Multiphase CT angiography perfusion maps for predicting target mismatch and ischemic lesion volumes.

The complexity of CT perfusion (CTP) acquisition protocols may limit the availability of target mismatch assessment at resource-limited hospitals. We compared CTP mismatch with a mismatch surrogate generated from a simplified dynamic imaging sequence comprising widely available non-contrast CT (NCCT) and multiphase CT angiography (mCTA). Consecutive patients with anterior circulation acute ischemic stroke who received NCCT, mCTA, and CTP were retrospectively included in this study. An mCTA-perfusion (mCTA-P) dynamic series was formed by co-registering NCCT and mCTA. We simulated an ideal mCTA-P study by down-sampling CTP (dCTP) dynamic images according to mCTA timing. Ischemic core and penumbra volumes were estimated by cerebral blood flow and Tmax thresholding, respectively, on perfusion maps calculated independently for CTP, dCTP, and mCTA-P by deconvolution. Concordance in target mismatch (core < 70 ml, penumbra ≥ 15 ml, mismatch ratio ≥ 1.8) determination by dCTP and mCTA-P versus CTP was assessed. Of sixty-one included patients, forty-six had a CTP target mismatch. Concordance with CTP profiles was 90% and 82% for dCTP and mCTA-P, respectively. Lower mCTA-P concordance was likely from differences in collimation width between NCCT and mCTA, which worsened perfusion map quality due to a CT number shift at mCTA. Moderate diagnostic agreement between CTP and mCTA-P was found and may improve with optimal mCTA scan parameter selection as simulated by dCTP. mCTA-P may be a pragmatic alternative where CTP is unavailable or the risks of additional radiation dose, contrast injections, and treatment delays outweigh the potential benefit of a separate CTP scan.

Glucose Infusion Induced Change in Intracellular pH and Its Relationship with Tumor Glycolysis in a C6 Rat Model of Glioblastoma.

INTRODUCTION: The reliance on glycolytic metabolism is a hallmark of tumor metabolism. Excess acid and protons are produced, leading to an acidic tumor environment. Therefore, we explored the relationship between the tumor glycolytic metabolism and tissue pH by comparing 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) and hyperpolarized [1-13C]pyruvate MR spectroscopy imaging (MRSI) to chemical exchange saturation transfer (CEST) MRI measurements of tumor pH. METHODS: 106 C6 glioma cells were implanted in the brains of male Wistar rats (N = 11) using stereotactic surgery. A 60-min PET acquisition after a bolus of FDG was performed at 11-13 days post implantation, and standardized uptake value (SUV) was calculated. CEST measurements were acquired the following day before and during constant infusion of glucose solution. Tumor intracellular pH (pHi) was evaluated using amine and amide concentration-independent detection (AACID) CEST MRI. The change of pHi (∆pHi) was calculated as the difference between pHi pre- and during glucose infusion. Rats were imaged immediately with hyperpolarized [1-13C]pyruvate MRSI. Regional maps of the ratio of Lac:Pyr were acquired. The correlations between SUV, Lac:Pyr ratio, and ∆pHi were evaluated using Pearson's correlation. RESULTS: A decrease of 0.14 in pHi was found after glucose infusion in tumor region. Significant correlations between tumor glycolysis measurements of Lac:Pyr and ∆pHi within the tumor (ρ = 0.83, P = 0.01) and peritumoral region (ρ = 0.76, P = 0.028) were observed. No significant correlations were found between tumor SUV and ∆pHi within the tumor (ρ = - 0.45, P = 0.17) and peritumor regions (ρ = - 0.6, P = 0.051). CONCLUSION: AACID detected the changes in pHi induced by glucose infusion. Significant correlations between tumor glycolytic measurement of Lac:Pyr and tumoral and peritumoral pHi and ∆pHi suggest the intrinsic relationship between tumor glycolytic metabolism and the tumor pH environment as well as the peritumor pH environment.

Feasibility of deconvolution-based multiphase CT angiography perfusion maps in acute ischemic stroke: Simulation and concordance with CT perfusion.

