Artificial Intelligence-Aided Selection of Needle Pathways: Proof-of-Concept in Percutaneous Lung Biopsies.

PURPOSE: To evaluate the concordance between lung biopsy puncture pathways determined by artificial intelligence (AI) and those determined by expert physicians. MATERIALS AND METHODS: An AI algorithm was created to choose optimal lung biopsy pathways based on segmented thoracic anatomy and emphysema in volumetric lung computed tomography (CT) scans combined with rules derived from the medical literature. The algorithm was validated using pathways generated from CT scans of randomly selected patients (n = 48) who had received percutaneous lung biopsies and had noncontrast CT scans of 1.25-mm thickness available in picture archiving and communication system (PACS) (n = 28, mean age, 68.4 years ± 9.2; 12 women, 16 men). The algorithm generated 5 potential pathways per scan, including the computer-selected best pathway and 4 random pathways (n = 140). Four experienced physicians rated each pathway on a 1-5 scale, where scores of 1-3 were considered safe and 4-5 were considered unsafe. Concordance between computer and physician ratings was assessed using Cohen's κ. RESULTS: The algorithm ratings were statistically equivalent to the physician ratings (safe vs unsafe: κ¯=0.73; ordinal scale: κ¯=0.62). The computer and physician ratings were identical in 57.9% (81/140) of cases and differed by a median of 0 points. All least-cost "best" pathways generated by the algorithm were considered safe by both computer and physicians (28/28) and were judged by physicians to be ideal or near ideal. CONCLUSIONS: AI-generated lung biopsy puncture paths were concordant with expert physician reviewers and considered safe. A prospective comparison between computer- and physician-selected puncture paths appears indicated in addition to expansion to other anatomic locations and procedures.

Detectability of Small Low-Attenuation Lesions With Deep Learning CT Image Reconstruction: A 24-Reader Phantom Study.

BACKGROUND. Iterative reconstruction (IR) techniques are susceptible to contrast-dependent spatial resolution, limiting overall radiation dose reduction potential. Deep learning image reconstruction (DLIR) may mitigate this limitation. OBJECTIVE. The purpose of our study was to evaluate low-contrast detectability performance and radiation-saving potential of a DLIR algorithm in comparison with filtered back projection (FBP) and IR using a human multireader noninferiority study design and task-based observer modeling. METHODS. A dual-phantom construct, consisting of a low-contrast detectability module (21 low-contrast hypoattenuating objects in seven sizes [2.4-10.0 mm] and three contrast levels [-15, -10, -5 HU] embedded within liver-equivalent background) and a phantom, was imaged at five radiation exposures (CTDIvol range, 1.4-14.0 mGy; size-specific dose estimate, 2.5-25.0 mGy; 90%-, 70%-, 50%-, and 30%-reduced radiation levels and full radiation level) using an MDCT scanner. Images were reconstructed using FBP, hybrid IR (ASiR-V), and DLIR (TrueFidelity). Twenty-four readers of varying experience levels evaluated images using a two-alternative forced choice. A task-based observer model (detectability index [d']) was calculated. Reader performance was estimated by calculating the AUC using a noninferiority method. RESULTS. Compared with FBP and IR methods at routine radiation levels, DLIR medium and DLIR high settings showed noninferior performance through a 90% radiation reduction (except DLIR medium setting at 70% reduced level). The IR method was non-inferior to routine radiation FBP only for 30% and 50% radiation reductions. No significant difference in d' was observed between routine radiation FBP and DLIR high setting through a 70% radiation reduction. Reader experience was not correlated with diagnostic accuracy (R2 = 0.005). CONCLUSION. Compared with FBP or IR methods at routine radiation levels, certain DLIR algorithm weightings yielded noninferior low-contrast detectability with radiation reductions of up to 90% as measured by 24 human readers and up to 70% as assessed by a task-based observer model. CLINICAL IMPACT. DLIR has substantial potential to preserve contrast-dependent spatial resolution for the detection of hypoattenuating lesions at decreased radiation levels in a phantom model, addressing a major shortcoming of current IR techniques.

CT Number Accuracy and Association With Object Size: A Phantom Study Comparing Energy-Integrating Detector CT and Deep Silicon Photon-Counting Detector CT.

