Improved Pancreatic Cancer Detection and Localization on CT Scans: A Computer-Aided Detection Model Utilizing Secondary Features.

The early detection of pancreatic ductal adenocarcinoma (PDAC) is essential for optimal treatment of pancreatic cancer patients. We propose a tumor detection framework to improve the detection of pancreatic head tumors on CT scans. In this retrospective research study, CT images of 99 patients with pancreatic head cancer and 98 control cases from the Catharina Hospital Eindhoven were collected.

The Impact of Expectation Management and Model Transparency on Radiologists' Trust and Utilization of AI Recommendations for Lung Nodule Assessment on Computed Tomography: Simulated Use Study.

Background: Many promising artificial intelligence (AI) and computer-aided detection and diagnosis systems have been developed, but few have been successfully integrated into clinical practice. This is partially owing to a lack of user-centered design of AI-based computer-aided detection or diagnosis (AI-CAD) systems.

Objective: We aimed to assess the impact of different onboarding tutorials and levels of AI model explainability on radiologists' trust in AI and the use of AI recommendations in lung nodule assessment on computed tomography (CT) scans.

Computer-Aided Detection for Pancreatic Cancer Diagnosis: Radiological Challenges and Future Directions.

Radiological imaging plays a crucial role in the detection and treatment of pancreatic ductal adenocarcinoma (PDAC). However, there are several challenges associated with the use of these techniques in daily clinical practice. Determination of the presence or absence of cancer using radiological imaging is difficult and requires specific expertise, especially after neoadjuvant therapy.

The Effects of Artificial Intelligence Assistance on the Radiologists' Assessment of Lung Nodules on CT Scans: A Systematic Review.

To reduce the number of missed or misdiagnosed lung nodules on CT scans by radiologists, many Artificial Intelligence (AI) algorithms have been developed. Some algorithms are currently being implemented in clinical practice, but the question is whether radiologists and patients really benefit from the use of these novel tools. This study aimed to review how AI assistance for lung nodule assessment on CT scans affects the performances of radiologists.

Looking through the eyes of the multidisciplinary team: the design and clinical evaluation of a decision support system for lung cancer care.

Background: Decision-making in lung cancer is complex due to a rapidly increasing amount of diagnostic data and treatment options. The need for timely and accurate diagnosis and delivery of care demands high-quality multidisciplinary team (MDT) collaboration and coordination. Clinical decision support systems (CDSSs) can potentially support MDTs in constructing a shared mental model of a patient case.

Rapid stromal remodeling by short-term VEGFR2 inhibition increases chemotherapy delivery in esophagogastric adenocarcinoma.

Anti-angiogenic agents combined with chemotherapy is an important strategy for the treatment of solid tumors. However, survival benefit is limited, urging the improvement of combination therapies. We aimed to clarify the effects of vascular endothelial growth factor receptor 2 (VEGFR2) targeting on hemodynamic function and penetration of drugs in esophagogastric adenocarcinoma (EAC).

Improved Evaluation of Antivascular Cancer Therapy Using Constrained Tracer-Kinetic Modeling for Multiagent Dynamic Contrast-Enhanced MRI.

Dynamic contrast-enhanced MRI (DCE-MRI) is a promising technique for assessing the response of tumor vasculature to antivascular therapies. Multiagent DCE-MRI employs a combination of low and high molecular weight contrast agents, which potentially improves the accuracy of estimation of tumor hemodynamic and vascular permeability parameters. In this study, we used multiagent DCE-MRI to assess changes in tumor hemodynamics and vascular permeability after vascular-disrupting therapy.

Detection of Treatment Success after Photodynamic Therapy Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Early evaluation of response to therapy is crucial for selecting the optimal therapeutic follow-up strategy for cancer patients. PDT is a photochemistry-based treatment modality that induces tumor tissue damage by cytotoxic oxygen radicals, generated by a pre-injected photosensitive drug upon light irradiation of tumor tissue. Vascular shutdown is an important mechanism of tumor destruction for most PDT protocols.

Quantitative Multi-Parametric Magnetic Resonance Imaging of Tumor Response to Photodynamic Therapy.

Objective: The aim of this study was to characterize response to photodynamic therapy (PDT) in a mouse cancer model using a multi-parametric quantitative MRI protocol and to identify MR parameters as potential biomarkers for early assessment of treatment outcome.

Methods: CT26.WT colon carcinoma tumors were grown subcutaneously in the hind limb of BALB/c mice.

Cluster analysis of DCE-MRI data identifies regional tracer-kinetic changes after tumor treatment with high intensity focused ultrasound.

Evaluation of high intensity focused ultrasound (HIFU) treatment with MRI is generally based on assessment of the non-perfused volume from contrast-enhanced T1-weighted images. However, the vascular status of tissue surrounding the non-perfused volume has not been extensively investigated with MRI. In this study, cluster analysis of the transfer constant K(trans) and extravascular extracellular volume fraction ve , derived from dynamic contrast-enhanced MRI (DCE-MRI) data, was performed in tumor tissue surrounding the non-perfused volume to identify tumor subregions with distinct contrast agent uptake kinetics.

Multiparametric MRI analysis for the evaluation of MR-guided high intensity focused ultrasound tumor treatment.