OBJECTIVES: Integration of CT perfusion (CTP) with requisite non-contrast CT and CT angiography (CTA) stroke imaging may allow efficient stroke lesion volume measurement. Using surrogate images from CTP, we simulated the feasibility of using multiphase CTA (mCTA) to generate perfusion maps and assess target mismatch profiles. MATERIALS AND METHODS: Patients with acute ischemic stroke who received admission CTP were included in this study. Four CTP images (surrogate mCTA, one pre-contrast and three post-contrast, starting at the arterial peak then at 8 s intervals) were selected according to the CTP arterial time-density curve to simulate non-contrast CT and mCTA images. Cerebral blood flow (CBF) and Tmax maps were calculated using the same model-based deconvolution algorithm for the standard CTP and surrogate mCTA studies. Infarct and penumbra were delineated with CBF < 20% and Tmax > 6 s threshold, respectively. Classification accuracy of surrogate mCTA target mismatch (infarct <70 ml; penumbra ≥15 ml; mismatch ratio ≥1.8) with respect to standard CTP was assessed. Agreement between infarct and penumbra volumes from standard CTP and surrogate mCTA maps were evaluated by Bland-Altman analysis. RESULTS: Of 34 included patients, 28 had target mismatch and 6 did not by standard CTP. Accuracy of classifying target mismatch profiles with surrogate mCTA was 79% with respect to that from standard CTP. Mean  ±  standard deviation of differences (standard CTP minus surrogate mCTA) of infarct and penumbra volumes were 9.8 ± 14.8 ml and 20.1 ± 45.4 ml, respectively. CONCLUSIONS: Surrogate mCTA ischemic lesion volumes agreed with those from standard CTP and may be an efficient alternative when CTP is not practical.

A Phase II Randomized Trial of Chemoradiation with or without Metformin in Locally Advanced Cervical Cancer.

PURPOSE: Tumor hypoxia is associated with poor response to radiation (RT). We previously discovered a novel mechanism of metformin: enhancing tumor RT response by decreasing tumor hypoxia. We hypothesized that metformin would decrease tumor hypoxia and improve cervical cancer response to RT. PATIENTS AND METHODS: A window-of-opportunity, phase II randomized trial was performed in stage IB-IVA cervical cancer. Patients underwent screening positron emission tomography (PET) imaging with hypoxia tracer fluoroazomycin arabinoside (FAZA). Only patients with FAZA uptake (hypoxic tumor) were included and randomized 2:1 to receive metformin in combination with chemoRT or chemoRT alone. A second FAZA-PET/CT scan was performed after 1 week of metformin or no intervention (control). The primary endpoint was a change in fractional hypoxic volume (FHV) between FAZA-PET scans, compared using the Wilcoxon signed-rank test. The study was closed early due to FAZA availability and the COVID-19 pandemic. RESULTS: Of the 20 consented patients, 6 were excluded due to no FAZA uptake and 1 withdrew. FHV of 10 patients in the metformin arm decreased by an average of 10.2% (44.4%-34.2%) ± SD 16.9% after 1 week of metformin, compared with an average increase of 4.7% (29.1%-33.8%) ± 11.5% for the 3 controls (P = 0.027). Those with FHV reduction after metformin had significantly lower MATE2 expression. With a median follow-up of 2.8 years, the 2-year disease-free survival was 67% for the metformin arm versus 33% for controls (P = 0.09). CONCLUSIONS: Metformin decreased cervical tumor hypoxia in this trial that selected for patients with hypoxic tumor. See related commentary by Lyng et al., p. 5233.

Fast beta-emitter Monte Carlo simulations and full patient dose calculations of targeted radionuclide therapy: introducing egs_mird.

BACKGROUND: Targeted radionuclide therapy (TRT) is a fast-growing field garnering much interest, with several clinical trials currently underway, that has a steady increase in development of treatment techniques. Unfortunately, within the field and many clinical trials, the dosimetry calculation techniques used remain relatively simple, often using a mix of S-value calculations and kernel convolutions. PURPOSE: The common TRT calculation techniques, although very quick, can often ignore important aspects of patient anatomy and radionuclide distribution, as well as the interplay there-in. This paper introduces egs_mird, a new Monte Carlo (MC) application built in EGSnrc which allows users to model full patient tissue and density (using clinical CT images) and radionuclide distribution (using clinical PET images) for fast and detailed dose TRT calculation. METHODS: The novel application egs_mird is introduced along with a general outline of the structure of egs_mird simulations. The general structure of the code, and the track-length (TL) estimator scoring implementation for variance reduction, is described. A new egs++ source class egs_internal_source, created to allow detailed patient-wide source distribution, and a modified version of egs_radionuclide_source, changed to be able to work with egs_internal_source, are also described. The new code is compared to other MC calculations of S-values kernels of 131 I, 90 Y, and 177 Lu in the literature, along with further self-validation using a histogram variant of the electron Fano test. Several full patient prostate 177 Lu TRT prostate cancer treatment simulations are performed using a single set of patient DICOM CT and [18 F]-DCFPyL PET data. RESULTS: Good agreement is found between S-value kernels calculated using egs_mird with egs_internal_source and those found in the literature. Calculating 1000 doses (individual voxel uncertainties of ∼0.05%) in a voxel grid Fano test for monoenergetic 500 keV electrons and 177 Lu electrons results in 94% and 99% of the doses being within 0.1% of the expected dose, respectively. For a hypothetical 177 Lu treatment, patient prostate, rectum, bone marrow, and bladder dose volume histograms (DVHs) results did not vary significantly when using the TL estimator and not modeling electron transport, modeling bone marrow explicitly (rather than using generic tissue compositions), and reducing activity to voxels containing partial or full calcifications to half or none, respectively. Dose profiles through different regions demonstrate there are some differences with model choices not seen in the DVH. Simulations using the TL estimator can be completed in under 15 min (∼30 min when using standard interaction scoring). CONCLUSION: This work shows egs_mird to be a reliable MC code for computing TRT doses as realistically as the patient Computed Tomography (CT) and Positron Emission Tomography (PET) data allow. Furthermore, the code can compute doses to sub-1% uncertainty within 15 min, with little to no optimization. Thus, this work supports the use of egs_mird for dose calculations in TRT.

