Low cost, high temporal resolution optical fiber-based γ-photon sensor for real-time pre-clinical evaluation of cancer-targeting radiopharmaceuticals.

Cancer radiopharmaceutical therapies (RPTs) have demonstrated great promise in the treatment of neuroendocrine and prostate cancer, giving hope to late-stage metastatic cancer patients with currently very few treatment options. These therapies have sparked a large amount of interest in pre-clinical research due to their ability to target metastatic disease, with many research efforts focused towards developing and evaluating targeted RPTs for different cancer types in in vivo models. Here we describe a method for monitoring real-time in vivo binding kinetics for the pre-clinical evaluation of cancer RPTs. Recognizing the significant heterogeneity in biodistribution of RPTs among even genetically identical animal models, this approach offers long-term monitoring of the same in vivo organism without euthanasia in contrast to ex vivo tissue dosimetry, while providing high temporal resolution with a low-cost, easily assembled platform, that is not present in small-animal SPECT/CTs. The method utilizes the developed optical fiber-based γ-photon biosensor, characterized to have a wide linear dynamic range with Lutetium-177 (177Lu) activity (0.5-500 µCi/mL), a common radioisotope used in cancer RPT. The probe's ability to track in vivo uptake relative to SPECT/CT and ex vivo dosimetry techniques was verified by administering 177Lu-PSMA-617 to mouse models bearing human prostate cancer tumors (PC3-PIP, PC3-flu). With this method for monitoring RPT uptake, it is possible to evaluate changes in tissue uptake at temporal resolutions <1 min to determine RPT biodistribution in pre-clinical models and better understand dose relationships with tumor ablation, toxicity, and recurrence when attempting to move therapies towards clinical trial validation.

A feasibility study for quantitative assessment of cerebrovascular malformations using flutriciclamide ([18F]GE-180) PET/MRI.

Aim: Neuroinflammation plays a key role in both the pathogenesis and the progression of cerebral cavernous malformations (CCM). Flutriciclamide ([18F]GE-180) is a translocator protein (TSPO) targeting positron emission tomography (PET) tracer, developed for imaging neuroinflammation. The objectives of this study were to describe characteristics of flutriciclamide uptake in different brain tissue regions in CCM patients compared to controls, and to evaluate flutriciclamide uptake and iron deposition within CCM lesions. Materials and methods: Five patients with CCM and six controls underwent a 60 or 90 min continuous PET/MRI scan following 315 ± 68.9 MBq flutriciclamide administration. Standardized uptake value (SUV) and standardized uptake value ratio (SUVr) were obtained using the striatum as a pseudo-reference. Quantitative susceptibility maps (QSM) were used to define the location of the vascular malformation and calculate the amount of iron deposition in each lesion. Results: Increased flutriciclamide uptake was observed in all CCM lesions. The temporal pole demonstrated the highest radiotracer uptake; the paracentral lobule, cuneus and hippocampus exhibited moderate uptake; while the striatum had the lowest uptake, with average SUVs of 0.66, 0.55, 0.63, 0.55, and 0.33 for patient with CCM and 0.57, 0.50, 0.48, 0.42, and 0.32 for controls, respectively. Regional SUVr showed similar trends. The average SUV and QSM values in CCM lesions were 0.58 ± 0.23 g/ml and 0.30 ± 0.10 ppm. SUVs and QSM were positively correlated in CCM lesions (r = 0.53, p = 0.03). Conclusion: The distribution of flutriciclamide ([18F]GE-180) in the human brain and CCM lesions demonstrated the potential of this TSPO PET tracer as a marker of neuroinflammation that may be relevant for characterizing CCM disease progression along with QSM.

Quantitative Assessment of Myocardial Ischemia With Positron Emission Tomography.

Recent advances in positron emission tomography (PET) technology and reconstruction techniques have now made quantitative assessment using cardiac PET readily available in most cardiac PET imaging centers. Multiple PET myocardial perfusion imaging (MPI) radiopharmaceuticals are available for quantitative examination of myocardial ischemia, with each having distinct convenience and accuracy profile. Important properties of these radiopharmaceuticals ( 15 O-water, 13 N-ammonia, 82 Rb, 11 C-acetate, and 18 F-flurpiridaz) including radionuclide half-life, mean positron range in tissue, and the relationship between kinetic parameters and myocardial blood flow (MBF) are presented. Absolute quantification of MBF requires PET MPI to be performed with protocols that allow the generation of dynamic multiframes of reconstructed data. Using a tissue compartment model, the rate constant that governs the rate of PET MPI radiopharmaceutical extraction from the blood plasma to myocardial tissue is calculated. Then, this rate constant ( K1 ) is converted to MBF using an established extraction formula for each radiopharmaceutical. As most of the modern PET scanners acquire the data only in list mode, techniques of processing the list-mode data into dynamic multiframes are also reviewed. Finally, the impact of modern PET technologies such as PET/CT, PET/MR, total-body PET, machine learning/deep learning on comprehensive and quantitative assessment of myocardial ischemia is briefly described in this review.

