Modeling of the contrast-enhanced perfusion test in liver based on the multi-compartment flow in porous media.

The paper deals with modeling the liver perfusion intended to improve quantitative analysis of the tissue scans provided by the contrast-enhanced computed tomography (CT). For this purpose, we developed a model of dynamic transport of the contrast fluid through the hierarchies of the perfusion trees. Conceptually, computed time-space distributions of the so-called tissue density can be compared with the measured data obtained from CT; such a modeling feedback can be used for model parameter identification. The blood flow is characterized at several scales for which different models are used. Flows in upper hierarchies represented by larger branching vessels are described using simple 1D models based on the Bernoulli equation extended by correction terms to respect the local pressure losses. To describe flows in smaller vessels and in the tissue parenchyma, we propose a 3D continuum model of porous medium defined in terms of hierarchically matched compartments characterized by hydraulic permeabilities. The 1D models corresponding to the portal and hepatic veins are coupled with the 3D model through point sources, or sinks. The contrast fluid saturation is governed by transport equations adapted for the 1D and 3D flow models. The complex perfusion model has been implemented using the finite element and finite volume methods. We report numerical examples computed for anatomically relevant geometries of the liver organ and of the principal vascular trees. The simulated tissue density corresponding to the CT examination output reflects a pathology modeled as a localized permeability deficiency.

Development of a mathematical model to estimate intra-tumor oxygen concentrations through multi-parametric imaging.

BACKGROUND: Tumor hypoxia is involved in every stage of solid tumor development: formation, progression, metastasis, and apoptosis. Two types of hypoxia exist in tumors-chronic hypoxia and acute hypoxia. Recent studies indicate that the regional hypoxia kinetics is closely linked to metastasis and therapeutic responses, but regional hypoxia kinetics is hard to measure. We propose a novel approach to determine the local pO2 by fusing the parameters obtained from in vivo functional imaging through the use of a modified multivariate Krogh model. METHODS: To test our idea and its potential to translate into an in vivo setting through the use of existing imaging techniques, simulation studies were performed comparing the local partial oxygen pressure (pO2) from the proposed multivariate image fusion model to the referenced pO2 derived by Green's function, which considers the contribution from every vessel segment of an entire three-dimensional tumor vasculature to profile tumor oxygen with high spatial resolution. RESULTS: pO2 derived from our fusion approach were close to the referenced pO2 with regression slope near 1.0 and an r2 higher than 0.8 if the voxel size (or the spatial resolution set by functional imaging modality) was less than 200 µm. The simulation also showed that the metabolic rate, blood perfusion, and hemoglobin concentration were dominant factors in tissue oxygenation. The impact of the measurement error of functional imaging to the pO2 precision and accuracy was simulated. A Gaussian error function with FWHM equal to 20 % of blood perfusion or fractional vascular volume measurement contributed to average 7 % statistical error in pO2. CONCLUSION: The simulation results indicate that the fusion of multiple parametric maps through the biophysically derived mathematical models can monitor the intra-tumor spatial variations of hypoxia in tumors with existing imaging methods, and the potential to further investigate different forms of hypoxia, such as chronic and acute hypoxia, in response to cancer therapies.

Treatment decision-making for post-partum hemorrhage using dynamic contrast-enhanced computed tomography.

AIM: Post-partum hemorrhage (PPH) is the leading cause of maternal mortality. Identification of the precise bleeding site is generally important to control hemorrhage, but such an approach has not been fully established in the context of PPH. We postulated that visualization of bleeding sites could aid treatment decisions in the management of PPH. METHODS: We conducted a prospective review of 26 patients who underwent dynamic computed tomography (CT) for PPH. RESULTS: A total of 17 cases presented with uterine bleeding, eight with vaginal hematomas, and one with hemoperitoneum. Overall, dynamic CT identified contrast media extravasation in the arterial phase in 12 of 26 (46.2%) cases: the upper (n = 4) and the lower uterine segment including the cervix (n = 2), subfascial space (n = 1) and vagina (n = 5). Identification of precise arterial bleeding sites using CT provided informative guidance about where to place balloons for intractable uterine bleeding, and how to manage hemoperitoneum and vaginal hematomas. In addition, dynamic CT revealed the existence of a subtype of uterine atony, which is characterized by focal active arterial bleeding in the upper uterine segment. Furthermore, negative contrast extravasation extracted cases of PPH that were well controlled without the need for surgical or radiological intervention. No patient required emergency hysterectomy to control PPH. CONCLUSION: Dynamic CT has potential clinical utility in treatment decision-making for PPH.