Imaging Biomarkers in Prostate Stereotactic Body Radiotherapy: A Review and Clinical Trial Protocol.

Advances in imaging have changed prostate radiotherapy through improved biochemical control from focal boost and improved detection of recurrence. These advances are reviewed in the context of prostate stereotactic body radiation therapy (SBRT) and the ARGOS/CLIMBER trial protocol. ARGOS/CLIMBER will evaluate 1) the safety and feasibility of SBRT with focal boost guided by multiparametric MRI (mpMRI) and 18F-PSMA-1007 PET and 2) imaging and laboratory biomarkers for response to SBRT. To date, response to prostate SBRT is most commonly evaluated using the Phoenix Criteria for biochemical failure. The drawbacks of this approach include lack of lesion identification, a high false-positive rate, and delay in identifying treatment failure. Patients in ARGOS/CLIMBER will receive dynamic 18F-PSMA-1007 PET and mpMRI prior to SBRT for treatment planning and at 6 and 24 months after SBRT to assess response. Imaging findings will be correlated with prostate-specific antigen (PSA) and biopsy results, with the goal of early, non-invasive, and accurate identification of treatment failure.

Short-duration dynamic [18F]DCFPyL PET and CT perfusion imaging to localize dominant intraprostatic lesions in prostate cancer: validation against digital histopathology and comparison to [18F]DCFPyL PET/MR at 120 minutes.

PURPOSE: Localized prostate cancer (PCa) in patients is characterized by a dominant focus in the gland (dominant intraprostatic lesion, DIL). Accurate DIL identification may enable more accurate diagnosis and therapy through more precise targeting of biopsy, radiotherapy and focal ablative therapies. The goal of this study is to validate the performance of [18F]DCFPyL PET and CT perfusion (CTP) for detecting and localizing DIL against digital histopathological images. METHODS: Multi-modality image sets: in vivo T2-weighted (T2w)-MRI, 22-min dynamic [18F]DCFPyL PET/CT, CTP, and 2-h post-injection PET/MR were acquired in patients prior to radical prostatectomy. The explanted gland with implanted fiducial markers was imaged with T2w-MRI. All images were co-registered to the pathologist-annotated digital images of whole-mount mid-gland histology sections using fiducial markers and anatomical landmarks. Regions of interest encompassing DIL and non-DIL tissue were drawn on the digital histopathological images and superimposed on PET and CTP parametric maps. Logistic regression with backward elimination of parameters was used to select the most sensitive parameter set to distinguish DIL from non-DIL voxels. Leave-one-patient-out cross-validation was performed to determine diagnostic performance. RESULTS: [18F]DCFPyL PET and CTP parametric maps of 15 patients were analyzed. SUVLate and a model combining Ki and k4 of [18F]DCFPyL achieved the most accurate performance distinguishing DIL from non-DIL voxels. Both detection models achieved an AUC of 0.90 and an error rate of < 10%. Compared to digital histopathology, the detected DILs had a mean dice similarity coefficient of 0.8 for the Ki and k4 model and 0.7 for SUVLate. CONCLUSIONS: We have validated using co-registered digital histopathological images that parameters from kinetic analysis of 22-min dynamic [18F]DCFPyL PET can accurately localize DILs in PCa for targeting of biopsy, radiotherapy, and focal ablative therapies. Short-duration dynamic [18F]DCFPyL PET was not inferior to SUVLate in this diagnostic task. CLINICAL TRIAL REGISTRATION NUMBER: NCT04009174 (ClinicalTrials.gov).

Technical Note: Volumetric computed tomography for radiotherapy simulation and treatment planning.