BACKGROUND. Variable beam hardening based on patient size causes variation in CT numbers for energy-integrating detector (EID) CT. Photon-counting detector (PCD) CT more accurately determines effective beam energy, potentially improving CT number reliability. OBJECTIVE. The purpose of the present study was to compare EID CT and deep silicon PCD CT in terms of both the effect of changes in object size on CT number and the overall accuracy of CT numbers. METHODS. A phantom with polyethylene rings of varying sizes (mimicking patient sizes) as well as inserts of different materials was scanned on an EID CT scanner in single-energy (SE) mode (120-kV images) and in rapid-kilovoltage-switching dual-energy (DE) mode (70-keV images) and on a prototype deep silicon PCD CT scanner (70-keV images). ROIs were placed to measure the CT numbers of the materials. Slopes of CT number as a function of object size were computed. Materials' ideal CT number at 70 keV was computed using the National Institute of Standards and Technology XCOM Photon Cross Sections Database. The root mean square error (RMSE) between measured and ideal numbers was calculated across object sizes. RESULTS. Slope (expressed as Hounsfield units per centimeter) was significantly closer to zero (i.e., less variation in CT number as a function of size) for PCD CT than for SE EID CT for air (1.2 vs 2.4 HU/cm), water (-0.3 vs -1.0 HU/cm), iodine (-1.1 vs -4.5 HU/cm), and bone (-2.5 vs -10.1 HU/cm) and for PCD CT than for DE EID CT for air (1.2 vs 2.8 HU/cm), water (-0.3 vs -1.0 HU/cm), polystyrene (-0.2 vs -0.9 HU/cm), iodine (-1.1 vs -1.9 HU/cm), and bone (-2.5 vs -6.2 HU/cm) (p < .05). For all tested materials, PCD CT had the smallest RMSE, indicating CT numbers closest to ideal numbers; specifically, RMSE (expressed as Hounsfield units) for SE EID CT, DE EID CT, and PCD CT was 32, 44, and 17 HU for air; 7, 8, and 3 HU for water; 9, 10, and 4 HU for polystyrene; 31, 37, and 13 HU for iodine; and 69, 81, and 20 HU for bone, respectively. CONCLUSION. For numerous materials, deep silicon PCD CT, in comparison with SE EID CT and DE EID CT, showed lower CT number variability as a function of size and CT numbers closer to ideal numbers. CLINICAL IMPACT. Greater reliability of CT numbers for PCD CT is important given the dependence of diagnostic pathways on CT numbers.

A Characterization of Deep Learning Reconstruction Applied to Dual-Energy Computed Tomography Monochromatic and Material Basis Images.

OBJECTIVE: Advancements in computed tomography (CT) reconstruction have enabled image quality improvements and dose reductions. Previous advancements have included iterative and model-based reconstruction. The latest image reconstruction advancement uses deep learning, which has been evaluated for polychromatic imaging only. This article characterizes a commercially available deep learning imaging reconstruction applied to dual-energy CT. METHODS: Monochromatic, iodine basis, and water basis images were reconstructed with filtered back projection (FBP), iterative (ASiR-V), and deep learning (DLIR) methods in a phantom experiment. Slice thickness, contrast-to-noise ratio, modulation transfer function, and noise power spectrum metrics were used to characterize ASiR-V and DLIR relative to FBP over a range of dose levels, phantom sizes, and iodine concentrations. RESULTS: Slice thicknesses for ASiR-V and DLIR demonstrated no statistically significant difference relative to FBP for all measurement conditions. Contrast-to-noise ratio performance for DLIR-high and ASiR-V 40% at 2 mg I/mL on 40-keV images were 162% and 30% higher than FBP, respectively. Task-based modulation transfer function measurements demonstrated no clinically significant change between FBP and ASiR-V and DLIR on monochromatic or iodine basis images. CONCLUSIONS: Deep learning image reconstruction enabled better image quality at lower monochromatic energies and on iodine basis images where image contrast is maximized relative to polychromatic or high-energy monochromatic images. Deep learning image reconstruction did not demonstrate thicker slices, decreased spatial resolution, or poor noise texture (ie, "plastic") relative to FBP.

A Method for Reducing Variability Across Dual-Energy CT Manufacturers in Quantification of Low Iodine Content Levels.

