• Humans
• Neoplasms/drug therapy
• Neoplasms/blood supply
• Neovascularization, Pathologic/drug therapy
• Neovascularization, Pathologic/diagnostic imaging
• Angiogenesis Inhibitors/therapeutic use

• R56 EB032211 NIBIB NIH HHS
• T32 EB007507 NIBIB NIH HHS
• R56 EB32211-01 NIBIB NIH HHS
• National Institute of Biomedical Imaging and Bioengineering
• NIH Ruth Kirschstein Training Grant

• assessment
• cerebrovascular diseases
• diagnosis
• imaging techniques
• neuroimaging

Lesions of breast imaging reporting and data system (BI-RADS) 4 at mammography vary from benign to malignant, leading to difficulties for clinicians to distinguish between them. The specificity of magnetic resonance imaging (MRI) in detecting breast is relatively low, leading to many false-positive results and high rates of re-examination or biopsy. Diffusion-weighted imaging (DWI), combined with perfusion-weighted imaging (PWI), might help to distinguish between benign and malignant BI-RADS 4 breast lesions at mammography.

To evaluate the value of DWI and PWI in diagnosing BI-RADS 4 breast lesions.

This is a retrospective study which included patients who underwent breast MRI between May 2017 and May 2019 in the hospital. The lesions were divided into benign and malignant groups according to the classification of histopathological results. The diagnostic efficacy of DWI and PWI were analyzed respectively and combinedly. The 95 lesions were divided according to histopathological diagnosis, with 46 benign and 49 malignant. The main statistical methods used included the Student t-test, the Mann-Whitney U-test, the chi-square test or Fisher’s exact test.

The mean apparent diffusion coefficient (ADC) values in the parenchyma and lesion area of the normal mammary gland were 1.82 ± 0.22 × 10^-3 mm²/s and 1.24 ± 0.16 × 10^-3 mm²/s, respectively (P = 0.021). The mean ADC value of the malignant group was 1.09 ± 0.23 × 10^-3 mm²/s, which was lower than that of the benign group (1.42 ± 0.68 × 10^-3 mm²/s) (P = 0.016). The volume transfer constant (Ktrans) and rate constant (Kep) values were higher in malignant lesions than in benign ones (all P < 0.001), but there were no significant statistical differences regarding volume fraction (V_e) (P = 0.866). The sensitivity and specificity of PWI combined with DWI (91.7% and 89.3%, respectively) were higher than that of PWI or DWI alone. The accuracy of PWI combined with DWI in predicting pathological results was significantly higher than that predicted by PWI or DWI alone.

DWI, combined with PWI, might possibly distinguish between benign and malignant BI-RADS 4 breast lesions at mammography.

• Magnetic resonance imaging
• Breast diseases
• Diffusion-weighted imaging
• Perfusion-weighted imaging

• Agreement
• Brain tumors
• Computed tomography perfusion
• Magnetic resonance perfusion-weighted Imaging

• CD105
• Marker
• Targeted therapy
• Tumor therapy

• Antigens, CD
• Endoglin
• Humans
• Neoplasms/diagnosis
• Neoplasms/therapy
• Neovascularization, Pathologic/pathology
• Prognosis
• Receptors, Cell Surface
• Transforming Growth Factor beta/metabolism

• Glioma
• Isocitrate dehydrogenase
• Magnetic resonance imaging
• Radiomics
• Vascular endothelial growth factor

To explore the correlations of radiomic features of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with microvessel density (MVD) in patients with hepatocellular carcinoma (HCC), based on single-input and dual-input two-compartment extended Tofts (SITET and DITET) models.

We compared the quantitative parameters of SITET and DITET models for DCE-MRI in 30 patients with HCC using paired sample t-tests. The correlations of SITET and DITET model parameters with CD31-MVD and CD34-MVD were analyzed using Pearson’s correlation analysis. A diagnostic model of CD34-MVD was established and the diagnostic abilities of models for MVD were analyzed using receiver operating characteristic curve (ROC) analysis.

