to blood perfusion

Knowledge of the properties of biological tissues is essential in monitoring any abnormalities that may be forming and have a major impact on organs malfunctioning. Therefore, these disorders must be detected and treated early to save lives and improve the general health. Within the framework of thermal therapies, e.g. hyperthermia or cryoablation, the knowledge of the tissue temperature and of the blood perfusion rate are of utmost importance. Therefore, motivated by such a significant biomedical application, this paper investigates, for the first time, the uniqueness and stable reconstruction of the space-dependent (heterogeneous) perfusion coefficient in the thermal-wave hyperbolic model of bio-heat transfer from Cauchy boundary data using the powerful technique of Carleman estimates. Additional novelties consist in the consideration of Robin boundary conditions, as well as developing a mathematical analysis that leads to stronger stability estimates valid over a shorter time interval than usually reported in the literature of coefficient identification problems for hyperbolic partial differential equations. Numerically, the inverse coefficient problem is recast as a nonlinear least-squares minimization that is solved using the conjugate gradient method (CGM). Both exact and noisy data are inverted. To achieve stability, the CGM is stopped according to the discrepancy principle. Numerical results for a physical example are presented and discussed, showing the convergence, accuracy and stability of the inversion procedure.

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

ObjectivesThis 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 methodsTwenty-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 [Ktrans], 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. ResultsD-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, Ktrans, 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). ConclusionsThe 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.

Determination of the space-dependent blood perfusion coefficient in the thermal-wave model of bio-heat transfer

PurposeWhen modeling heat propagation in biological bodies, a non-negligible relaxation time (typically between 15-30 s) is required for the thermal waves to accumulate and transfer, i.e. thermal waves propagate at a finite velocity. To accommodate for this feature that is characteristic to heat transfer in biological bodies, the classical Fourier's law has to be modified resulting in the thermal-wave model of bio-heat transfer. The purpose of the paper is to retrieve the space-dependent blood perfusion coefficient in such a thermal-wave model of bio-heat transfer from final time temperature measurements.Design/methodology/approachThe non-linear and ill-posed blood perfusion coefficient identification problem is reformulated as a non-linear minimization problem of a Tikhonov regularization functional subject to lower and upper simple bounds on the unknown coefficient. For the numerical discretization, an unconditionally stable direct solver based on the Crank–Nicolson finite difference scheme is developed. The Tikhonov regularization functional is minimized iteratively by the built-in routine lsqnonlin from the MATLAB optimization toolbox. Both exact and numerically simulated noisy input data are inverted.FindingsThe reconstruction of the unknown blood perfusion coefficient for three benchmark numerical examples is illustrated and discussed to verify the proposed numerical procedure. Moreover, the proposed algorithm is tested on a physical example which consists of identifying the blood perfusion rate of a biological tissue subjected to an external source of laser irradiation. The numerical results demonstrate that accurate and stable solutions are obtained.Originality/valueAlthough previous studies estimated the important thermo-physical blood perfusion coefficient, they neglected the wave-like nature of heat conduction present in biological tissues that are captured by the more accurate thermal-wave model of bio-heat transfer. The originalities of the present paper are to account for such a more accurate thermal-wave bio-heat model and to investigate the possibility of determining its space-dependent blood perfusion coefficient from temperature measurements at the final time.

Analytical assessment of the time‐space fractional bioheat transfer equation by the radial basis function method for living tissues

AbstractIn recent years, thermal treatment has proven to be helpful, notably in oncology. In fact, ablating the superfluous mass and eliminating the malignant tumor using a different modality such as warmth or cooling is a therapeutic method. In this study, the radial basis function approach was used to answer the time‐space fractional heat transfer equations of human body tissue during thermal therapy. To validate the radial basis function technique, it was also compared to the fourth‐order Runge–Kutta numerical method. The findings demonstrated that this methodology is extremely accurate and efficient, with an error rate of less than 1%. The effect of time and spatial fractional parameters, blood perfusion coefficient, metabolic coefficient, and internal source coefficient on the temperature profile inside human living tissues has been studied and depicted well.