Comparison and calibration of dose delivered by137Cs and x-ray irradiators in mice.

Objective.The Office of Radiological Security, U.S. Department of Energy's National Nuclear Security Administration, is implementing a radiological risk reduction program which seeks to minimize or eliminate the use of high activity radiological sources, including137Cs, by replacing them with non-radioisotopic technologies, such as x-ray irradiators. The main goal of this paper is to evaluate the equivalence of the dose delivered by gamma- and x-ray irradiators in mice using experimental measurements and Monte Carlo simulations. We also propose a novel biophantom as anin situdose calibration method.Approach.We irradiated mouse carcasses and 3D-printed mouse biophantoms in a137Cs irradiator (Mark I-68) and an x-ray irradiator (X-Rad320) at three voltages (160 kVp, 225 kVp and 320 kVp) and measured the delivered radiation dose. A Geant4-based Monte Carlo model was developed and validated to provide a comprehensive picture of gamma- and x-ray irradiation in mice.Main Results.Our Monte Carlo model predicts a uniform dose delivered in soft-tissue for all the explored irradiation programs and in agreement with the absolute dose measurements. Our Monte Carlo model shows an energy-dependent difference between dose in bone and in soft tissue that decreases as photon energy increases. Dose rate depends on irradiator and photon energy. We observed a deviation of the measured dose from the target value of up to -9% for the Mark I-68, and up to 35% for the X-Rad320. The dose measured in the 3D-printed phantoms are equivalent to that in the carcasses within 6% uncertainty.Significance.Our results suggest that 320 kVp irradiation is a good candidate to substitute137Cs irradiation barring a few caveats. There is a significant difference between measured and targeted doses for x-ray irradiation that suggests a strong need forin situcalibration, which can be achieved with 3D-printed mouse biophantoms. A dose correction is necessary for bone doses, which can be provided by a Monte Carlo calculation. Finally, the biological implications of the differences in dose rates and dose per photon for the different irradiation methods should be carefully assessed for each small-animal irradiation experiment.

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition.

Purpose: Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera. Methods: A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated. Results: The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth. Conclusion: The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

Application of a Domain-specific BERT for Detection of Speech Recognition Errors in Radiology Reports.

Purpose: To develop radiology domain-specific bidirectional encoder representations from transformers (BERT) models that can identify speech recognition (SR) errors and suggest corrections in radiology reports. Materials and Methods: A pretrained BERT model, Clinical BioBERT, was further pretrained on a corpus of 114 008 radiology reports between April 2016 and August 2019 that were retrospectively collected from two hospitals. Next, the model was fine-tuned on a training dataset of generated insertion, deletion, and substitution errors, creating Radiology BERT. This model was retrospectively evaluated on an independent dataset of radiology reports with generated errors (n = 18 885) and on unaltered report sentences (n = 2000) and prospectively evaluated on true clinical SR errors (n = 92). Correction Radiology BERT was separately trained to suggest corrections for detected deletion and substitution errors. Area under the receiver operating characteristic curve (AUC) and bootstrapped 95% CIs were calculated for each evaluation dataset. Results: Radiology-specific BERT had AUC values of >.99 (95% CI: >0.99, >0.99), 0.94 (95% CI: 0.93, 0.94), 0.98 (95% CI: 0.98, 0.98), and 0.97 (95% CI: 0.97, 0.97) for detecting insertion, deletion, substitution, and all errors, respectively, on the independently generated test set. Testing on unaltered report impressions revealed a sensitivity of 82% (28 of 34; 95% CI: 70%, 93%) and specificity of 88% (1521 of 1728; 95% CI: 87%, 90%). Testing on prospective SR errors showed an accuracy of 75% (69 of 92; 95% CI: 65%, 83%). Finally, the correct word was the top suggestion for 45.6% (475 of 1041; 95% CI: 42.5%, 49.3%) of errors. Conclusion: Radiology-specific BERT models fine-tuned on generated errors were able to identify SR errors in radiology reports and suggest corrections.Keywords: Computer Applications, Technology Assessment Supplemental material is available for this article. © RSNA, 2022See also the commentary by Abajian and Cheung in this issue.

