The Effect of taVNS at 25 Hz and 100 Hz on Parkinson's Disease Gait-A Randomized Motion Sensor Study.

BACKGROUND: Transcutaneous electrostimulation of the auricular branch of the vagal nerve (taVNS) has the propensity to reach diffuse neuromodulatory networks, which are dysfunctional in Parkinson's disease (PD). Previous studies support the use of taVNS as an add-on treatment for gait in PD. OBJECTIVES: We assessed the effect of taVNS at 25 Hz (taVNS25), taVNS at 100 Hz (taVNS100), and sham earlobe stimulation (sVNS) on levodopa responsive (arm swing velocity, arm range of motion, stride length, gait speed) and non-responsive gait characteristics (arm range of motion asymmetry, anticipatory postural adjustment [APA] duration, APA first step duration, APA first step range of motion), and turns (first turn duration, double 360° turn duration, steps per turn) in advanced PD. METHODS: In our double blind sham controlled within-subject randomized trial, we included 30 PD patients (modified Hoehn and Yahr stage, 2.5-4) to assess the effect of taVNS25, taVNS100, and sVNS on gait characteristics measured with inertial motion sensors during the instrumented stand and walk test and a double 360° turn. Separate generalized mixed models were built for each gait characteristic. RESULTS: During taVNS100 compared to sVNS arm swing velocity (P = 0.030) and stride length increased (P = 0.027), and APA duration decreased (P = 0.050). During taVNS25 compared to sVNS stride length (P = 0.024) and gait speed (P = 0.021) increased and double 360° turn duration decreased (P = 0.039). CONCLUSIONS: We have found that taVNS has a frequency specific propensity to improve stride length, arm swing velocity, and gait speed and double 360° turn duration in PD patients. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Tail Artifact Removal via Transmittance Effect Subtraction in Optical Coherence Tail Artifact Images.

Optical Coherence Tomography Angiography (OCTA) has revolutionized non-invasive, high-resolution imaging of blood vessels. However, the challenge of tail artifacts in OCTA images persists. In response, we present the Tail Artifact Removal via Transmittance Effect Subtraction (TAR-TES) algorithm that effectively mitigates these artifacts. Through a simple physics-based model, the TAR-TES accounts for variations in transmittance within the shallow layers with the vasculature, resulting in the removal of tail artifacts in deeper layers after the vessel. Comparative evaluations with alternative correction methods demonstrate that TAR-TES excels in eliminating these artifacts while preserving the essential integrity of vasculature images. Crucially, the success of the TAR-TES is closely linked to the precise adjustment of a weight constant, underlining the significance of individual dataset parameter optimization. In conclusion, TAR-TES emerges as a powerful tool for enhancing OCTA image quality and reliability in both clinical and research settings, promising to reshape the way we visualize and analyze intricate vascular networks within biological tissues. Further validation across diverse datasets is essential to unlock the full potential of this physics-based solution.

Hyperspectral Imaging with Active Illumination: A Theoretical Study on the Use of Incandescent Lamp and Variable Filament Temperature.

In this study, we introduce a novel hyperspectral imaging approach that leverages variable filament temperature incandescent lamps for active illumination, coupled with multi-channel image acquisition, and provide a comprehensive characterization of the approach. Our methodology simulates the imaging process, encompassing spectral illumination ranging from 400 to 700 nm at varying filament temperatures, multi-channel image capture, and hyperspectral image reconstruction. We present an algorithm for spectrum reconstruction, addressing the inherent challenges of this ill-posed inverse problem. Through a rigorous sensitivity analysis, we assess the impact of various acquisition parameters on the accuracy of reconstructed spectra, including noise levels, temperature steps, filament temperature range, illumination spectral uncertainties, spectral step sizes in reconstructed spectra, and the number of detected spectral channels. Our simulation results demonstrate the successful reconstruction of most spectra, with Root Mean Squared Errors (RMSE) below 5%, reaching as low as 0.1% for specific cases such as black color. Notably, illumination spectrum accuracy emerges as a critical factor influencing reconstruction quality, with flat spectra exhibiting higher accuracy than complex ones. Ultimately, our study establishes the theoretical grounds of this innovative hyperspectral approach and identifies optimal acquisition parameters, setting the stage for future practical implementations.

Curvature and height corrections of hyperspectral images using built-in 3D laser profilometry.