Dynamic contrast-enhanced computed tomography perfusion parameters of canine suspected brain tumors at baseline and during radiotherapy might be different depending on tumor location but not associated with survival.

Introduction: Treatment of brain tumors in dogs can be associated with significant morbidity and reliable prognostic factors are lacking. Dynamic contrast-enhanced computed tomography (DCECT) can be used to assess tumor perfusion. The objectives of this study were to assess perfusion parameters and change in size of suspected brain tumors before and during radiotherapy (RT) depending on their location and find a potential correlation with survival. Methods: Seventeen client-owned dogs with suspected brain tumors were prospectively recruited. All dogs had a baseline DCECT to assess mass size, blood volume (BV), blood flow (BF), and transit time (TT). Twelve dogs had a repeat DCECT after 12 Gy of megavoltage RT. Survival times were calculated. Results: Intra-axial masses had lower BF (p = 0.005) and BV (p < 0.001) than extra-axial masses but not than pituitary masses. Pituitary masses had lower BF (p = 0.001) and BV (p = 0.004) than extra-axial masses. The volume of the mass was positively associated with TT (p = 0.001) but not with BF and BV. Intra-axial masses showed a more marked decrease in size than extra-axial and pituitary masses during RT (p = 0.022 for length, p = 0.05 for height). Extra-axial masses showed a greater decrease in BF (p = 0.011) and BV (p = 0.012) during RT than pituitary masses and intra-axial masses. Heavier dogs had a shorter survival time (p = 0.011). Perfusion parameters were not correlated with survival. Conclusion: DCECT perfusion parameters and change in size of brain masses during RT might be different based on the location of the mass.

Application of CD34 expression combined with three-phase dynamic contrast-enhanced computed tomography scanning in preoperative staging of gastric cancer.

BACKGROUND: Accurate preoperative staging of gastric cancer (GC), a common malignant tumor worldwide, is critical for appropriate treatment plans and prognosis. Dynamic three-phase enhanced computed tomography (CT) scanning for preoperative staging of GC has limitations in evaluating tumor angiogenesis. CD34, a marker on vascular endothelial cell surfaces, is promising in evaluating tumor angiogenesis. We explored the value of their combination for preoperative staging of GC to improve the efficacy and prognosis of patients with GC. AIM: To explore the evaluation value of CD34 expression + dynamic three-phase enhanced CT scanning in preoperative staging of GC. METHODS: Medical records of 106 patients with GC treated at the First People's Hospital of Lianyungang between February 2021 and January 2023 were retrospectively studied. All patients underwent three-phase dynamic contrast-enhanced CT scanning before surgery, and CD34 was detected in gastroscopic biopsy specimens. Using surgical and pathological results as the gold standard, the diagnostic results of three-phase dynamic contrast-enhanced CT scanning at different T and N stages were analyzed, and the expression of CD34-marked microvessel density (MVD) at different T and N stages was determined. The specificity and sensitivity of three-phase dynamic contrast-enhanced CT and CD34 in T and N staging were calculated; those of the combined diagnosis of the two were evaluated in parallel. Independent factors affecting lymph node metastasis were analyzed using multiple logistic regression. RESULTS: The accuracy of three-phase dynamic contrast-enhanced CT scanning in diagnosing stages T1, T2, T3 and T4 were 68.00%, 75.00%, 79.41%, and 73.68%, respectively, and for diagnosing stages N0, N1, N2, and N3 were 75.68%, 74.07%, 85.00%, and 77.27%, respectively. CD34-marked MVD expression increased with increasing T and N stages. Specificity and sensitivity of three-phase dynamic contrast-enhanced CT in T staging were 86.79% and 88.68%; for N staging, 89.06% and 92.86%; for CD34 in T staging, 64.15% and 88.68%; and for CD34 in N staging, 84.38% and 78.57%, respectively. Specificity and sensitivity of joint diagnosis in T staging were 55.68% and 98.72%, and N staging were 75.15% and 98.47%, respectively, with the area under the curve for diagnosis improving accordingly. According to multivariate analysis, a longer tumor diameter, higher pathological T stage, lower differentiation degree, and higher expression of CD34-marked MVD were independent risk factors for lymph node metastasis in patients with GC. CONCLUSION: With high accuracy in preoperatively determining the invasion depth and lymph node metastasis of GC, CD34 expression and three-phase dynamic contrast-enhanced CT can provide a reliable basis for surgical resection.