Prediction of future healthcare expenses of patients from chest radiographs using deep learning: a pilot study.

Our objective was to develop deep learning models with chest radiograph data to predict healthcare costs and classify top-50% spenders. 21,872 frontal chest radiographs were retrospectively collected from 19,524 patients with at least 1-year spending data. Among the patients, 11,003 patients had 3 years of cost data, and 1678 patients had 5 years of cost data. Model performances were measured with area under the receiver operating characteristic curve (ROC-AUC) for classification of top-50% spenders and Spearman ρ for prediction of healthcare cost. The best model predicting 1-year (N = 21,872) expenditure achieved ROC-AUC of 0.806 [95% CI 0.793-0.819] for top-50% spender classification and ρ of 0.561 [0.536-0.586] for regression. Similarly, for predicting 3-year (N = 12,395) expenditure, ROC-AUC of 0.771 [0.750-0.794] and ρ of 0.524 [0.489-0.559]; for predicting 5-year (N = 1779) expenditure ROC-AUC of 0.729 [0.667-0.729] and ρ of 0.424 [0.324-0.529]. Our deep learning model demonstrated the feasibility of predicting health care expenditure as well as classifying top 50% healthcare spenders at 1, 3, and 5 year(s), implying the feasibility of combining deep learning with information-rich imaging data to uncover hidden associations that may allude to physicians. Such a model can be a starting point of making an accurate budget in reimbursement models in healthcare industries.

Assessment of late-term progression of cardiac allograft vasculopathy in patients with orthotopic heart transplantation using quantitative cardiac 82Rb PET.

The risk stratification and long-term survival of patients with orthotopic heart transplantation (OHT) is impacted by the complication of cardiac allograft vasculopathy (CAV). This study evaluates changes in myocardial blood flow (MBF) and myocardial coronary flow reserve (CFR) in a group of long-term OHT patients using quantitative cardiac 82Rb-positron emission tomography (PET). Twenty patients (7 females and 13 males, mean age = 72.7 ± 12.2 years with CAV and 62.9 ± 7.2 years without CAV and post-OHT mean time = 13.9 years), were evaluated retrospectively using dynamic cardiac 82Rb-PET at rest and regadenoson-induced stress. The patients also underwent selective coronary angiography (SCA) for diagnosis and risk stratification. CAV was diagnosed based on SCA findings and maximal intimal thickness greater than 0.5 mm, as defined by International Society of Heart and Lung Transplantation (ISHLT). Global and regional MBFs were estimated in three vascular territories using the standard 1-tissue compartment model for dynamic 82Rb-PET. The myocardial CFR was also calculated as the ratio of peak stress MBF to rest MBF. Among twenty patients, seven had CAV in, at least, one major coronary artery (ISHLT CAV grade 1 or higher) while 13 patients did not have CAV (NonCAV). Mean rate-pressure products (RPP) at rest were significantly elevated in CAV patients compared to those without CAV (P = 0.002) but it was insignificant at stress (P = NS). There was no significant difference in the stress MBFs between CAV and NonCAV patients (P = NS). However, the difference in RPP-normalized stress MBFs was significant (P = 0.045), while RPP-normalized MBFs at rest was not significant (P = NS). Both CFR and RPP-normalized CFR were significantly lower in CAV compared to NonCAV patients (P < 0.001). There were significant correlations between MBFs and RPPs at rest for both CAV (ρ = 0.764, P = 0.047) and NonCAV patients (ρ = 0.641, P = 0.017), while there were no correlations at stress for CAV (ρ = 0.232, P = NS) and NonCAV patients (ρ = 0.068, P = NS). This study indicates that the resting MBF is higher in late-term post-OHT patients. The high resting MBF and reduced CFR suggest an unprecedented demand of blood flow and blunted response to stress due to impaired vasodilatory capacity that is exacerbated by the presence of CAV.

Patient-specific dosimetry using pretherapy [¹²4I]m-iodobenzylguanidine ([¹²4I]mIBG) dynamic PET/CT imaging before [¹³¹I]mIBG targeted radionuclide therapy for neuroblastoma.