Optical imaging systems use a light source that illuminates a sample and a photodetector that detects light reflected from or transmitted through the sample. The sample surface curvature, surface-to-camera distance, and illumination-source-to-surface distance significantly affect the measured signal, resulting in image artifacts. To correct the images, a three-dimensional (3D) profilometry system was used to obtain 3D surface information. The 3D information enables image correction using Lambert cosine law and height correction. In this study, the feasibility of the correction method for push-broom hyperspectral imaging of three different objects is presented. Results show a significant reduction of image artifacts, making further image analysis more accurate and robust. The presented 3D profilometry method is applicable to all push-broom imaging systems and the described correction procedure can be applied to all spectral or monochromatic imaging systems.

Optimal scan time for evaluation of parathyroid adenoma with [(18)F]-fluorocholine PET/CT.

BACKGROUND: Parathyroid adenomas, the most common cause of primary hyperparathyroidism, are benign tumours which autonomously produce and secrete parathyroid hormone. [(18)F]-fluorocholine (FCH), PET marker of cellular proliferation, was recently demonstrated to accumulate in lesions representing enlarged parathyroid tissue; however, the optimal time to perform FCH PET/CT after FCH administration is not known. The aim of this study was to determine the optimal scan time of FCH PET/CT in patients with primary hyperparathyroidism. PATIENTS AND METHODS: 43 patients with primary hyperparathyroidism were enrolled in this study. A triple-phase PET/CT imaging was performed five minutes, one and two hours after the administration of FCH. Regions of interest (ROI) were placed in lesions representing enlarged parathyroid tissue and thyroid tissue. Standardized uptake value (SUVmean), retention index and lesion contrast for parathyroid and thyroid tissue were calculated. RESULTS: Accumulation of FCH was higher in lesions representing enlarged parathyroid tissue in comparison to the thyroid tissue with significantly higher SUVmean in the second and in the third phase (p < 0.0001). Average retention index decreased significantly between the first and the second phase and increased significantly between the second and the third phase in lesions representing enlarged parathyroid tissue and decreased significantly over all three phases in thyroid tissue (p< 0.0001). The lesion contrast of lesions representing enlarged parathyroid tissue and thyroid tissue was significantly better in the second and the third phase compared to the first phase (p < 0.05). CONCLUSIONS: According to the results the optimal scan time of FCH PET/CT for localization of lesions representing enlarged parathyroid tissue is one hour after administration of the FCH.

Imaging microvascular changes in nonocular oncological clinical applications by optical coherence tomography angiography: a literature review.

BACKGROUND: Optical coherence tomography angiography (OCTA) is an emerging imaging modality that enables noninvasive visualization and analysis of tumor vasculature. OCTA has been particularly useful in clinical ocular oncology, while in this article, we evaluated OCTA in assessing microvascular changes in clinical nonocular oncology through a systematic review of the literature. METHOD: The inclusion criterion for the literature search in PubMed, Web of Science and Scopus electronic databases was the use of OCTA in nonocular clinical oncology, meaning that all ocular clinical studies and all ocular and nonocular animal, phantom, ex vivo, experimental, research and development, and purely methodological studies were excluded. RESULTS: Eleven articles met the inclusion criteria. The anatomic locations of the neoplasms in the selected articles were the gastrointestinal tract (2 articles), head and neck (1 article) and skin (8 articles). CONCLUSIONS: While OCTA has shown great advancements in ophthalmology, its translation to the nonocular clinical oncology setting presents several limitations, with a lack of standardized protocols and interpretation guidelines posing the most significant challenge.

Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer's disease-related pattern.