BACKGROUND. Clinical use of the dual-energy CT (DECT) iodine quantification technique is hindered by between-platform (i.e., across different manufacturers) variability in iodine concentration (IC) values, particularly at low iodine levels. OBJECTIVE. The purpose of this study was to develop in an anthropomorphic phantom a method for reducing between-platform variability in quantification of low iodine content levels using DECT and to evaluate the method's performance in patients undergoing serial clinical DECT examinations on different platforms. METHODS. An anthropomorphic phantom in three body sizes, incorporating varied lesion types and scanning conditions, was imaged with three distinct DECT implementations from different manufacturers at varying radiation exposures. A cross-platform iodine quantification model for correcting between-platform variability at low iodine content was developed using the phantom data. The model was tested in a retrospective series of 30 patients (20 men, 10 women; median age, 62 years) who each underwent three serial contrast-enhanced DECT examinations of the abdomen and pelvis (90 scans total) for routine oncology surveillance using the same three DECT platforms as in the phantom. Estimated accuracy of phantom IC values was summarized using root-mean-square error (RMSE) relative to known IC. Between-platform variability in patients was summarized using root-mean-square deviation (RMSD). RMSE and RMSD were compared between platform-based IC (ICPB) and cross-platform IC (ICCP). ICPB was normalized to aorta and portal vein. RESULTS. In the phantom study, mean RMSE of ICPB across platforms and other experimental conditions was 0.65 ± 0.18 mg I/mL compared with 0.40 ± 0.08 mg I/mL for ICCP (38% decrease in mean RMSE; p < .05). Intrapatient between-platform variability across serial DECT examinations was higher for ICPB than ICCP (RMSD, 97% vs 88%; p < .001). Between-platform variability was not reduced by normalization of ICPB to aorta (RMSD, 97% vs 101%; p = .12) or portal vein (RMSD, 97% vs 97%; p = .81). CONCLUSION. The developed cross-platform method significantly decreased between-platform variability occurring at low iodine content with platform-based DECT iodine quantification. CLINICAL IMPACT. With further validation, the cross-platform method, which has been implemented as a web-based app, may expand clinical use of DECT iodine quantification, yielding meaningful IC values that reflect tissue biologic viability or treatment response in patients who undergo serial examinations on different platforms.

Virtual Unenhanced Dual-Energy CT Images Obtained with a Multimaterial Decomposition Algorithm: Diagnostic Value for Renal Mass and Urinary Stone Evaluation.

Background Virtual unenhanced (VUE) images obtained by using a dual-energy CT (DECT) multimaterial decomposition algorithm hold promise for diagnostic use in the abdomen in lieu of true unenhanced (TUE) images. Purpose To assess VUE images obtained from a DECT multimaterial decomposition algorithm in patients undergoing renal mass and urinary stone evaluation. Materials and Methods In this retrospective Health Insurance Portability and Accountability Act-compliant study, DECT was performed in patients undergoing evaluation for renal mass or urinary stone. VUE images were compared quantitatively to TUE images and qualitatively assessed by four independent radiologists. Differences in attenuation between VUE and TUE images were summarized by using 95% limits of agreement. Diagnostic performance in urinary stone detection was summarized by using area under the receiver operating characteristic curve, sensitivity, and specificity. Results A total of 221 patients (mean age ± standard deviation, 61 years ± 14; 129 men) with 273 renal masses were evaluated. Differences in renal mass attenuation between VUE and TUE images were within 3 HU for both enhancing masses (95% limits of agreement, -3.1 HU to 2.7 HU) and nonenhancing cysts (95% limits of agreement, -2.9 HU to 2.5 HU). Renal mass classification as enhancing mass versus nonenhancing cyst did not change (reclassification rate of enhancing masses, 0% [0 of 78]; 95% CI: 0, 5; reclassification rate of nonenhancing cysts, 0% [0 of 193]; 95% CI: 0, 2) with use of VUE in lieu of TUE images. Among 166 urinary stones evaluated, diagnostic performance of VUE images for stone detection was lower compared with that of TUE images (area under the receiver operating characteristic curve, 0.79 [95% CI: 0.73, 0.84] vs 0.93 [95% CI: 0.91, 0.95]; P < .001) due to reduced sensitivity of VUE for detection of stones 3 mm in diameter or less compared with those greater than 3 mm (sensitivity, 23% [25 of 108; 95% CI: 12, 40] vs 88% [126 of 144; 95% CI: 77, 94]; P < .001). Conclusion Compared with true unenhanced images, virtual unenhanced (VUE) images were unlikely to change renal mass classification as enhancing mass versus nonenhancing cyst. Diagnostic performance of VUE images remained suboptimal for urinary stone detection due to subtraction of stones 3 mm or less in diameter. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Sosna in this issue.

Use of Dual-Energy CT for Quantification of Essential Trace Metals (Iron, Copper, and Zinc): Proof of Concept.