Grading of pancreatic neuroendocrine neoplasms with imaging: an update

Imaging evaluation of pancreatic neuroendocrine neoplasms is developing with the updating of pathological grading. Tumor size, blood perfusion and apparent diffusion coefficient(ADC)value are the most commonly used imaging indicators for the evaluation of the malignancy of pancreatic neuroendocrine neoplasms, as well as other imaging characteristics representing the tumor invasiveness. Dual-probe imaging with SSR-PET and FDG-PET can further improve the accuracy of diagnosis and classification of pancreatic neuroendocrine neoplasms, and provide further information for the tumor treatment and prognosis. Quantitative analysis including texture analysis and radiomics is also a new topic in the research of pancreatic neuroendocrine neoplasms. The combination of morphology, functional imaging and quantitative analysis may contribute to the non-invasive evaluation of the malignancy of pancreatic neuroendocrine neoplasms.

Numerical evaluation of the duodenal mucosal resurfacing technique for the treatment of Type 2 diabetes

Backgrounds and objectivesThis work presents a numerical analysis of the Duodenal Mucosal Resurfacing (DMR) technique, which is a relatively new treatment for Type 2 diabetes that has been already tested in human beings. In this innovative strategy, an endoscopic catheter is placed inside the duodenum thus serving as a guide to an ablation device. A circumferential ablation is then performed by using a balloon filled with a hot fluid with pre- and post-cooling stages that allows for a controlled thermal procedure. Clinical outcomes indicate that the damaged duodenal lining induces a better control of glycemic levels. Therefore, a numerical evaluation of the efficiency of this treatment is carried out by utilizing the bioheat transfer equation in the transient form. MethodsThe finite volume method is used in the discretization of the energy equation and the results are verified by exploring the same mathematical model in a commercial finite-element package. The Arrhenius criterion for the evaluation of the thermally affected tissue is employed in this study. ResultsA systematic analysis of the simulations is performed by investigating two scenarios: one in which the lifting of the mucosal duodenum layer is achieved and another one where the lifting strategy is not implemented. The role of the magnitude of the blood perfusion coefficient, tissue thermal conductivity, peak, pre- and post-cooling temperatures is thoroughly explored, especially in connection with the evaluation of the extent of the thermally affected region. ConclusionsAccording to the simulations discussed in the present contribution, this treatment is capable of accurately targeting the cells in the mucosal layer without significantly affecting the outermost stratum of the organ if the lifting process is applied. However, for the case without lifting, the muscularis propria layer may reach temperatures above 42 °C during a short time interval and thus the treatment should be considered with caution by the physician.

Perfusion parameters derived from MRI for preoperative prediction of IDH mutation and MGMT promoter methylation status in glioblastomas

PurposeTo investigate the feasibility for preoperative prediction of IDH mutation and MGMT promoter methylation status in glioblastomas(GBMs) by intravoxel incoherent motion(IVIM) and dynamic susceptibility contrast(DSC). MethodsPreoperative IVIM and DSC images of 71 patients(IDH mutation:45, IDH wildtype: 26; MGMT methylation: 31, MGMT unmethylation:40) with glioblastomas were analyzed retrospectively. Perfusion parameters including microcirculation perfusion coefficient(D*), perfusion fraction(f), cerebral blood volume(CBV) and cerebral blood flow(CBF) were measured. Corrected perfusion parameters containing corrected perfusion coefficient(ADCperf) and simplified perfusion fraction(SPF) were from the simplified IVIM with 3 b values. Correlations among parameters were analyzed by Spearman correlation. All parameters were compared with Mann-Whitney U test. Univariate and multivariate logistic regression models were constructed. The receiver operating characteristic(ROC) curve was analyzed. ResultsThe IVIM parameters showed merely moderate correlations with CBV and showed no correlation with CBF. IDH mutation GBMs showed lower D*, ADCperf, SPF, CBV and higher f than IDH wildtype GBMs(all p < 0.05). D* was the independent predictor for IDH mutation with the highest AUC of 0.912(95%CI: 0.821–0.966). The D*, ADCperf, SPF and CBV of MGMT promoter methylation GBMs were lower than unmethylation GBMs while f was higher(all p < 0.05). Multivariate model showed the highest prediction efficacy for MGMT promoter methylation with an AUC of 0.915(95%CI: 0.824–0.968). The CBF was not useful in distinguishing IDH mutation and MGMT promoter methylation status(p = 0.055, 0.215). ConclusionIDH mutation and MGMT promoter methylation status in GBMs can be assessed effectively by IVIM and DSC. Besides, D* was the independent predictor of IDH mutation status.