BACKGROUND: Alzheimer's disease-related pattern (ADRP) is a metabolic brain biomarker of Alzheimer's disease (AD). While ADRP is being introduced into research, the effect of the size of the identification cohort and the effect of the resolution of identification and validation images on ADRP's performance need to be clarified. METHODS: 240 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography images [120 AD/120 cognitive normals (CN)] were selected from the Alzheimer's disease neuroimaging initiative database. A total of 200 images (100 AD/100 CN) were used to identify different versions of ADRP using a scaled subprofile model/principal component analysis. For this purpose, five identification groups were randomly selected 25 times. The identification groups differed in the number of images (20 AD/20 CN, 30 AD/30 CN, 40 AD/40 CN, 60 AD/60 CN, and 80 AD/80 CN) and image resolutions (6, 8, 10, 12, 15 and 20 mm). A total of 750 ADRPs were identified and validated through the area under the curve (AUC) values on the remaining 20 AD/20 CN with six different image resolutions. RESULTS: ADRP's performance for the differentiation between AD patients and CN demonstrated only a marginal average AUC increase, when the number of subjects in the identification group increases (AUC increase for about 0.03 from 20 AD/20 CN to 80 AD/80 CN). However, the average of the lowest five AUC values increased with the increasing number of participants (AUC increase for about 0.07 from 20 AD/20 CN to 30 AD/30 CN and for an additional 0.02 from 30 AD/30 CN to 40 AD/40 CN). The resolution of the identification images affects ADRP's diagnostic performance only marginally in the range from 8 to 15 mm. ADRP's performance stayed optimal even when applied to validation images of resolution differing from the identification images. CONCLUSIONS: While small (20 AD/20 CN images) identification cohorts may be adequate in a favorable selection of cases, larger cohorts (at least 30 AD/30 CN images) shall be preferred to overcome possible/random biological differences and improve ADRP's diagnostic performance. ADRP's performance stays stable even when applied to the validation images with a resolution different than the resolution of the identification ones.

Imaging perfusion changes in oncological clinical applications by hyperspectral imaging: a literature review.

BACKGROUND: Hyperspectral imaging (HSI) is a promising imaging modality that uses visible light to obtain information about blood flow. It has the distinct advantage of being noncontact, nonionizing, and noninvasive without the need for a contrast agent. Among the many applications of HSI in the medical field are the detection of various types of tumors and the evaluation of their blood flow, as well as the healing processes of grafts and wounds. Since tumor perfusion is one of the critical factors in oncology, we assessed the value of HSI in quantifying perfusion changes during interventions in clinical oncology through a systematic review of the literature. MATERIALS AND METHODS: The PubMed and Web of Science electronic databases were searched using the terms "hyperspectral imaging perfusion cancer" and "hyperspectral imaging resection cancer". The inclusion criterion was the use of HSI in clinical oncology, meaning that all animal, phantom, ex vivo, experimental, research and development, and purely methodological studies were excluded. RESULTS: Twenty articles met the inclusion criteria. The anatomic locations of the neoplasms in the selected articles were as follows: kidneys (1 article), breasts (2 articles), eye (1 article), brain (4 articles), entire gastrointestinal (GI) tract (1 article), upper GI tract (5 articles), and lower GI tract (6 articles). CONCLUSIONS: HSI is a potentially attractive imaging modality for clinical application in oncology, with assessment of mastectomy skin flap perfusion after reconstructive breast surgery and anastomotic perfusion during reconstruction of gastrointenstinal conduit as the most promising at present.

The dose accumulation and the impact of deformable image registration on dose reporting parameters in a moving patient undergoing proton radiotherapy.

INTRODUCTION: Potential changes in patient anatomy during proton radiotherapy may lead to a deviation of the delivered dose. A dose estimate can be computed through a deformable image registration (DIR) driven dose accumulation. The present study evaluates the accumulated dose uncertainties in a patient subject to an inadvertent breathing associated motion. MATERIALS AND METHODS: A virtual lung tumour was inserted into a pair of single participant landmark annotated computed tomography images depicting opposite breathing phases, with the deep inspiration breath-hold the planning reference and the exhale the off-reference geometry. A novel Monte Carlo N-Particle, Version 6 (MCNP6) dose engine was developed, validated and used in treatment plan optimization. Three DIR methods were compared and used to transfer the exhale simulated dose to the reference geometry. Dose conformity and homogeneity measures from International Committee on Radioactivity Units and Measurements (ICRU) reports 78 and 83 were evaluated on simulated dose distributions registered with different DIR algorithms. RESULTS: The MCNP6 dose engine handled patient-like geometries in reasonable dose calculation times. All registration methods were able to align image associated landmarks to distances, comparable to voxel sizes. A moderate deterioration of ICRU measures was encountered in comparing doses in on and off-reference anatomy. There were statistically significant DIR driven differences in ICRU measures, particularly a 10% difference in the relative D98% for planning tumour volume and in the 3 mm/3% gamma passing rate. CONCLUSIONS: T he dose accumulation over two anatomies resulted in a DIR driven uncertainty, important in reporting the associated ICRU measures for quality assurance.