PURPOSE: For lung and liver tumors requiring radiotherapy, motion artifacts are common in 4D-CT images due to the small axial field-of-view (aFOV) of conventional CT scanners. This may negatively impact contouring and dose calculation accuracy and could lead to a geographic miss during treatment. Recent advancements in volumetric CT (vCT) enable an aFOV up to 160 mm in a single rotation, which may reduce motion artifacts. However, the impact of large aFOV on CT number required for dose calculation needs to be evaluated before clinical implementation. The objective of this study was to determine the utility of a 256-slice vCT scanner for 4D-CT simulation by evaluating image quality and generating relative electron density (RED) curves. METHODS: Images were acquired on a 256-slice GE Revolution CT scanner with 40 mm, 80 mm, 120 mm, 140 mm, and 160 mm aFOV. Image quality was assessed by evaluating CT number linearity, uniformity, noise, and low-contrast resolution. The relationship between each quality metric and aFOV was assessed. RESULTS: CT number linearity, uniformity, noise, and low-contrast resolution were within the expected range for each image set, except CT number in Teflon and Delrin, which were underestimated. Spearman correlation coefficient (ρ) showed that the CT number for Teflon (ρ = 1.0, p = 0.02), Delrin (ρ = 1.0, p = 0.02), and air (ρ = 1.0, p = 0.02) was significantly related to aFOV, while all other measurements were not. The measured deviations from expected values were not clinically significant. CONCLUSION: These results suggest that vCT can be used for CT simulation for radiation treatment planning.

Multimodality In Vivo Imaging of Perfusion and Glycolysis in a Rat Model of C6 Glioma.

PURPOSE: Chemical exchange saturation transfer MRI using an infusion of glucose (glucoCEST) is sensitive to the distribution of glucose in vivo; however, whether glucoCEST is more related to perfusion or glycolysis is still debatable. We compared glucoCEST to computed tomography perfusion (CTP), [18F] fluorodeoxyglucose positron emission tomography (FDG-PET), and hyperpolarized [1-13C] pyruvate magnetic resonance spectroscopy imaging (MRSI) in a C6 rat model of glioma to determine if glucoCEST is more strongly correlated with measurements of perfusion or glycolysis. METHODS: 106 C6 glioma cells were implanted in Wistar rat brains (n = 11). CTP (including blood volume, BV; blood flow, BF; and permeability surface area product, PS) and FDG-PET standardized uptake value (SUV) were acquired at 11 to 13 days post-surgery. GlucoCEST measurements (∆CEST) were acquired the following day on a 9.4 T MRI before and after an infusion of glucose solution. This was followed by MRSI on a 3.0 T MRI after the injection of hyperpolarized [1-13C] pyruvate to generate regional maps of the lactate:pyruvate ratio (Lac:Pyr). Pearson's correlations between glucoCEST, CTP, FDG-PET, and Lac:Pyr ratio were evaluated. RESULTS: Tumors had significantly higher SUV, BV, and PS than the contralateral brain. Tumor ∆CEST was most strongly correlated with CTP measurements of BV (ρ = 0.74, P = 0.01) and PS (ρ = 0.55, P = 0.04). No significant correlation was found between glycolysis measurements of SUV or Lac:Pyr with tumor ∆CEST. PS significantly correlated with SUV (ρ = 0.58, P = 0.005) and Lac:Pyr (ρ = 0.75, P = 0.005). BV significantly correlated with Lac:Pyr (ρ = 0.57, P = 0.02), and BF significantly correlated with SUV (ρ = 0.49, P = 0.02). CONCLUSION: This study determined that glucoCEST is more strongly correlated to measurements of perfusion than glycolysis. GlucoCEST measurements have additional confounds, such as sensitivity to changing pH, that merit additional investigation.

In-vivo lung biomechanical modeling for effective tumor motion tracking in external beam radiation therapy.

Lung cancer is the most common cause of cancer-related death in both men and women. Radiation therapy is widely used for lung cancer treatment; however, respiratory motion presents challenges that can compromise the accuracy and/or effectiveness of radiation treatment. Respiratory motion compensation using biomechanical modeling is a common approach used to address this challenge. This study focuses on the development and validation of a lung biomechanical model that can accurately estimate the motion and deformation of lung tumor. Towards this goal, treatment planning 4D-CT images of lung cancer patients were processed to develop patient-specific finite element (FE) models of the lung to predict the patients' tumor motion/deformation. The tumor motion/deformation was modeled for a full respiration cycle, as captured by the 4D-CT scans. Parameters driving the lung and tumor deformation model were found through an inverse problem formulation. The CT datasets pertaining to the inhalation phases of respiration were used for validating the model's accuracy. The volumetric Dice similarity coefficient between the actual and simulated gross tumor volumes (GTVs) of the patients calculated across respiration phases was found to range between 0.80 ± 0.03 and 0.92 ± 0.01. The average error in estimating tumor's center of mass calculated across respiration phases ranged between 0.50 ± 0.10 (mm) and 1.04 ± 0.57 (mm), indicating a reasonably good accuracy of the proposed model. The proposed model demonstrates favorable accuracy for estimating the lung tumor motion/deformation, and therefore can potentially be used in radiation therapy applications for respiratory motion compensation.

Predicting pathological complete response (pCR) after stereotactic ablative radiation therapy (SABR) of lung cancer using quantitative dynamic [18F]FDG PET and CT perfusion: a prospective exploratory clinical study.