Prediction of Microvascular Invasion in Hepatocellular Carcinoma With a Multi-Disciplinary Team-Like Radiomics Fusion Model on Dynamic Contrast-Enhanced Computed Tomography.

OBJECTIVE: To investigate microvascular invasion (MVI) of HCC through a noninvasive multi-disciplinary team (MDT)-like radiomics fusion model on dynamic contrast enhanced (DCE) computed tomography (CT). METHODS: This retrospective study included 111 patients with pathologically proven hepatocellular carcinoma, which comprised 57 MVI-positive and 54 MVI-negative patients. Target volume of interest (VOI) was delineated on four DCE CT phases. The volume of tumor core (V tc ) and seven peripheral tumor regions (V pt , with varying distances of 2, 4, 6, 8, 10, 12, and 14 mm to tumor margin) were obtained. Radiomics features extracted from different combinations of phase(s) and VOI(s) were cross-validated by 150 classification models. The best phase and VOI (or combinations) were determined. The top predictive models were ranked and screened by cross-validation on the training/validation set. The model fusion, a procedure analogous to multidisciplinary consultation, was performed on the top-3 models to generate a final model, which was validated on an independent testing set. RESULTS: Image features extracted from V tc +V pt(12mm) in the portal venous phase (PVP) showed dominant predictive performances. The top ranked features from V tc +V pt(12mm) in PVP included one gray level size zone matrix (GLSZM)-based feature and four first-order based features. Model fusion outperformed a single model in MVI prediction. The weighted fusion method achieved the best predictive performance with an AUC of 0.81, accuracy of 78.3%, sensitivity of 81.8%, and specificity of 75% on the independent testing set. CONCLUSION: Image features extracted from the PVP with V tc +V pt(12mm) are the most reliable features indicative of MVI. The MDT-like radiomics fusion model is a promising tool to generate accurate and reproducible results in MVI status prediction in HCC.

Dynamic contrast-enhanced computed tomography diagnosis of primary liver cancers using transfer learning of pretrained convolutional neural networks: Is registration of multiphasic images necessary?

PURPOSE: To evaluate the effect of image registration on the diagnostic performance of transfer learning (TL) using pretrained convolutional neural networks (CNNs) and three-phasic dynamic contrast-enhanced computed tomography (DCE-CT) for primary liver cancers. METHODS: We retrospectively evaluated 215 consecutive patients with histologically proven primary liver cancers, including six early, 58 well-differentiated, 109 moderately differentiated, 29 poorly differentiated hepatocellular carcinomas (HCCs), and 13 non-HCC malignant lesions containing cholangiocellular components. We performed TL using various pretrained CNNs and preoperative three-phasic DCE-CT images. Three-phasic DCE-CT images were manually registered to correct respiratory motion. The registered DCE-CT images were then assigned to the three color channels of an input image for TL: pre-contrast, early phase, and delayed phase images for the blue, red, and green channels, respectively. To evaluate the effects of image registration, the registered input image was intentionally misaligned in the three color channels by pixel shifts, rotations, and skews with various degrees. The diagnostic performances (DP) of the pretrained CNNs after TL in the test set were compared by three general radiologists (GRs) and two experienced abdominal radiologists (ARs). The effects of misalignment in the input image and the type of pretrained CNN on the DP were statistically evaluated. RESULTS: The mean DPs for histological subtype classification and differentiation in primary malignant liver tumors on DCE-CT for GR and AR were 39.1%, and 47.9%, respectively. The highest mean DPs for CNNs after TL with pixel shifts, rotations, and skew misalignments were 44.1%, 44.2%, and 43.7%, respectively. Two-way analysis of variance revealed that the DP is significantly affected by the type of pretrained CNN (P = 0.0001), but not by misalignments in input images other than skew deformations. CONCLUSION: TL using pretrained CNNs is robust against misregistration of multiphasic images and comparable to experienced ARs in classifying primary liver cancers using three-phasic DCE-CT.