OBJECTIVE. Altered concentrations of essential trace metals have been associated with the development of abdominal tumors. We developed a method to quantify trace metals (iron, copper, and zinc) using monochromatic data from commercially available dual-energy CT (DECT) implementations. CONCLUSION. Our data provide a foundation for the use of DECT for noninvasive quantification of essential trace metals. Minimum detectable concentrations of iron and zinc estimated with DECT overlap with in vivo hepatic concentrations reported in the literature.

CT Detectability of Small Low-Contrast Hypoattenuating Focal Lesions: Iterative Reconstructions versus Filtered Back Projection.

Purpose To investigate performance in detectability of small (≤1 cm) low-contrast hypoattenuating focal lesions by using filtered back projection (FBP) and iterative reconstruction (IR) algorithms from two major CT vendors across a range of 11 radiation exposures. Materials and Methods A low-contrast detectability phantom consisting of 21 low-contrast hypoattenuating focal objects (seven sizes between 2.4 and 10.0 mm, three contrast levels) embedded into a liver-equivalent background was scanned at 11 radiation exposures (volume CT dose index range, 0.5-18.0 mGy; size-specific dose estimate [SSDE] range, 0.8-30.6 mGy) with four high-end CT platforms. Data sets were reconstructed by using FBP and varied strengths of image-based, model-based, and hybrid IRs. Sixteen observers evaluated all data sets for lesion detectability by using a two-alternative-forced-choice (2AFC) paradigm. Diagnostic performances were evaluated by calculating area under the receiver operating characteristic curve (AUC) and by performing noninferiority analyses. Results At benchmark exposure, FBP yielded a mean AUC of 0.79 ± 0.09 (standard deviation) across all platforms which, on average, was approximately 2% lower than that observed with the different IR algorithms, which showed an average AUC of 0.81 ± 0.09 (P = .12). Radiation decreases of 30%, 50%, and 80% resulted in similar declines of observer detectability with FBP (mean AUC decrease, -0.02 ± 0.05, -0.03 ± 0.05, and -0.05 ± 0.05, respectively) and all IR methods investigated (mean AUC decrease, -0.00 ± 0.05, -0.04 ± 0.05, and -0.04 ± 0.05, respectively). For each radiation level and CT platform, variance in performance across observers was greater than that across reconstruction algorithms (P = .03). Conclusion Iterative reconstruction algorithms have limited radiation optimization potential in detectability of small low-contrast hypoattenuating focal lesions. This task may be further complicated by a high degree of variation in radiologists' performances, seemingly exceeding real performance differences among reconstruction algorithms. © RSNA, 2018 Online supplemental material is available for this article.

Approaches, advantages, and challenges to photon counting detector and multi-energy CT.

Photon counting detector CT (PCD-CT) is the newest major development in CT technology and has been commercially available since 2021. It offers major technological advantages over current standard-of-care energy integrating detector CT (EID-CT) including improved spatial resolution, improved iodine contrast to noise ratio, multi-energy imaging, and reduced noise. This article serves as a foundational basis to the technical approaches and concepts of PCD-CT technology with primary emphasis on detector technology in direct comparison to EID-CT. The article also addresses current technological challenges to PCD-CT with particular attention to cross talk and its causes (e.g., Compton scattering, fluorescence, charge sharing, K-escape) as well as pile-up.

Standardizing technical parameters and terms for abdominopelvic photon-counting CT: laying the groundwork for innovation and evidence sharing.

Photon-counting detector CT (PCD-CT) is a new technology that has multiple diagnostic benefits including increased spatial resolution, iodine signal, and radiation dose efficiency, as well as multi-energy imaging capability, but which also has unique challenges in abdominal imaging. The purpose of this work is to summarize key features, technical parameters, and terms, which are common amongst current abdominopelvic PCD-CT systems and to propose standardized terminology (where none exists). In addition, user-selectable protocol parameters are highlighted to facilitate both scientific evaluation and early clinical adoption. Unique features of PCD-CT systems include photon-counting detectors themselves, energy thresholds and bins, and tube potential considerations for preserved spectral separation. Key parameters for describing different PCD-CT systems are reviewed and explained. While PCD-CT can generate multi-energy images like dual-energy CT, there are new types of images such as threshold images, energy bin images, and special spectral images. The standardized terms and concepts herein build upon prior interdisciplinary consensus and have been endorsed by the newly created Society of Abdominal Radiology Photon-counting CT Emerging Technology Commission.

Diagnostic performance of the "drooping" sign in CT diagnosis of exophytic renal angiomyolipoma.