BACKGROUND: Stereotactic ablative radiation therapy (SABR) is effective in treating inoperable stage I non-small cell lung cancer (NSCLC), but imaging assessment of response after SABR is difficult. This prospective study aimed to develop a predictive model for true pathologic complete response (pCR) to SABR using imaging-based biomarkers from dynamic [18F]FDG-PET and CT Perfusion (CTP). METHODS: Twenty-six patients with early-stage NSCLC treated with SABR followed by surgical resection were included, as a pre-specified secondary analysis of a larger study. Dynamic [18F]FDG-PET and CTP were performed pre-SABR and 8-week post. Dynamic [18F]FDG-PET provided maximum and mean standardized uptake value (SUV) and kinetic parameters estimated using a previously developed flow-modified two-tissue compartment model while CTP measured blood flow, blood volume and vessel permeability surface product. Recursive partitioning analysis (RPA) was used to establish a predictive model with the measured PET and CTP imaging biomarkers for predicting pCR. The model was compared to current RECIST (Response Evaluation Criteria in Solid Tumours version 1.1) and PERCIST (PET Response Criteria in Solid Tumours version 1.0) criteria. RESULTS: RPA identified three response groups based on tumour blood volume before SABR (BVpre-SABR) and change in SUVmax (ΔSUVmax), the thresholds being BVpre-SABR = 9.3 mL/100 g and ΔSUVmax = - 48.9%. The highest true pCR rate of 92% was observed in the group with BVpre-SABR < 9.3 mL/100 g and ΔSUVmax < - 48.9% after SABR while the worst was observed in the group with BVpre-SABR ≥ 9.3 mL/100 g (0%). RPA model achieved excellent pCR prediction (Concordance: 0.92; P = 0.03). RECIST and PERCIST showed poor pCR prediction (Concordance: 0.54 and 0.58, respectively). CONCLUSIONS: In this study, we developed a predictive model based on dynamic [18F]FDG-PET and CT Perfusion imaging that was significantly better than RECIST and PERCIST criteria to predict pCR of NSCLC to SABR. The model used BVpre-SABR and ΔSUVmax which correlates to tumour microvessel density and cell proliferation, respectively and warrants validation with larger sample size studies. TRIAL REGISTRATION: MISSILE-NSCLC, NCT02136355 (ClinicalTrials.gov). Registered May 8, 2014, https://clinicaltrials.gov/ct2/show/NCT02136355.

Kinetic analysis of dominant intraprostatic lesion of prostate cancer using quantitative dynamic [18F]DCFPyL-PET: comparison to [18F]fluorocholine-PET.

PURPOSE: Identification of the dominant intraprostatic lesion(s) (DILs) can facilitate diagnosis and treatment by targeting biologically significant intra-prostatic foci. A PSMA ligand, [18F]DCFPyL (2-(3-{1-carboxy-5-[(6-[18F]fluoro-pyridine-3-carbonyl)-amino]-pentyl}-ureido)-pentanedioic acid), is better than choline-based [18F]FCH (fluorocholine) in detecting and localizing DIL because of higher tumour contrast, particularly when imaging is delayed to 1 h post-injection. The goal of this study was to investigate whether the different imaging performance of [18F]FCH and [18F]DCFPyL can be explained by their kinetic behaviour in prostate cancer (PCa) and to evaluate whether DIL can be accurately detected and localized using a short duration dynamic positron emission tomography (PET). METHODS: 19 and 23 PCa patients were evaluated with dynamic [18F]DCFPyL and [18F]FCH PET, respectively. The dynamic imaging protocol with each tracer had a total imaging time of 22 min and consisted of multiple frames with acquisition times from 10 to 180 s. Tumour and benign tissue regions identified by sextant biopsy were compared using standardized uptake value (SUV) and tracer kinetic parameters from kinetic analysis of time-activity curves. RESULTS: For [18F]DCFPyL, logistic regression identified Ki and k4 as the optimal model to discriminate tumour from benign tissue (84.2% sensitivity and 94.7% specificity), while only SUV was predictive for [18F]FCH (82.6% sensitivity and 87.0% specificity). The higher k3 (binding) of [18F]FCH than [18F]DCFPyL explains why [18F]FCH SUV can differentiate tumour from benign tissue within minutes of injection. Superior [18F]DCFPyL tumour contrast was due to the higher k4/k3 (more rapid washout) in benign tissue compared to tumour tissue. CONCLUSIONS: DIL was detected with good sensitivity and specificity using 22-min dynamic [18F]DCFPyL PET and avoids the need for delayed post-injection imaging timepoints. The dissimilar in vivo kinetic behaviour of [18F]DCFPyL and [18F]FCH could explain their different SUV images. Clinical Trial Registration NCT04009174 (ClinicalTrials.gov).

Plasma radio-metabolite analysis of PET tracers for dynamic PET imaging: TLC and autoradiography.