Anatomically Accurate, High-Resolution Modeling of the Human Index Finger Using In Vivo Magnetic Resonance Imaging.

Anatomically accurate models of a human finger can be useful in simulating various disorders. In order to have potential clinical value, such models need to include a large number of tissue types, identified by an experienced professional, and should be versatile enough to be readily tailored to specific pathologies. Magnetic resonance images were acquired at ultrahigh magnetic field (7 T) with a radio-frequency coil specially designed for finger imaging. Segmentation was carried out under the supervision of an experienced radiologist to accurately capture various tissue types (TTs). The final segmented model of the human index finger had a spatial resolution of 0.2 mm and included 6,809,600 voxels. In total, 15 TTs were identified: subcutis, Pacinian corpuscle, nerve, vein, artery, tendon, collateral ligament, volar plate, pulley A4, bone, cartilage, synovial cavity, joint capsule, epidermis and dermis. The model was applied to the conditions of arthritic joint, ruptured tendon and variations in the geometry of a finger. High-resolution magnetic resonance images along with careful segmentation proved useful in the construction of an anatomically accurate model of the human index finger. An example illustrating the utility of the model in biomedical applications is shown. As the model includes a number of tissue types, it may present a solid foundation for future simulations of various musculoskeletal disease processes in human joints.

Effect of curvature correction on parameters extracted from hyperspectral images.

SIGNIFICANCE: Hyperspectral imaging (HSI) has emerged as a promising optical technique. Besides optical properties of a sample, other sample physical properties also affect the recorded images. They are significantly affected by the sample curvature and sample surface to camera distance. A correction method to reduce the artifacts is necessary to reliably extract sample properties. AIM: Our aim is to correct hyperspectral images using the three-dimensional (3D) surface data and assess how the correction affects the extracted sample properties. APPROACH: We propose the combination of HSI and 3D profilometry to correct the images using the Lambert cosine law. The feasibility of the correction method is presented first on hemispherical tissue phantoms and next on human hands before, during, and after the vascular occlusion test (VOT). RESULTS: Seven different phantoms with known optical properties were created and imaged with a hyperspectral system. The correction method worked up to 60 deg inclination angle, whereas for uncorrected images the maximum angles were 20 deg. Imaging hands before, during, and after VOT shows good agreement between the expected and extracted skin physiological parameters. CONCLUSIONS: The correction method was successfully applied on the images of tissue phantoms of known optical properties and geometry and VOT. The proposed method could be applied to any reflectance optical imaging technique and should be used whenever the sample parameters need to be extracted from a curved surface sample.

Selection of the First 99mTc-Labelled Somatostatin Receptor Subtype 2 Antagonist for Clinical Translation-Preclinical Assessment of Two Optimized Candidates.

Recently, radiolabelled antagonists targeting somatostatin receptors subtype 2 (SST2) in neuroendocrine neoplasms demonstrated certain superior properties over agonists. Within the ERA-PerMED project "TECANT" two 99mTc-Tetramine (N4)-derivatized SST2 antagonists (TECANT-1 and TECANT-2) were studied for the selection of the best candidate for clinical translation. Receptor-affinity, internalization and dissociation studies were performed in human embryonic kidney-293 (HEK293) cells transfected with the human SST2 (HEK-SST2). Log D, protein binding and stability in human serum were assessed. Biodistribution and SPECT/CT studies were carried out in nude mice bearing HEK-SST2 xenografts, together with dosimetric estimations from mouse-to-man. [99mTc]Tc-TECANT-1 showed higher hydrophilicity and lower protein binding than [99mTc]-TECANT-2, while stability was comparable. Both radiotracers revealed similar binding affinity, while [99mTc]Tc-TECANT-1 had higher cellular uptake (>50%, at 2 h/37 °C) and lower dissociation rate (<30%, at 2 h/37 °C). In vivo, [99mTc]Tc-TECANT-1 showed lower blood values, kidney and muscles uptake, whereas tumour uptake was comparable to [99mTc]Tc-TECANT-2. SPECT/CT imaging confirmed the biodistribution results, providing the best tumour-to-background image contrast for [99mTc]Tc-TECANT-1 at 4 h post-injection (p.i.). The estimated radiation dose amounted to approximately 6 µSv/MBq for both radiotracers. This preclinical study provided the basis of selection of [99mTc]Tc-TECANT-1 for clinical translation of the first 99mTc-based SST2 antagonist.

