Clinical Utility of Tumor-Naïve Pre-surgical ctDNA Detection in Early-stage NSCLC.

PURPOSE: The use of tumor-informed circulating tumor DNA (ctDNA) testing in early-stage patients before surgery is limited mainly due to restricted tissue access and extended turnaround times. This study aimed to evaluate the clinical value of a tumor-naïve, methylation-based cell-free DNA assay in a large cohort of patients with resected non-small cell lung cancer (NSCLC). METHOD: We analyzed pre-surgical plasma samples from 895 patients with EGFR and ALK-wild-type, clinical stage I or II NSCLC. The ctDNA status was evaluated for its prognostic significance in relation to tumor volume, metabolic activity, histology, histological subtypes, and clinical-to-pathological TNM upstaging. RESULTS: Pre-surgical ctDNA detection was observed in 55 out of 414 (13%) patients with clinical stage I lung adenocarcinoma (LUAD) and was associated with poor recurrence-free survival (RFS) (2-year RFS 69% versus 91%; log-rank P<0.001), approaching that of clinical stage II LUAD. Pre-surgical ctDNA detection was not prognostic in patients with clinical stage II LUAD or non-LUAD. Within LUAD, tumor volume and positron emission tomography avidity interacted to predict pre-surgical ctDNA detection. Moreover, pre-surgical ctDNA detection was predictive of the post-surgical discovery of IASLC G3 tumors (P<0.001) and pathological TNM upstaging (P<0.001). Notably, pre-surgical ctDNA detection strongly correlated with higher PD-L1 expression in tumors (positive rates 28% vs. 55%, P<0.001), identifying a subgroup likely to benefit from anti-PD-(L)-1 therapies. CONCLUSION: These findings support the integration of ctDNA testing into routine diagnostic workflows in early-stage NSCLC without the need of tumor tissue profiling. Furthermore, it is clinically useful in identifying high-risk patients who might benefit from innovative treatments, including neoadjuvant immune checkpoint inhibitors.

MRI blood-brain barrier permeability measurements to predict hemorrhagic transformation in a rat model of ischemic stroke.

Permeability imaging might add valuable information in the risk assessment of hemorrhagic transformation. This study evaluates the predictive value of blood-brain barrier permeability (BBBP) measurements extracted from dynamic contrast-enhanced MRI for hemorrhagic transformation in ischemic stroke. Spontaneously hypertensive and Wistar rats with 2 h filament occlusion of the right MCA underwent MRI during occlusion, at 4 and 24 h post reperfusion. BBBP was imaged by DCE imaging and quantified by Patlak analysis. Cresyl-violet staining was used to characterize hemorrhage in sacrificed rats at 24 h, immediately following the last imaging study. BBBP changes were evaluated at baseline, 4 and 24 h after reperfusion. Receiver-operating characteristic (ROC) analysis was performed to determine the most accurate BBBP threshold to predict hemorrhagic transformation. In animals showing macroscopic hemorrhage at 24 h, 95th BBBP percentile values ipsilateral were 0.323 [0.260, 0.387], 0.685 [0.385, 0.985], and 0.412 [0.210, 0.613] ml/min·100 g (marginal mean [95%CI]) during occlusion, at 4 and 24 h post reperfusion, respectively. The BBBP values on the infarcted and contralateral side were significantly different at 4 (p = 0.034) and 24 h post reperfusion (p = 0.031). The predictive value of BBBP in terms of macroscopic hemorrhage was highest 4 h after reperfusion (ROC area under the curve = 84 %) with a high negative predictive value (98.3 %) and limited positive predictive value (14.9 %) for a threshold of 0.35 ml/min·100g. Altered BBBP is a necessary but not sufficient condition to cause hemorrhagic transformation in rats with an infarct. Further research is needed to identify those additional risk factors that are required for hemorrhagic transformation to develop in the setting of ischemic stroke.

Validation of in vivo magnetic resonance imaging blood-brain barrier permeability measurements by comparison with gold standard histology.

BACKGROUND AND PURPOSE: We sought to validate the blood-brain barrier permeability measurements extracted from perfusion-weighted MRI through a relatively simple and frequently applied model, the Patlak model, by comparison with gold standard histology in a rat model of ischemic stroke. METHODS: Eleven spontaneously hypertensive rats and 11 Wistar rats with unilateral 2-hour filament occlusion of the right middle cerebral artery underwent imaging during occlusion at 4 hours and 24 hours after reperfusion. Blood-brain barrier permeability was imaged by gradient echo imaging after the first pass of the contrast agent bolus and quantified by a Patlak analysis. Blood-brain barrier permeability was shown on histology by the extravasation of Evans blue on fluorescence microscopy sections matching location and orientation of MR images. Cresyl-violet staining was used to detect and characterize hemorrhage. Landmark-based elastic image registration allowed a region-by-region comparison of permeability imaging at 24 hours with Evans blue extravasation and hemorrhage as detected on histological slides obtained immediately after the 24-hour image set. RESULTS: Permeability values in the nonischemic tissue (marginal mean ± SE: 0.15 ± 0.019 mL/min 100 g) were significantly lower compared to all permeability values in regions of Evans blue extravasation or hemorrhage. Permeability values in regions of weak Evans blue extravasation (0.23 ± 0.016 mL/min 100 g) were significantly lower compared to permeability values of in regions of strong Evans blue extravasation (0.29 ± 0.020 mL/min 100 g) and macroscopic hemorrhage (0.35 ± 0.049 mL/min 100 g). Permeability values in regions of microscopic hemorrhage (0.26 ± 0.024 mL/min 100 g) only differed significantly from values in regions of nonischemic tissue (0.15 ± 0.019 mL/min 100 g). CONCLUSIONS: Areas of increased permeability measured in vivo by imaging coincide with blood-brain barrier disruption and hemorrhage observed on gold standard histology.