There were significant differences between the quantitative parameters in the two kinds of models. Compared with SITET, DITET parameters showed better correlations with CD31-MVD and CD34-MVD. The K^trans and Ve radiomics features of the DITET model showed high efficiency for predicting the level of CD34-MVD according to ROC analysis, with areas under curves of 0.83 and 0.94, respectively.

Compared with SITET, the DITET model provides a better indication of the microcirculation of HCC and is thus more suitable for examining patients with HCC.

• Hepatocellular carcinoma
• dual-input two-compartment extended Tofts model
• hepatic artery
• magnetic resonance imaging
• microvessel density
• portal vein
• single-input two-compartment extended Tofts model

Targeted therapy against tumor angiogenesis is widely used in clinical practice for patients with colorectal liver metastases (CRLM). Possible predictive biomarkers for tumor angiogenesis, such as, microvessel density (MVD), hypoxia and cell proliferation, can be determined using immunohistochemical staining. However, patients ineligible for surgical treatment need to undergo invasive diagnostic interventions in order to determine these biomarkers. CT perfusion (CTP) is an emerging functional imaging technique, which can non-invasively determine vascular properties of solid tumors. The purpose of this study was to evaluate CTP with histological biomarkers in CRLM.

Patients with CRLM underwent CTP one day before liver surgery. CTP analysis was performed on the entire volume of the largest metastases in each patient. Dual-input maximum slope analysis was used and data concerning arterial flow (AF), portal flow (PF) and perfusion index (PI) were recorded. Immunohistochemical staining with CD34, M75/CA-IX and MIB-1 was performed on the rim in the midsection of the tumor to determine respectively MVD, hypoxia and cell proliferation.

Twenty CRLM in 20 patients were studied. Mean size of the largest CRLM was 37 mm (95% CI 21–54 mm). Mean AF and PF were respectively 64 ml/min/100ml (95% CI 48–79) and 30 ml/min/100ml (95% CI 22–38). Mean PI was 68% (95% CI 62–73). No significant correlation was found between tumor growth patterns and CTP (p = 0.95). MVD did not significantly correlate to AF (r = 0.05; p = 0.84), PF (r = 0.17; p = 0.47) and PI (r = -0.12; p = 0.63). Cell proliferation also did not significantly correlate to AF (r = 0.07; p = 0.78), PF (r = -0.01; p = 0.95) and PI (r = 0.15; p = 0.52). Hypoxia did not significantly correlate to AF (r = -0.05; p = 0.83), however, significantly to PF (r = 0.51; p = 0.02) and a trend to negative correlation with PF (r = -0.43; p = 0.06). However, after controlling the false discovery rate, no significant correlation between CTP and used immunohistochemical biomarkers was found.

In conclusion, this feasibility study found a trend to negative correlation between PI and hypoxia, CTP might therefore possibly evaluate this prognostic marker in CRLM non-invasively. However, CTP is not an appropriate technique for the assessment of microvessels or cell proliferation in CRLM.

• Aged
• Biomarkers, Tumor/metabolism
• Colorectal Neoplasms/pathology
• Female
• Humans
• Liver/diagnostic imaging
• Liver/metabolism
• Liver/pathology
• Liver Neoplasms/diagnostic imaging
• Liver Neoplasms/metabolism
• Liver Neoplasms/secondary
• Male
• Middle Aged
• Neovascularization, Pathologic/diagnostic imaging
• Neovascularization, Pathologic/pathology
• Perfusion Imaging/methods
• Perfusion Imaging/standards
• Tomography, X-Ray Computed/methods
• Tomography, X-Ray Computed/standards
• Tumor Hypoxia

• Breast cancer
• dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)
• estrogen receptor (ER)
• texture analysis