[18F]FDG PET immunotherapy radiomics signature (iRADIOMICS) predicts response of non-small-cell lung cancer patients treated with pembrolizumab.

Background Immune checkpoint inhibitors have changed the paradigm of cancer treatment; however, non-invasive biomarkers of response are still needed to identify candidates for non-responders. We aimed to investigate whether immunotherapy [18F]FDG PET radiomics signature (iRADIOMICS) predicts response of metastatic non-small-cell lung cancer (NSCLC) patients to pembrolizumab better than the current clinical standards. Patients and methods Thirty patients receiving pembrolizumab were scanned with [18F]FDG PET/CT at baseline, month 1 and 4. Associations of six robust primary tumour radiomics features with overall survival were analysed with Mann-Whitney U-test (MWU), Cox proportional hazards regression analysis, and ROC curve analysis. iRADIOMICS was constructed using univariate and multivariate logistic models of the most promising feature(s). Its predictive power was compared to PD-L1 tumour proportion score (TPS) and iRECIST using ROC curve analysis. Prediction accuracies were assessed with 5-fold cross validation. Results The most predictive were baseline radiomics features, e.g. Small Run Emphasis (MWU, p = 0.001; hazard ratio = 0.46, p = 0.007; AUC = 0.85 (95% CI 0.69-1.00)). Multivariate iRADIOMICS was found superior to the current standards in terms of predictive power and timewise with the following AUC (95% CI) and accuracy (standard deviation): iRADIOMICS (baseline), 0.90 (0.78-1.00), 78% (18%); PD-L1 TPS (baseline), 0.60 (0.37-0.83), 53% (18%); iRECIST (month 1), 0.79 (0.62-0.95), 76% (16%); iRECIST (month 4), 0.86 (0.72-1.00), 76% (17%). Conclusions Multivariate iRADIOMICS was identified as a promising imaging biomarker, which could improve management of metastatic NSCLC patients treated with pembrolizumab. The predicted non-responders could be offered other treatment options to improve their overall survival.

Computational modelling of resistance and associated treatment response heterogeneity in metastatic cancers.

Metastatic cancer patients invariably develop treatment resistance. Different levels of resistance lead to observed heterogeneity in treatment response. The main goal was to evaluate treatment response heterogeneity with a computation model simulating the dynamics of drug-sensitive and drug-resistant cells. Model parameters included proliferation, drug-induced death, transition and proportion of intrinsically resistant cells. The model was benchmarked with imaging metrics extracted from 39 metastatic prostate cancer patients who had 18F-NaF-PET/CT scans performed at baseline and at three cycles into chemotherapy or hormonal therapy. Two initial model assumptions were evaluated: considering only inter-patient heterogeneity and both inter-patient and intra-patient heterogeneity in the proportion of intrinsically resistant cells. The correlation between the median proportion of intrinsically resistant cells and baseline patient-level imaging metrics was assessed with Spearman's rank correlation coefficient. The impact of model parameters on simulated treatment response was evaluated with a sensitivity study. Treatment response after periods of six, nine, and 12 months was predicted with the model. The median predicted range of response for patients treated with both therapies was compared with a Wilcoxon rank sum test. For each patient, the time was calculated when the proportion of disease with a non-favourable response outperformed a favourable response. By taking into account inter-patient and intra-patient heterogeneity in the proportion of intrinsically resistant cells, the model performed significantly better ([Formula: see text]) than by taking into account only inter-patient heterogeneity ([Formula: see text]). The median proportion of intrinsically resistant cells showed a moderate correlation (ρ = 0.55) with mean patient-level uptake, and a low correlation (ρ = 0.36) with the dispersion of mean metastasis-level uptake in a patient. The sensitivity study showed a strong impact of the proportion of intrinsically resistant cells on model behaviour after three cycles of therapy. The difference in the median range of response (MRR) was not significant between cohorts at any time point (p  > 0.15). The median time when the proportion of disease with a non-favourable response outperformed the favourable response was eight months, for both cohorts. The model provides an insight into inter-patient and intra-patient heterogeneity in the evolution of treatment resistance.