A numerical study of space‐fractional three‐phase‐lag bioheat transfer model during thermal therapy

AbstractPrediction of accurate temperature profile and control of temperature are two important factors to treat the cancerous cells effectively in the living tissue during thermal therapy. To deal with this, we have generated a space‐fractional mathematical model of bioheat transfer within the living skin tissue by using three‐phase‐lag constitutive relation. The present model with Dirichlet's boundary condition is investigated in the companionship of the metabolic and external heat source during the thermal therapy. Exponentially decaying (with position) laser heat source is used as an external heating source term. To find out the solution, the model is converted to an initial value problem by using a fractional backward finite difference scheme and then Runge–Kutta (4,5) scheme is applied for determining the temperature profile within the living biological skin tissue. The effect on the dimensionless temperature profile during thermal therapy due to variations in the value of parameters like an order of space‐fractional derivative, relaxation times, blood perfusion coefficient, rate of thermal conductivity, and the external laser heat source incorporated in the current bioheat transfer model is discussed graphically. Results obtained from the study are beneficial in the field of medicine, especially for oncologists.

Optimization of pseudo-continuous arterial spin labeling at 7T with parallel transmission B1 shimming.

PurposeTo optimize pseudo‐continuous arterial spin labeling (pCASL) for 7 T, and to further improve the labeling efficiency with parallel RF transmission transmit B1 (B1+) shimming.MethodspCASL parameters were optimized based on B1+/B0 field distributions at 7 T with simulation. To increase labeling efficiency, the B1+ amplitude at inflowing arteries was increased with parallel RF transmission B1+ shimming. The “indv‐shim” with shimming weights calculated for each individual subject, and the “univ‐shim” with universal weights calculated on a group of 12 subjects, were compared with circular polarized (CP) shim. The optimized pCASL sequences with three B1+ shimming modes (indv‐shim, univ‐shim, and CP‐shim) were evaluated in 6 subjects who underwent two repeated scans 24 hours apart, along with a pulsed ASL sequence. Quantitative metrics including mean B1+ amplitude, perfusion, and intraclass correlation coefficient were calculated. The optimized 7T pCASL was compared with standard 3T pCASL on 5 subjects, using spatial SNR and temporal SNR.ResultsThe optimal pCASL parameter set (RF duration/gap = 300/250 us, Gave=0.6mT/m,gRatio=10) achieved robust perfusion measurement in the presence of B1+/B0 inhomogeneities. Both indv‐shim and univ‐shim significantly increased B1+ amplitude compared with CP‐shim in simulation and in vivo experiment (P < .01). Compared with CP‐shim, perfusion signal was increased by 9.5% with indv‐shim (P < .05) and by 5.3% with univ‐shim (P = .35). All three pCASL sequences achieved fair to good repeatability (intraclass correlation coefficient ≥ 0.5). Compared with 3T pCASL, the optimized 7T pCASL achieved 78.3% higher spatial SNR and 200% higher temporal SNR.ConclusionThe optimized pCASL achieved robust perfusion imaging at 7 T, while both indv‐shim and univ‐shim further increased labeling efficiency.