BACKGROUND: In molecular imaging with dynamic PET, the binding and dissociation of a targeted tracer is characterized by kinetics modeling which requires the arterial concentration of the tracer to be measured accurately. Once in the body the radiolabeled parent tracer may be subjected to hydrolysis, demethylation/dealkylation and other biochemical processes, resulting in the production and accumulation of different metabolites in blood which can be labeled with the same PET radionuclide as the parent. Since these radio-metabolites cannot be distinguished by PET scanning from the parent tracer, their contribution to the arterial concentration curve has to be removed for the accurate estimation of kinetic parameters from kinetic analysis of dynamic PET. High-performance liquid chromatography has been used to separate and measure radio-metabolites in blood plasma; however, the method is labor intensive and remains a challenge to implement for each individual patient. The purpose of this study is to develop an alternate technique based on thin layer chromatography (TLC) and a sensitive commercial autoradiography system (Beaver, Ai4R, Nantes, France) to measure radio-metabolites in blood plasma of two targeted tracers-[18F]FAZA and [18F]FEPPA, for imaging hypoxia and inflammation, respectively. RESULTS: Radioactivity as low as 17 Bq in 2 µL of pig's plasma can be detected on the TLC plate using autoradiography. Peaks corresponding to the parent tracer and radio-metabolites could be distinguished in the line profile through each sample (n = 8) in the autoradiographic image. Significant intersubject and intra-subject variability in radio-metabolites production could be observed with both tracers. For [18F]FEPPA, 50% of plasma activity was from radio-metabolites as early as 5-min post injection, while for [18F]FAZA, significant metabolites did not appear until 50-min post. Simulation study investigating the effect of radio-metabolite in the estimation of kinetic parameters indicated that 32-400% parameter error can result without radio-metabolites correction. CONCLUSION: TLC coupled with autoradiography is a good alternative to high-performance liquid chromatography for radio-metabolite correction. The advantages of requiring only small blood samples (~ 100 µL) and of analyzing multiple samples simultaneously, make the method suitable for individual dynamic PET studies.

COMP Report: A survey of radiation safety regulations for medical imaging x-ray equipment in Canada.

X-ray regulations and room design methodology vary widely across Canada. The Canadian Organization of Medical Physicists (COMP) conducted a survey in 2016/2017 to provide a useful snapshot of existing variations in rules and methodologies for human patient medical imaging facilities. Some jurisdictions no longer have radiation safety regulatory requirements and COMP is concerned that lack of regulatory oversight might erode safe practices. Harmonized standards will facilitate oversight that will ensure continued attention is given to public safety and to control workplace exposure. COMP encourages all Canadian jurisdictions to adopt the dose limits and constraints outlined in Health Canada Safety Code 35 with the codicil that the design standards be updated to those outlined in NCRP 147 and BIR 2012.

A prospective feasibility study evaluating the role of multimodality imaging and liquid biopsy for response assessment in locally advanced rectal carcinoma.

PURPOSE: Colorectal cancer is a commonly encountered disease that poses several diagnostic and therapeutic challenges. The inherent heterogeneity of tumor biology and propensity to relapse despite "curative" resection pose significant challenges with regard to response assessment. Although MR imaging already plays a key role in primary staging of patients with rectal carcinoma, its reliability in restaging after neoadjuvant therapy is debatable (Van der broek et al. in Dis Colon Rectum 60(3):274-283, 2017). Therefore, there is significant interest in developing additional methods which may improve diagnostic accuracy. This study aims to evaluate the role of multimodality imaging and liquid biopsy in therapeutic response assessment. METHODS: Seventeen patients were enrolled into the study over a span of 24 months. All underwent hybrid PET-MRI and CT-perfusion (CT-P), prior to and following neoadjuvant therapy for locally advanced rectal carcinoma. Twelve of the 17 patients also underwent liquid biopsy, which consisted of blood sampling and analysis of circulating tumor cells (CTCs) and extracellular vesicles (EVs), including cell fragments and microparticles (MPs), using the Cell Search System (Menarini Silicon Biosystems). SUV, DWI, and ADC were calculated during PET-MRI, and several parameters were evaluated during CT-perfusion, including average perfusion, blood flow (BF), blood volume (BV), mean transit time (MTT), permeability-surface area product (PS), contrast extraction efficiency (E), and K-trans (K). Changes observed pre- and post-neoadjuvant therapy in each modality were compared to tumor response at histopathology using a modified Ryan tumor regression grading system. RESULTS: Of the 17 patients included in the study, 14 were classified as non-responders, and 3 were classified as responders as determined by the modified Ryan Tumor Regression Grade (TRG) scoring system (Van der broek et al. in Dis Colon Rectum 60(3):274-283, 2017). When combined, blood markers and CT-P parameters (mean transit time (MTT), K-trans, and permeability-surface area product (PS)) produced the strongest models (p < 0.01). PET (SUV measurement) combined with CT-P-derived K-trans produced a marginally significant (p = 0.057) model for predicting response. MRI-derived ADC value did not provide a significant model for response prediction. CONCLUSION: A model of CT-P parameters plus liquid biopsy more accurately predicts tumor response than PET-MRI, CT-P alone, or liquid biopsy alone. These results suggest that in the evaluation of treatment response, liquid biopsy could provide additional information to functional imaging modalities such as CT-P and should therefore be explored further in a trial with larger sample size.