High and Low Molecular Weight Fluorescein Isothiocyanate (FITC)-Dextrans to Assess Blood-Brain Barrier Disruption: Technical Considerations.

This note is to report how histological preparation techniques influence the extravasation pattern of the different molecular sizes of fluorescein isothiocyanate (FITC)-dextrans, typically used as markers for blood-brain barrier leakage. By using appropriate preparation methods, false negative results can be minimized. Wistar rats underwent a 2-h middle cerebral artery occlusion and magnetic resonance imaging. After the last imaging scan, Evans blue and FITC-dextrans of 4, 40, and 70 kDa molecular weight were injected. Different histological preparation methods were used. Sites of blood-brain barrier leakage were analyzed by fluorescence microscopy. Extravasation of Evans blue and high molecular FITC-dextrans (40 and 70 kDa) in the infarcted region could be detected with all preparation methods used. If exposed directly to saline, the signal intensity of these FITC-dextrans decreased. Extravasation of the 4-kDa low molecular weight FITC-dextran could only be detected using freshly frozen tissue sections. Preparations involving paraformaldehyde and sucrose resulted in the 4-kDa FITC-dextran dissolving in these reactants and being washed out, giving the false negative result of no extravasation. FITC-dextrans represent a valuable tool to characterize altered blood-brain barrier permeability in animal models. Diffusion and washout of low molecular weight FITC-dextran can be avoided by direct immobilization through immediate freezing of the tissue. This pitfall needs to be known to avoid the false impression that there was no extravasation of low molecular weight FITC-dextrans.

Simulation model for contrast agent dynamics in brain perfusion scans.

Standardization efforts are currently under way to reduce the heterogeneity of quantitative brain perfusion methods. A brain perfusion simulation model is proposed to generate test data for an unbiased comparison of these methods. This model provides realistic simulated patient data and is independent of and different from any computational method. The flow of contrast agent solute and blood through cerebral vasculature with disease-specific configurations is simulated. Blood and contrast agent dynamics are modeled as a combination of convection and diffusion in tubular networks. A combination of a cerebral arterial model and a microvascular model provides arterial-input and time-concentration curves for a wide range of flow and perfusion statuses. The model is configured to represent an embolic stroke in one middle cerebral artery territory and provides physiologically plausible vascular dispersion operators for major arteries and tissue contrast agent retention functions. These curves are fit to simpler template curves to allow the use of the simulation results in multiple validation studies. A gamma-variate function with fit parameters is proposed as the vascular dispersion operator, and a combination of a boxcar and exponential decay function is proposed as the retention function. Such physiologically plausible operators should be used to create test data that better assess the strengths and the weaknesses of various analysis methods.

Strategies to configure image analysis algorithms for clinical usage.

Medical imaging informatics must exceed the mere development of algorithms. The discipline is also responsible for the establishment of methods in clinical practice to assist physicians and improve health care. From our point of view, it is commonly accepted that model-based analysis of medical images is superior to other concepts, but only a few applications are found in daily clinical use. The gap between development of model-based image analysis and its routine application can be addressed by identifying four necessary transfer steps: formulation, parameterization, instantiation, and validation. Usually, computer scientists formulate the model and define its parameterization, i.e., configure a model to handle a selected subset of clinical data. During instantiation, the algorithm adapts the model to the actual data, which is validated by physicians. Since medical a priori knowledge and particular knowledge on technical details are required for parameterization and validation, these steps are considered to be bottlenecks. In this paper, we propose general schemes that allow an application- or image-specific parameterization to be performed by medical users. Combining noncontextual and contextual approaches, we also suggest a reliable scheme that allows application-specific validation, even if a gold standard is unavailable. To emphasize our point of view, we provide examples based on unsupervised segmentation in medical imagery, which is one of the most difficult tasks. Following the proposed schemes, an exact delineation of cells in micrographs is parameterized, validated, and successfully established in daily clinical use, while automatic determination of body regions in radiographs cannot be configured to support reliable and robust clinical use. The results stress that parameterization and validation must be based on clinical data that show all potential variations and artifact sources.