Predicting tumour response to anti-PD-1 immunotherapy with computational modelling.

Cancer immunotherapy is a rapidly developing field, with numerous drugs and therapy combinations waiting to be tested in pre-clinical and clinical settings. However, the costly and time-consuming trial-and-error approach to development of new treatment paradigms creates a research bottleneck, motivating the development of complementary approaches. Computational modelling is a compelling candidate for this task, however, difficulties associated with the validation of such models limit their use in pre-clinical and clinical settings. Here we propose a bottom-up deterministic computational model to simulate tumour response to treatment with anti-programmed-death-1 antibodies (anti-PD-1). The model was built with validation in mind, and so contains minimum number of parameters, and only four free parameters. Moreover, all model parameters can be measured experimentally. Free parameters were tuned by fitting the model to experimental data from the literature, using B16-F10 murine melanoma implanted into wild type (C57BL/6), as well as into immunodeficient (NSG) mice strains, and treated with anti-PD-1 antibodies. The model's predictive ability was verified on two independent datasets from literature with different but well-known inputs. To identify possible biomarkers of response to anti-PD-1 immunotherapy, sensitivity study of key model parameters was performed. Good agreement between the simulated tumour growth curves and the experimental data was achieved, with mean relative deviations in the range of 13%-20%. Our sensitivity study demonstrated that major histocompatibility complex (MHC) class I expression was the only parameter able to clearly discriminate responders from non-responders to anti-PD-1 therapy. Additionally, the results of sensitivity studies suggest that MHC class I expression might affect the predictive ability of other biomarkers that are currently used in the clinics, such as PD-1 ligand (PD-L1) expression. Interestingly, our model predicts the best response to anti-PD-1 therapy for subjects with moderate PD-L1 values. Such computational models show promise to support, guide and accelerate future immunotherapy research.

Dynamic 18F-FLT PET imaging of spatiotemporal changes in tumor cell proliferation and vasculature reveals the mechanistic actions of anti-angiogenic therapy.

Anti-angiogenic therapies target tumor vasculature and tumor cells, thus a concurrent assessment of these targets would lead to a greater understanding of therapeutic resistance and facilitate development of improved therapeutic strategies. We utilize dynamic 3'-deoxy-3'-18F-fluorothymidine positron emission tomography (18F-FLT PET) scanning to concurrently assess changes in tumor cell proliferation and vasculature during anti-angiogenic therapy, providing insight into how these therapies may be used effectively with combination chemotherapy. Thirty-three patients with advanced solid malignancies underwent treatment with vascular endothelial growth factor receptor inhibitor (VEGFR-TKI) axitinib on an intermittent schedule (two-weeks-on/one-week-off). Patients had up to three dynamic 18F-FLT PET/CT scans: at baseline, after two weeks of continuous VEGFR-TKI treatment, and following a one week treatment break. 18F-FLT kinetics were analyzed using a two-tissue compartment kinetic model. Kinetic parameters V b and K 1 were extracted to quantify changes in tumor vasculature and the 18F-FLT flux constant K i was calculated to quantify changes in tumor cell proliferation. Two weeks of continuous axitinib exposure led to decreases in V b (median -21%, P = 0.07), K 1 (median -39%, P < 0.01), and K i (median -37%, P < 0.01), corresponding to diminished tumor vasculature and cell proliferation that may antagonize treatment with concurrent chemotherapy. Axitinib treatment breaks led to significant increases in V b (median +42%, P < 0.01), K 1 (median +46%, P < 0.01), and K i (median +39%, P < 0.01) that is suggestive of an optimal time to schedule synergistic chemotherapy. Significant negative correlations (rho ⩽ -0.70, P < 0.01) were found between changes in tumor vasculature during axitinib exposure weeks and changes in tumor vasculature during treatment breaks. Imaging with dynamic 18F-FLT PET revealed new insights relating to the interplay of vascular and proliferative pharmacodynamics of axitinib therapy, facilitating a greater understanding of the mechanistic actions of VEGFR-TKIs. Increases in tumor vasculature and cell proliferation during VEGFR-TKI treatment breaks, suggests this period is an optimal time to schedule synergistic chemotherapy and warrants further investigation.

Comparison of DCE-MRI kinetic parameters and FMISO-PET uptake parameters in head and neck cancer patients.