Assessment of tumour response after stereotactic ablative radiation therapy for lung cancer: A prospective quantitative hybrid 18 F-fluorodeoxyglucose-positron emission tomography and CT perfusion study.

INTRODUCTION: Stereotactic ablative radiotherapy (SABR) is a guideline-recommended treatment for inoperable stage I non-small cell lung cancer (NSCLC), but imaging assessment of response after SABR is difficult. The goal of this study was to evaluate imaging-based biomarkers of tumour response using dynamic 18 F-FDG-PET and CT perfusion (CTP). METHODS: Thirty-one patients with early-stage NSCLC participated in this prospective correlative study. Each underwent dynamic 18 F-FDG-PET/CTP studies on a PET/CT scanner pre- and 8 weeks post-SABR. The dynamic 18 F-FDG-PET measured the tumour SUVmax , SUVmean and the following parameters: K1 , k2 , k3 , k4 and Ki , all using the Johnson-Wilson-Lee kinetic model. CTP quantitatively mapped BF, BV, MTT and PS in tumours and measured largest tumour diameter. Since free-breathing was allowed during CTP scanning, non-rigid image registration of CT images was applied to minimize misregistration before generating the CTP functional maps. Differences between pre- and post-SABR imaging-based parameters were compared. RESULTS: Tumour size changed only slightly after SABR (median 26 mm pre-SABR vs. 23 mm post-SABR; P = 0.01). However, dynamic 18 F-FDG-PET and CTP study showed substantial and significant changes in SUVmax , SUVmean , k3 , k4 and Ki . Significant decreases were evident in SUVmax (median 6.1 vs. 2.6; P < 0.001), SUVmean (median 2.5 vs. 1.5; P < 0.001), k3 (relative decrease of 52%; P = 0.002), Ki (relative decrease of 27%; P = 0.03), whereas there was an increase in k4 (+367%; P < 0.001). CONCLUSIONS: Hybrid 18 F-FDG-PET/CTP allowed the response of NSCLC to SABR to be assessed regarding metabolic and functional parameters. Future studies are needed, with correlation with long-term outcomes, to evaluate these findings as potential imaging biomarkers of response.

Computational Assessment of Blood Flow Heterogeneity in Peritoneal Dialysis Patients' Cardiac Ventricles.

Dialysis prolongs life but augments cardiovascular mortality. Imaging data suggests that dialysis increases myocardial blood flow (BF) heterogeneity, but its causes remain poorly understood. A biophysical model of human coronary vasculature was used to explain the imaging observations, and highlight causes of coronary BF heterogeneity. Post-dialysis CT images from patients under control, pharmacological stress (adenosine), therapy (cooled dialysate), and adenosine and cooled dialysate conditions were obtained. The data presented disparate phenotypes. To dissect vascular mechanisms, a 3D human vasculature model based on known experimental coronary morphometry and a space filling algorithm was implemented. Steady state simulations were performed to investigate the effects of altered aortic pressure and blood vessel diameters on myocardial BF heterogeneity. Imaging showed that stress and therapy potentially increased mean and total BF, while reducing heterogeneity. BF histograms of one patient showed multi-modality. Using the model, it was found that total coronary BF increased as coronary perfusion pressure was increased. BF heterogeneity was differentially affected by large or small vessel blocking. BF heterogeneity was found to be inversely related to small blood vessel diameters. Simulation of large artery stenosis indicates that BF became heterogeneous (increase relative dispersion) and gave multi-modal histograms. The total transmural BF as well as transmural BF heterogeneity reduced due to large artery stenosis, generating large patches of very low BF regions downstream. Blocking of arteries at various orders showed that blocking larger arteries results in multi-modal BF histograms and large patches of low BF, whereas smaller artery blocking results in augmented relative dispersion and fractal dimension. Transmural heterogeneity was also affected. Finally, the effects of augmented aortic pressure in the presence of blood vessel blocking shows differential effects on BF heterogeneity as well as transmural BF. Improved aortic blood pressure may improve total BF. Stress and therapy may be effective if they dilate small vessels. A potential cause for the observed complex BF distributions (multi-modal BF histograms) may indicate existing large vessel stenosis. The intuitive BF heterogeneity methods used can be readily used in clinical studies. Further development of the model and methods will permit personalized assessment of patient BF status.

[18F]-DCFPyL Positron Emission Tomography/Magnetic Resonance Imaging for Localization of Dominant Intraprostatic Foci: First Experience.