Quantification of intravoxel incoherent motion with optimized b-values using deep neural network.

To develop a framework for quantifying intravoxel incoherent motion (IVIM) parameters, where a neural network for quantification and b-values for diffusion-weighted imaging are simultaneously optimized. A deep neural network (DNN) method is proposed for accurate quantification of IVIM parameters from multiple diffusion-weighted images. In addition, optimal b-values are selected to acquire the multiple diffusion-weighted images. The proposed framework consists of an MRI signal generation part and an IVIM parameter quantification part. Monte-Carlo (MC) simulations were performed to evaluate the accuracy of the IVIM parameter quantification and the efficacy of b-value optimization. In order to analyze the effect of noise on the optimized b-values, simulations were performed with five different noise levels. For in vivo data, diffusion images were acquired with the b-values from four b-values selection methods for five healthy volunteers at 3T MRI system. Experiment results showed that both the optimization of b-values and the training of DNN were simultaneously performed to quantify IVIM parameters. We found that the accuracies of the perfusion coefficient (Dp ) and perfusion fraction (f) were more sensitive to b-values than the diffusion coefficient (D) was. Furthermore, when the noise level changed, the optimized b-values also changed. Therefore, noise level has to be considered when optimizing b-values for IVIM quantification. The proposed scheme can simultaneously optimize b-values and train DNN to minimize quantification errors of IVIM parameters. The trained DNN can quantify IVIM parameters from the diffusion-weighted images obtained with the optimized b-values.

Texture analysis for chemotherapy response evaluation in osteosarcoma using MR imaging.

The efficacy of MRI-based statistical texture analysis (TA) in predicting chemotherapy response among patients with osteosarcoma was assessed. Forty patients (male: female = 31:9; age = 17.2 ± 5.7 years) with biopsy-proven osteosarcoma were analyzed in this prospective study. Patients were scheduled for three cycles of neoadjuvant chemotherapy (NACT) and diffusion-weighted MRI acquisition at three time points: at baseline (t0), after the first NACT (t1) and after the third NACT (t2) using a 1.5 T scanner. Eight patients (nonsurvivors) died during NACT while 34 patients (survivors) completed the NACT regimen followed by surgery. Histopathological evaluation was performed in the resected tumor to assess NACT response (responder [≤50% viable tumor] and nonresponder [>50% viable tumor]) and revealed nonresponder: responder = 20:12. Apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) parameters, diffusion coefficient (D), perfusion coefficient (D*) and perfusion fraction (f) were evaluated. A total of 25 textural features were evaluated on ADC, D, D* and f parametric maps and structural T1-weighted (T1W) and T2-weighted (T2W) images in the entire tumor volume using 3D TA methods gray-level cooccurrence matrix (GLCM), neighborhood gray-tone-difference matrix (NGTDM) and run-length matrix (RLM). Receiver-operating-characteristic curve analysis was performed on the selected textural feature set to assess the role of TA features (a) as marker(s) of tumor aggressiveness leading to mortality at baseline and (b) in predicting the NACT response among survivors in the course of treatment. Findings showed that the NGTDM features coarseness, busyness and strength quantifying tumor heterogeneity in D, D* and f maps and T1W and T2W images were useful markers of tumor aggressiveness in identifying the nonsurvivor group (area-under-the-curve [AUC] = 0.82-0.88) at baseline. The GLCM features contrast and correlation, NGTDM features contrast and complexity and RLM feature short-run-low-gray-level-emphasis quantifying homogeneity/terogeneity in tumor were effective markers for predicting chemotherapeutic response using D (AUC = 0.80), D* (AUC = 0.80) and T2W (AUC = 0.70) at t0, and D* (AUC = 0.80) and f (AUC = 0.70) at t1. 3D statistical TA features might be useful as imaging-based markers for characterizing tumor aggressiveness and predicting chemotherapeutic response in patients with osteosarcoma.