PURPOSE: Tumor hypoxia is a major cause of radiation resistance, often present in various solid tumors. Dynamic [18 F]-fluoromisonidazole (FMISO) PET imaging is able to reliably assess tumor hypoxia. Comprehensive characterization of tumor microenvironment through FMISO-PET and dynamic contrast enhanced (DCE) MR multimodality imaging might be a valuable alternative to the dynamic FMISO-PET acquisition. The aim of this work was to explore the correlation between the FMISO-PET and DCE-MRI kinetic parameters. METHODS: This study was done on head and neck cancer patients (N = 6), who were imaged dynamically with FMISO-PET and DCE-MRI on the same day. Images were registered and analyzed for kinetics on a voxel basis. FMISO-PET images were analyzed with the two-tissue compartment three rate-constant model. Additionally, tumor-to-muscle ratio (TMR) maps were evaluated. DCE-MRI was analyzed with the extended Tofts model. Voxel-wise Pearson's coefficients were calculated for each patient to assess pairwise parameter correlations. RESULTS: Median correlations between FMISO uptake parameters and DCE-MRI kinetic parameters varied across the parameter pairs in the range from -0.05 to 0.71. The highest median correlation of r = 0.71 was observed for the pair Vb -vp , while the K1 -Ktrans median correlation was r = 0.45. Median correlation coefficients for the K1 -vp and the Ki -Ktrans pairs were r = 0.42 and r = 0.32, respectively. Correlations between FMISO uptake rate parameter Ki and DCE-MRI kinetic parameters varied substantially across the patients, whereas correlations between the FMISO and DCE-MRI vascular parameters were consistently high. Median TMR-K1 and TMR-Ktrans correlations were r = 0.52 and r = 0.46, respectively, but varied substantially across the patients. CONCLUSIONS: Based on this clinical evidence, we can conclude that the vascular fraction parameters obtained through DCE-MRI kinetic analysis or FMISO kinetic analysis measure the same biological property, while other kinetic parameters are unrelated. These results might be useful in the design of future clinical trials involving FMISO-PET/DCE-MR multimodality imaging for the assessment of tumor microenvironment.

Molecular Imaging to Plan Radiotherapy and Evaluate Its Efficacy.

Molecular imaging plays a central role in the management of radiation oncology patients. Specific uses of imaging, particularly to plan radiotherapy and assess its efficacy, require an additional level of reproducibility and image quality beyond what is required for diagnostic imaging. Specific requirements include proper patient preparation, adequate technologist training, careful imaging protocol design, reliable scanner technology, reproducible software algorithms, and reliable data analysis methods. As uncertainty in target definition is arguably the greatest challenge facing radiation oncology, the greatest impact that molecular imaging can have may be in the reduction of interobserver variability in target volume delineation and in providing greater conformity between target volume boundaries and true tumor boundaries. Several automatic and semiautomatic contouring methods based on molecular imaging are available but still need sufficient validation to be widely adopted. Biologically conformal radiotherapy (dose painting) based on molecular imaging-assessed tumor heterogeneity is being investigated, but many challenges remain to fully exploring its potential. Molecular imaging also plays increasingly important roles in both early (during treatment) and late (after treatment) response assessment as both a predictive and a prognostic tool. Because of potentially confounding effects of radiation-induced inflammation, treatment response assessment requires careful interpretation. Although molecular imaging is already strongly embedded in radiotherapy, the path to widespread and all-inclusive use is still long. The lack of solid clinical evidence is the main impediment to broader use. Recommendations for practicing physicians are still rather scarce. (18)F-FDG PET/CT remains the main molecular imaging modality in radiation oncology applications. Although other molecular imaging options (e.g., proliferation imaging) are becoming more common, their widespread use is limited by lack of tracer availability and inadequate reimbursement models. With the increasing presence of molecular imaging in radiation oncology, special emphasis should be placed on adequate training of radiation oncology personnel to understand the potential, and particularly the limitations, of quantitative molecular imaging applications. Similarly, radiologists and nuclear medicine specialists should be sensitized to the special need of the radiation oncologist in terms of quantification and reproducibility. Furthermore, strong collaboration between radiation oncology, nuclear medicine/radiology, and medical physics teams is necessary, as optimal and safe use of molecular imaging can be ensured only within appropriate interdisciplinary teams.