For the clinical application of high intensity focused ultrasound (HIFU) for thermal ablation of malignant tumors, accurate treatment evaluation is of key importance. In this study, we have employed a multiparametric MRI protocol, consisting of quantitative T1, T2, ADC, amide proton transfer (APT), T1ρ and DCE-MRI measurements, to evaluate MR-guided HIFU treatment of subcutaneous tumors in rats. K-means clustering using all different combinations of the endogenous contrast MRI parameters (feature vectors) was performed to segment the multiparametric data into tissue populations with similar MR parameter values.

MRI methods for the evaluation of high intensity focused ultrasound tumor treatment: Current status and future needs.

Thermal ablation with high intensity focused ultrasound (HIFU) is an emerging noninvasive technique for the treatment of solid tumors. HIFU treatment of malignant tumors requires accurate treatment planning, monitoring and evaluation, which can be facilitated by performing the procedure in an MR-guided HIFU system. The MR-based evaluation of HIFU treatment is most often restricted to contrast-enhanced T1 -weighted imaging, while it has been shown that the non-perfused volume may not reflect the extent of nonviable tumor tissue after HIFU treatment.

A novel approach to tracer-kinetic modeling for (macromolecular) dynamic contrast-enhanced MRI.

Purpose: To develop a novel tracer-kinetic modeling approach for multi-agent dynamic contrast-enhanced MRI (DCE-MRI) that facilitates separate estimation of parameters characterizing blood flow and microvascular permeability within one individual.

Methods: Monte Carlo simulations were performed to investigate the performance of the constrained multi-agent model. Subsequently, multi-agent DCE-MRI was performed on tumor-bearing mice (n = 5) on a 7T Bruker scanner on three measurement days, in which two dendrimer-based contrast agents having high and intermediate molecular weight, respectively, along with gadoterate meglumine, were sequentially injected within one imaging session.

Automatic segmentation of subcutaneous mouse tumors by multiparametric MR analysis based on endogenous contrast.

Object: Contrast-enhanced T1-weighted imaging is usually included in MRI procedures for automatic tumor segmentation. Use of an MR contrast agent may not be appropriate for some applications, however. We assessed the feasability of automatic tumor segmentation by multiparametric cluster analysis that uses intrinsic MRI contrast only.

Multiparametric MRI analysis for the identification of high intensity focused ultrasound-treated tumor tissue.

Purpose: In this study endogenous magnetic resonance imaging (MRI) biomarkers for accurate segmentation of High Intensity Focused Ultrasound (HIFU)-treated tumor tissue and residual or recurring non-treated tumor tissue were identified.

Methods: Multiparametric MRI, consisting of quantitative T1, T2, Apparent Diffusion Coefficient (ADC) and Magnetization Transfer Ratio (MTR) mapping, was performed in tumor-bearing mice before (n = 14), 1 h after (n = 14) and 72 h (n = 7) after HIFU treatment. A non-treated control group was included (n = 7).

Amide proton transfer imaging of high intensity focused ultrasound-treated tumor tissue.

Purpose: In this study, the suitability of amide proton transfer (APT) imaging as a biomarker for the characterization of high intensity focused ultrasound (HIFU)-treated tumor tissue was assessed.

Methods: APT imaging was performed on tumor-bearing mice before (n = 15), directly after (n = 15) and at 3 days (n = 8) after HIFU treatment. A control group (n = 7) of nontreated animals was scanned at the same time points.

Targeting of ICAM-1 on vascular endothelium under static and shear stress conditions using a liposomal Gd-based MRI contrast agent.

Background: The upregulation of intercellular adhesion molecule-1 (ICAM-1) on the endothelium of blood vessels in response to pro-inflammatory stimuli is of major importance for the regulation of local inflammation in cardiovascular diseases such as atherosclerosis, myocardial infarction and stroke. In vivo molecular imaging of ICAM-1 will improve diagnosis and follow-up of patients by non-invasive monitoring of the progression of inflammation.

Results: A paramagnetic liposomal contrast agent functionalized with anti-ICAM-1 antibodies for multimodal magnetic resonance imaging (MRI) and fluorescence imaging of endothelial ICAM-1 expression is presented.

Dual-targeting of αvβ3 and galectin-1 improves the specificity of paramagnetic/fluorescent liposomes to tumor endothelium in vivo.

Molecular imaging of angiogenesis requires a highly specific and efficient contrast agent for targeting activated endothelium. We have previously demonstrated that paramagnetic and fluorescent liposomes functionalized with two angiogenesis-specific ligands, the galectin-1-specific anginex (Anx) and the α(v)β(3) integrin-specific RGD, produce synergistic targeting effect in vitro. In the current study, we applied Anx and RGD dual-conjugated liposomes (Anx/RGD-L) for angiogenesis-specific MRI in vivo, focusing on the specificity and efficacy of liposome association with tumor endothelium.

Noninvasive visualization of in vivo release and intratumoral distribution of surrogate MR contrast agent using the dual MR contrast technique.

A direct evaluation of the in vivo release profile of drugs from carriers is a clinical demand in drug delivery systems, because drug release characterized in vitro correlates poorly with in vivo release. The purpose of this study is to demonstrate the in vivo applicability of the dual MR contrast technique as a useful tool for noninvasive monitoring of the stability and the release profile of drug carriers, by visualizing in vivo release of the encapsulated surrogate MR contrast agent from carriers and its subsequent intratumoral distribution profile. The important aspect of this technique is that it incorporates both positive and negative contrast agents within a single carrier.