A higher degree of angiogenesis is associated with shortened survival in glioblastoma. Feasible morphometric parameters for analyzing vascular networks in brain tumors in clinical practice are lacking. We investigated whether the macrovascular network classified by the number of vessel-like structures (nVS) visible on three-dimensional T1-weighted contrast–enhanced (3D-T1CE) magnetic resonance imaging (MRI) could improve survival prediction models for newly diagnosed glioblastoma based on clinical and other imaging features. Ninety-seven consecutive patients (62 men; mean age, 58 ± 15 years) with histologically proven glioblastoma underwent 1.5T-MRI, including anatomical, diffusion-weighted, dynamic susceptibility contrast perfusion, and 3D-T1CE sequences after 0.1 mmol/kg gadobutrol. We assessed nVS related to the tumor on 1-mm isovoxel 3D-T1CE images, and relative cerebral blood volume, relative cerebral flow volume (rCBF), delay mean time, and apparent diffusion coefficient in volumes of interest for contrast-enhancing lesion (CEL), non-CEL, and contralateral normal-appearing white matter. We also assessed Visually Accessible Rembrandt Images scoring system features. We used ROC curves to determine the cutoff for nVS and univariate and multivariate cox proportional hazards regression for overall survival. Prognostic factors were evaluated by Kaplan-Meier survival and ROC analyses. Lesions with nVS > 5 were classified as having highly developed macrovascular network; 58 (60.4%) tumors had highly developed macrovascular network. Patients with highly developed macrovascular network were older, had higher volume_CEL, increased rCBF_CEL, and poor survival; nVS correlated negatively with survival (r = −0.286; p = 0.008). On multivariate analysis, standard treatment, age at diagnosis, and macrovascular network best predicted survival at 1 year (AUC 0.901, 83.3% sensitivity, 93.3% specificity, 96.2% PPV, 73.7% NPV). Contrast-enhanced MRI macrovascular network improves survival prediction in newly diagnosed glioblastoma.

• angiogenesis
• biomarker
• glioblastoma
• magnetic resonance imaging
• survival

• glioblastoma
• magnetic resonance imaging
• perfusion imaging
• treatment evaluation

• Brain/diagnostic imaging
• Brain Neoplasms/diagnostic imaging
• Contrast Media/pharmacology
• Disease Progression
• Edema/diagnostic imaging
• Glioblastoma/diagnostic imaging
• Humans
• Image Processing, Computer-Assisted/methods
• Magnetic Resonance Angiography/methods
• Magnetic Resonance Angiography/standards
• Neuroimaging/methods
• Reproducibility of Results

• University of Groningen with a Mandema
• Junior Scientific Masterclass

Glioblastoma multiforme (GBM) represents the most malignant primary brain tumor characterized by pathological vascularization. Mutations in isocitrate dehydrogenases 1 and 2 (IDH1 and IDH2) were observed in GBM. We aimed to assess the intra-tumor hypoxia, angiogenesis and microvessel formation in GBM and to find their associations with IDH1 mutation status and patients prognosis.

52 patients with a diagnosis of GBM were included into the study. IDH1 R132H mutation was assessed by RT-PCR from FFPE tumor samples obtained during surgery. The expression of markers of hypoxia (HIF2α), angiogenesis (VEGF), tumor microvascularity (CD31, CD34, vWF, CD105), and proliferation (Ki-67) were assessed immunohistochemically (IHC). IDH1 mutation and IHC markers were correlated with the patient survival.

20 from 52 GBM tumor samples comprised IDH1 R132H mutation (38.5%). The majority of mutated tumors were classified as secondary glioblastomas (89.9%). Patients with IDH1 mutated tumors experienced better progression-free survival (P = 0.037) as well as overall survival (P = 0.035) compared with wild type tumors. The significantly lower expression of VEGF was observed in GBM with IDH1 mutation than in wild type tumors (P = 0.01). No such association was found for microvascular markers. The increased expression of newly-formed microvessels (ratio CD105/CD31) in tumor samples was associated with worse patient’s progression-free survival (P = 0.026).

No increase in HIF/VEGF-mediated angiogenesis was observed in IDH1-mutated GBM compared with IDH1 wild type tumors. The histological assessment of the portion of newly-formed microvessels in tumor tissue can be used for the prediction of GBM patient’s prognosis.

• biomarkers
• glioblastoma multiforme
• isocitrate dehydrogenase
• microvascularity
• microvessel