OBJECTIVE: To evaluate the prevalence of angular interface and the "drooping" sign in exophytic renal angiomyolipomas (AMLs) and the diagnostic performance in differentiating exophytic lipid-poor AMLs from other solid renal masses. METHODS: This IRB-approved, two-center study included 185 patients with 188 exophytic solid renal masses < 4 cm with histopathology and pre-operative CT within 30 days of surgical resection or biopsy. Images were reviewed for the presence of angular interface and the "drooping" sign qualitatively by three readers blinded to the final diagnosis, with majority rules applied. Both features were assessed quantitatively by cohort creators (who are not readers) independently. Free-marginal kappa was used to assess inter-reader agreement and agreement between two methods assessing each feature. Fisher's exact test, Mann-Whitney test, and multivariable logistic regression with two-tailed p < 0.05 were used to determine statistical significance. Diagnostic performance was assessed. RESULTS: Ninety-four patients had 96 AMLs, and 91 patients had 92 non-AMLs. Seventy-four (77%) of AMLs were lipid-poor based on quantitative assessment on CT. The presence of angular interface and the "drooping" sign by both qualitative and quantitative assessment were statistically significantly associated with AMLs (39% (qualitative) and 45% (quantitative) vs 15% (qualitative) and 13% (quantitative), and 48% (qualitative) and 43% (quantitative) vs 4% (qualitative) and 1% (quantitative), respectively, all p < 0.001) in univariable analysis. In multivariable analysis, only the "drooping" sign in either qualitative or quantitative assessment was a statistically significant predictor of AMLs (both p < 0.001). Inter-reader agreement for the "drooping" sign was moderate (k = 0.55) and for angular interface was fair (k = 0.33). Agreement between the two methods of assessing the "drooping" sign was substantial (k = 0.84) and of assessing the angular interface was moderate (k = 0.59). The "drooping" sign both qualitatively and quantitatively, alone or in combination of angular interface, had very high specificity (96-100%) and positive predictive value (PPV) (89-100%), moderate negative predictive value (62-68%), but limited sensitivity (23-49%) for lipid-poor AMLs. CONCLUSION: The "drooping" sign by both qualitative and quantitative assessment is highly specific for lipid-rich and lipid-poor AMLs. This feature alone or in combination with angular interface can aid in CT diagnosis of lipid-poor AMLs with very high specificity and PPV.

Consumable Material Waste and Workflow Efficiency Comparison Between Multi-use Syringeless and Single-use Syringe-Based Injectors in Computed Tomography.

RATIONALE AND OBJECTIVES: Syringeless power injectors obviate the need for reloading iodinated contrast media (ICM) and plastic consumable pistons between exams. This study evaluates the potential time and material waste (ICM, plastic, saline, and total) saved using a multi-use syringeless injector (MUSI) compared to a single-use syringe-based injector (SUSI). MATERIALS AND METHODS: Two observers recorded technologist time spent using a SUSI and a MUSI over three clinical workdays. CT technologists (n = 15) were polled on their experience between the systems using a 5-point Likert scale survey. ICM, plastic, and saline waste data from each system were collected. A mathematical model was created to estimate total and categorical waste from each injector system over a 16-week period. RESULTS: On average, CT technologists spent 40.5 seconds less per exam with MUSI compared to SUSI (p < .001). Technologists rated MUSI work efficiency, user-friendliness, and overall satisfaction (strongly or somewhat improved) higher relative to SUSI (p < .05). Iodine waste was 31.3 L and 0.0 L for SUSI and MUSI, respectively. Plastic waste was 467.7 kg and 71.9 kg for SUSI and MUSI, respectively. Saline waste was 43.3 L and 52.5 L for SUSI and MUSI, respectively. Total waste was 555.0 kg and 124.4 kg for SUSI and MUSI respectively. CONCLUSION: Switching from SUSI to MUSI resulted in a 100%, 84.6%, and 77.6% reduction in ICM, plastic, and total waste. This system may fortify institutional endeavors toward green radiology initiatives. The potential time saved administering contrast using MUSI may improve CT technologist efficiency.

CT Navigation for Percutaneous Needle Placement: How I Do It.