PURPOSE: Iodine-131-m-iodobenzylguanidine ([(131)I]mIBG)-targeted radionuclide therapy (TRT) is a standard treatment for recurrent or refractory neuroblastoma with response rates of 30-40 %. The aim of this study is to demonstrate patient-specific dosimetry using quantitative [(124)I]mIBG positron emission tomography/X-ray computed tomography (PET/CT) imaging with a GEometry ANd Tracking 4 (Geant4)-based Monte Carlo method for better treatment planning. PROCEDURES: A Monte Carlo dosimetry method was developed using the Geant4 toolkit with voxelized anatomical geometry and source distribution as input. The presegmented hybrid computational human phantoms developed by the University of Florida and the National Cancer Institute (UF/NCI) were used as a surrogate to characterize the anatomy of a given patient. S values for I-131 were estimated by the phantoms coupled with Geant4 and compared with those estimated by OLINDA|EXM and MCNPX for the newborn model. To obtain patient-specific biodistribution of [(131)I]mIBG, a 10-year-old girl with relapsed neuroblastoma was imaged with [(124)I]mIBG PET/CT at four time points prior to the planned [(131)I]mIBG TRT. The organ- and tumor-absorbed doses of the clinical case were estimated with the Geant4 method using the modified UF/NCI 10-year-old phantom with tumors and the patient-specific residence time. RESULTS: For the newborn model, the Geant4 S values were consistent with the MCNPX S values. The S value ratio of the Geant4 method to OLINDA|EXM ranged from 0.08 to 6.5 of all major organs. The [(131)I]mIBG residence time quantified from the pretherapy [(124)I]mIBG PET/CT imaging of the 10-year-old patient was mostly comparable to those previously reported. Organ-absorbed dose for the salivary glands was 98.0 Gy, heart wall 36.5 Gy, and liver 34.3 Gy, while tumor-absorbed dose ranged from 143.9 to 1,641.3 Gy in different sites. CONCLUSIONS: Patient-specific dosimetry for [(131)I]mIBG TRT was accomplished using pretherapy [(124)I]mIBG PET/CT imaging and a Geant4-based Monte Carlo dosimetry method. The Geant4 method with quantitative pretherapy imaging can provide dose estimates to normal organs and tumors with more realistic simulation geometry, and thus may improve treatment planning for [(131)I]mIBG TRT.

Monitoring and risk assessment of pesticide residues in commercially dried vegetables.

We tested for residual pesticide levels in dried vegetables in Seoul, Korea. A total of 100 samples of 13 different types of agricultural products were analyzed by a gas chromatography-nitrogen phosphate detector (GC-NPD), an electron capture detector (GC-µECD), a mass spectrometry detector (GC-MSD), and a high performance liquid chromatography-ultraviolet detector (HPLC-UV). We used multi-analysis methods to analyze for 253 different pesticide types. Among the selected agricultural products, residual pesticides were detected in 11 samples, of which 2 samples (2.0%) exceeded the Korea Maximum Residue limits (MRLs). We detected pesticide residue in 6 of 9 analyzed dried pepper leaves and 1 sample exceeded the Korea MRLs. Data obtained were then used for estimating the potential health risks associated with the exposures to these pesticides. The estimated daily intakes (EDIs) range from 0.1% of the acceptable daily intake (ADI) for bifenthrin to 8.4% of the ADI for cadusafos. The most critical commodity is cadusafos in chwinamul, contributing 8.4% to the hazard index (HI). This results show that the detected pesticides could not be considered a serious public health problem. Nevertheless, an investigation into continuous monitoring is recommended.

Technological development and advances in single-photon emission computed tomography/computed tomography.

Single-photon emission computed tomography/computed tomography (SPECT/CT) has emerged during the past decade as a means of correlating anatomical information from CT with functional information from SPECT. The integration of SPECT and CT in a single imaging device facilitates anatomical localization of the radiopharmaceutical to differentiate physiological uptake from that associated with disease and patient-specific attenuation correction to improve the visual quality and quantitative accuracy of the SPECT image. The first clinically available SPECT/CT systems performed emission-transmission imaging using a dual-headed SPECT camera and a low-power x-ray CT subsystem. Newer SPECT/CT systems are available with high-power CT subsystems suitable for detailed anatomical diagnosis, including CT coronary angiography and coronary calcification that can be correlated with myocardial perfusion measurements. The high-performance CT capabilities also offer the potential to improve compensation of partial volume errors for more accurate quantitation of radionuclide measurement of myocardial blood flow and other physiological processes and for radiation dosimetry for radionuclide therapy. In addition, new SPECT technologies are being developed that significantly improve the detection efficiency and spatial resolution for radionuclide imaging of small organs including the heart, brain, and breast, and therefore may provide new capabilities for SPECT/CT imaging in these important clinical applications.