Optimal timing of contrast-enhanced computed tomography in an evaluation of severe acute pancreatitis-associated complications.

Dynamic contrast-enhanced computed tomography (CECT) has been used previously to evaluate severe acute pancreatitis (SAP)-associated complications. However, optimal time points of CECT have not yet been established. The present study aimed to determine optimal timings for CECT to be undertaken for patients with SAP. The results of CECT from 309 patients with SAP, who were classified into either infected or non-infected SAP groups, were retrospectively analyzed. The severity and alterations in the periods within 72 h to >4 weeks of SAP onset were also assessed. In the analysis of the disease severity and changes, acute peripancreatic fluid collection was detected, where the number of areas increased within 1 week of SAP onset but decreased within 4 weeks and longer. However, no significant differences were observed between the infected and non-infected groups. The acute necrotic collection (ANC) areas were ≤30% of the area of the pancreas, with significantly more ANC areas and pancreatic necrosis in the infected SAP group compared with the non-infected SAP group at a time interval of >4 weeks. The exudation of pleural effusion (PE) was elevated within 1 week, but decreased within 2 weeks and longer. The difference in the alteration of the exudation of PE was not statistically different between the two groups. In conclusion, the results suggest that the period between 72 h and 1 week of SAP onset is optimal timing of CECT to assess SAP-associated complications, particularly for infected SAP patients.

Interobserver and Intraobserver Reproducibility with Volume Dynamic Contrast Enhanced Computed Tomography (DCE-CT) in Gastroesophageal Junction Cancer.

The purpose of this study was to assess inter- and intra-observer reproducibility of three different analytic methods to evaluate quantitative dynamic contrast-enhanced computed tomography (DCE-CT) measures from gastroesophageal junctional cancer. Twenty-five DCE-CT studies with gastroesophageal junction cancer were selected from a previous longitudinal study. Three radiologists independently reviewed all scans, and one repeated the analysis eight months later for intraobserver analysis. Review of the scans consisted of three analysis methods: (I) Four, fixed small sized regions of interest (2-dimensional (2D) fixed ROIs) placed in the tumor periphery, (II) 2-dimensional regions of interest (2D-ROI) along the tumor border in the tumor center, and (III) 3-dimensional volumes of interest (3D-VOI) containing the entire tumor volume. Arterial flow, blood volume and permeability (k(trans)) were recorded for each observation. Inter- and intra-observer variability were assessed by Intraclass Correlation Coefficient (ICC) and Bland-Altman statistics. Interobserver ICC was excellent for arterial flow (0.88), for blood volume (0.89) and for permeability (0.91) with 3D-VOI analysis. The 95% limits of agreement were narrower for 3D analysis compared to 2D analysis. Three-dimensional volume DCE-CT analysis of gastroesophageal junction cancer provides higher inter- and intra-observer reproducibility with narrower limits of agreement between readers compared to 2D analysis.

Early evaluation of targeted therapy effectiveness in non-small cell lung cancer by dynamic contrast-enhanced CT.

PURPOSE: To study the feasibility and clinical value of dynamic contrast-enhanced (DCE) computed tomography (CT) for early evaluation of targeted therapy efficacy in non-small cell lung cancer (NSCLC). METHODS: We measured tumor diameter, peak height (PH), time to peak (TP), tumor mass-aortic peak height ratio (M/A), and blood perfusion (BP) in 20 patients with advanced NSCLC using DCE-CT before and 7 days after treatment. Therapy efficacy was assessed with conventional CT 4-6 weeks post-treatment. RESULTS: Patients were grouped into those with partial response (PR), stable disease (SD), and progressive disease (PD) according to the therapy efficacy assessment at 4-6 weeks post-treatment. The PR group primary tumor diameter (P = 0.0007) and BP (P = 0.0225) were reduced at 7 days post-treatment; the SD group DCE-CT value changes were not significant. The PD group M/A (P = 0.0443) and BP (P = 0.0268) were increased 7 days post-treatment. The BP decrease group had significantly longer progression-free survival than the BP increase group (median, 54 vs. 6 weeks). CONCLUSION: DCE-CT can evaluate targeted therapy efficacy at 7 days post-treatment. Decreased primary tumor diameter and BP indicate tumor sensitivity to therapy; increased BP with unchanged tumor diameter suggests the tumor is not sensitive to therapy. Reduced BP suggests treatment effectiveness.