CT navigation (CTN) has recently been developed to combine many of the advantages of conventional CT and CT-fluoroscopic guidance for needle placement. CTN systems display real-time needle position superimposed on a CT dataset. This is accomplished by placing electromagnetic (EM) or optical transmitters/sensors on the patient and needle, combined with fiducials placed within the scan field to superimpose a known needle location onto a CT dataset. Advantages of CTN include real-time needle tracking using a contemporaneous CT dataset with the patient in the treatment position, reduced radiation to the physician, facilitation of procedures outside the gantry plane, fewer helical scans during needle placement, and needle guidance based on diagnostic-quality CT datasets. Limitations include the display of a virtual (vs actual) needle position, which can be inaccurate if the needle bends, the fiducial moves, or patient movement occurs between scans, and limitations in anatomical regions with a high degree of motion such as the lung bases. This review summarizes recently introduced CTN technologies in comparison to historical methods of CT needle guidance. A "How I do it" section follows, which describes how CT navigation has been integrated into the study center for both routine and challenging procedures, and includes step-by-step explanations, technical tips, and pitfalls.

Quantitative dual-energy CT techniques in the abdomen.

Advances in dual-energy CT (DECT) technology and spectral techniques are catalyzing the widespread implementation of this technology across multiple radiology subspecialties. The inclusion of energy- and material-specific datasets has ushered overall improvements in CT image contrast and noise as well as artifacts reduction, leading to considerable progress in radiologists' ability to detect and characterize pathologies in the abdomen. The scope of this article is to provide an overview of various quantitative clinical DECT applications in the abdomen and pelvis. Several of the reviewed applications have not reached mainstream clinical use and are considered investigational. Nonetheless awareness of such applications is critical to having a fully comprehensive knowledge base to DECT and fostering future clinical implementation.

Microsurgical Pontine Descending Tractotomy in Cases of Intractable Trigeminal Neuralgia.

BACKGROUND: Current treatment strategies in patients with trigeminal neuralgia (TN) include trials of medical therapy and surgical intervention, when necessary. In some patients, pain is not adequately managed with these existing strategies. OBJECTIVE: To present a novel technique, ventral pontine trigeminal tractotomy via retrosigmoid craniectomy, as an adjunct treatment in TN when there is no significant neurovascular compression. METHODS: We present a nonrandomized retrospective comparison between 50 patients who lacked clear or impressive arterial neurovascular compression of the trigeminal nerve as judged by preoperative magnetic resonance imaging and intraoperative observations. These patients had intractable TN unresponsive to previous treatment. Trigeminal tractotomy was performed either alone or in conjunction with microvascular decompression. Stereotactic neuronavigation was used during surgery to localize the descending tract via a ventral pontine approach for descending tractotomy. RESULTS: Follow-up was a mean of 44 months. At first follow-up, 80% of patients experienced complete relief of their pain, and 18% had partial relief. At the most recent follow-up, 74% of patients were considered a successful outcome. Only 1 (2%) patient had no relief after trigeminal tractotomy. Of those with multiple sclerosis-related TN, 87.5% experienced successful relief of pain at their latest follow-up. CONCLUSION: While patient selection is a significant challenge, this procedure represents an option for patients with TN who have absent or equivocal neurovascular compression, multiple sclerosis-related TN, or recurrent TN.

An angiogenic inhibitor, cyclic RGDfV, attenuates MPTP-induced dopamine neuron toxicity.

We previously demonstrated that several dopamine (DA) neurotoxins produced punctate areas of FITC-labeled albumin (FITC-LA) leakage in the substantia nigra and striatum suggesting blood brain barrier (BBB) dysfunction. Further, this leakage was co-localized with αvß3 integrin up-regulation, a marker for angiogenesis. This suggested that the FITC-LA leakage might have been a result of angiogenesis. To assess the possible role of angiogenesis in DA neuron loss, we treated mice with 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine (MPTP) and on the following day treated with cyRGDfV, a cyclic peptide that binds to integrin αvß3 and prevents angiogenesis. Post-treatment for 3 days (b.i.d.) with cyRGDfV blocked the MPTP-induced upregulation of integrin ß3 immunoreactivity (a marker for angiogenesis), leakage of FITC-LA into brain parenchyma (a marker for BBB disruption) as well as the down regulation of Zona Occludin-1 (ZO-1; a marker for tight junction integrity). In addition, cyRGDfV also completely prevented tyrosine hydroxylase immunoreactive cell loss (a marker for DA neurons) and markedly attenuated the up-regulation of activated microglia (Iba1 cell counts and morphology). These data suggest that cyRGDfV, and perhaps other anti-angiogenic drugs, are neuroprotective following acute MPTP treatment and may suggest that compensatory angiogenesis and BBB dysfunction may contribute to inflammation and DA neuron loss.