An ongoing prospective study is acquiring preoperative imaging data for men with prostate cancer (PCa) using the molecular imaging agent [18F]-DCFPyL targeted against prostate-specific membrane antigen (PSMA). To date, six men (of a planned accrual of 24) with clinically localized, biopsy-proven PCa have undergone preoperative [18F]-DCFPyL positron emission tomography (PET) imaging and multiparametric magnetic resonance imaging acquired using a hybrid PET/MRI system. Lesions identified by [18F]-DCFPyL uptake on PET/MRI were characterized in terms of maximum standardized uptake value (SUVmax) and volume using a boundary threshold of 40% SUVmax. Following surgery, all prostatectomy specimens were processed using a whole-mount technique for accurate deformable co-registration and correlation with PCa foci defined on digitized pathology images. Well-defined intraprostatic dominant lesions were identified by [18F]-DCFPyL PET/MRI (mean SUVmax 11.4±8.25; mean volume 2.2±2.4cm3) in all six men. Co-registered digitized whole-mount pathology for the first case revealed that intense [18F]-DCFPyL uptake (SUVmax 27±1.1cm3) and multiparametric MRI changes (Prostate Imaging Reporting and Data System score of 4) were highly correlated with a 0.5-cm3 dominant (largest) lesion with Gleason pattern 4 PCa in the right mid peripheral zone. A smaller focus (0.01cm3) of lower-grade PCa (Gleason pattern 3) had much lower uptake (SUV 2.7). These early prospective data show that dominant intraprostatic lesions could be identified in all six men using [18F]-DCFPyL as an imaging probe. Trial accrual will continue to quantify in terms of spatial concordance the ability of [18F]-DCFPyL to identify the location and characterize the grade of intraprostatic cancer foci in clinically localized PCa. PATIENT SUMMARY: Positron emission tomography using a novel probe called [18F]-DCFPyL directed against the prostate-specific membrane antigen protein was able to identify locations of prostate cancer in the prostate glands of men undergoing imaging before surgery. In the future, such imaging may allow better targeting of treatment to the portion of the prostate containing the most aggressive components of cancer rather than treating the whole prostate in a uniform fashion.

A generalized parametric response mapping method for analysis of multi-parametric imaging: A feasibility study with application to glioblastoma.

PURPOSE: Parametric response map (PRM) analysis of functional imaging has been shown to be an effective tool for early prediction of cancer treatment outcomes and may also be well-suited toward guiding personalized adaptive radiotherapy (RT) strategies such as sub-volume boosting. However, the PRM method was primarily designed for analysis of longitudinally acquired pairs of single-parameter image data. The purpose of this study was to demonstrate the feasibility of a generalized parametric response map analysis framework, which enables analysis of multi-parametric data while maintaining the key advantages of the original PRM method. METHODS: MRI-derived apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps acquired at 1 and 3-months post-RT for 19 patients with high-grade glioma were used to demonstrate the algorithm. Images were first co-registered and then standardized using normal tissue image intensity values. Tumor voxels were then plotted in a four-dimensional Cartesian space with coordinate values equal to a voxel's image intensity in each of the image volumes and an origin defined as the multi-parametric mean of normal tissue image intensity values. Voxel positions were orthogonally projected onto a line defined by the origin and a pre-determined response vector. The voxels are subsequently classified as positive, negative or nil, according to whether projected positions along the response vector exceeded a threshold distance from the origin. The response vector was selected by identifying the direction in which the standard deviation of tumor image intensity values was maximally different between responding and non-responding patients within a training dataset. Voxel classifications were visualized via familiar three-class response maps and then the fraction of tumor voxels associated with each of the classes was investigated for predictive utility analogous to the original PRM method. Independent PRM and MPRM analyses of the contrast-enhancing lesion (CEL) and a 1 cm shell of surrounding peri-tumoral tissue were performed. Prediction using tumor volume metrics was also investigated. Leave-one-out cross validation (LOOCV) was used in combination with permutation testing to assess preliminary predictive efficacy and estimate statistically robust P-values. The predictive endpoint was overall survival (OS) greater than or equal to the median OS of 18.2 months. RESULTS: Single-parameter PRM and multi-parametric response maps (MPRMs) were generated for each patient and used to predict OS via the LOOCV. Tumor volume metrics (P ≥ 0.071 ± 0.01) and single-parameter PRM analyses (P ≥ 0.170 ± 0.01) were not found to be predictive of OS within this study. MPRM analysis of the peri-tumoral region but not the CEL was found to be predictive of OS with a classification sensitivity, specificity and accuracy of 80%, 100%, and 89%, respectively (P = 0.001 ± 0.01). CONCLUSIONS: The feasibility of a generalized MPRM analysis framework was demonstrated with improved prediction of overall survival compared to the original single-parameter method when applied to a glioblastoma dataset. The proposed algorithm takes the spatial heterogeneity in multi-parametric response into consideration and enables visualization. MPRM analysis of peri-tumoral regions was shown to have predictive potential supporting further investigation of a larger glioblastoma dataset.