Technical prerequisites and imaging protocols for CT perfusion imaging in oncology.

The aim of this review article is to define the technical prerequisites of modern state-of-the-art CT perfusion imaging in oncology at reasonable dose levels. The focus is mainly on abdominal and thoracic tumor imaging, as they pose the largest challenges with respect to attenuation and patient motion. We will show that low kV dynamic scanning in conjunction with detection technology optimized for low photon fluxes has the highest impact on reducing dose independently of other choices made in the protocol selection. We discuss, derived from relatively simple first principles, on what appropriate temporal sampling and total scan duration depend on and why optimized contrast medium injection protocols are also essential in limiting dose. Finally we will examine the possibility of simultaneously extracting standard morphological and functional information from one single 4D examination as a potential enabler for a more widespread use of dynamic contrast enhanced CT in oncology.

Diagnostic performance of hyperaemic myocardial blood flow index obtained by dynamic computed tomography: does it predict functionally significant coronary lesions?

AIMS: The severity of coronary artery narrowing is a poor predictor of functional significance, in particular in intermediate coronary lesions (30-70% diameter narrowing). The aim of this work was to compare the performance of a quantitative hyperaemic myocardial blood flow (MBF) index derived from adenosine dynamic computed tomography perfusion (CTP) imaging with that of visual CT coronary angiography (CTCA) and semi-automatic quantitative CT (QCT) in the detection of functionally significant coronary lesions in patients with stable chest pain. METHODS AND RESULTS: CTCA and CTP were performed in 80 patients (210 analysable coronary vessels) referred to invasive coronary angiography (ICA). The MBF index (mL/100 mL/min) was computed using a model-based parametric deconvolution method. The diagnostic performance of the MBF index in detecting functionally significant coronary lesions was compared with visual CTCA and QCT. Coronary lesions with invasive fractional flow reserve of ≤0.75 were defined as functionally significant. The optimal cut-off value of the MBF index to detect functionally significant coronary lesions was 78 mL/100 mL/min. On a vessel-territory level, the MBF index had a larger area under the curve (0.95; 95% confidence interval [95% CI]: 0.92-0.98) compared with visual CTCA (0.85; 95% CI: 0.79-0.91) and QCT (0.89; 95% CI: 0.84-0.93) (both P-values <0.001). In the analysis restricted to intermediate coronary lesions, the specificity of visual CTCA (69%) and QCT (77%) could be improved by the subsequent use of the MBF index (89%). CONCLUSION: In this proof-of-principle study, the MBF index performed better than visual CTCA and QCT in the identification of functionally significant coronary lesions. The MBF index had additional value beyond CTCA anatomy in intermediate coronary lesions. This may have a potential to support patient management.

Tumor perfusion imaging predicts the intra-tumoral accumulation of liposomes.

Liposomes have proven to be a viable drug delivery strategy resulting in significant increases in tumor accumulation of drugs via exploitation of the enhanced permeability and retention (EPR) effect. However, significant variability has been observed in their bulk tumor accumulation and intra-tumoral distribution. The heterogeneous accumulation of liposomes in solid tumors is largely believed to result from the chaotic morphology and physiology of tumor blood vessels. Thus, tumor perfusion imaging may provide a novel method to predict the accumulation and resulting therapeutic effect of liposome formulations. In this study, dynamic contrast enhanced computed tomography (DCE-CT) was employed to quantitatively estimate the intra-tumoral distribution of perfusion and anatomical CT was used to map the spatio-temporal accumulation of a CT-liposome contrast agent. A statistically significant positive correlation was found between quantitative and semi-quantitative measures of tumor perfusion (i.e. K(trans), vp, and AUC(iox)) and liposome accumulation (AUC(lipo) and C(peak)) in two mouse xenograft models of human cervical cancer. Specifically, it was found that regions with higher K(trans),vp, and AUC(iox) had greater liposome accumulation. These findings demonstrate that DCE-CT measurements of tumor perfusion may be an important technique for selecting patients that are likely to respond to liposome and potentially other nanoparticle-based therapies.