Practical Tools for Patient-specific Characterization and Dosimetry of Radiopharmaceutical Extravasation.

ABSTRACT: Extravasation during radiopharmaceutical injection may occur with a frequency of more than 10%. In these cases, radioactivity remains within tissue and deposits unintended radiation dose. Characterization of extravasations is a necessary step in accurate dosimetry, but a lack of free and publicly available tools hampers routine standardized analysis. Our objective was to improve existing extravasation characterization and dosimetry methods and to create and validate tools to facilitate standardized practical dosimetric analysis in clinical settings. Using Monte Carlo simulations, we calculated dosimetric values for sixteen nuclear medicine isotopes: 11 C, 64 Cu, 18 F, 67 Ga, 68 Ga, 123 I, 131 I, 111 In, 177 Lu, 13 N, 15 O, 82 Rb, 153 Sm, 89 Sr, 99m Tc, and 90 Y. We validated our simulation results against five logical alternative dose assessment methods. We then created three new characterization tools: a worksheet, a spreadsheet, and a web application. We assessed each tool by recalculating extravasation dosimetry results found in the literature and used each of the tools for patient cases to show clinical practicality. Average variation between our simulation results and alternative methods was 3.1%. Recalculation of published dosimetry results indicated an average error of 7.9%. Time required to use each characterization tool ranged from 1 to 5 min, and agreement between the three tools was favorable. We improved upon existing methods by creating new tools for characterization and dosimetry of radiopharmaceutical extravasation. These free and publicly available tools will enable standardized routine clinical analysis and benefit patient care, clinical follow-up, documentation, and event reporting.

Development of a classifier for [18F]fluorodeoxyglucose extravasation severity using semi-quantitative readings from topically applied detectors.

BACKGROUND: Radiotracer extravasations, caused largely by faulty tracer injections, can occur in up to 23% of 18F-fluorodeoxyglucose (FDG) PET/CT scans and negatively impact radiological review and tracer quantification. Conventional radiological assessment of extravasation severity on PET has limited performance (e.g., extravasations frequently resolve before scanning) and practical drawbacks. In this study, we develop a new topical detector-based FDG extravasation severity classifier, calibrated from semi-quantitative PET measurements, and assess its performance on human subjects. METHODS: A retrospective study examined patients whose FDG injections had been monitored as part of their standard workup for PET/CT imaging. Topical uncollimated gamma ray detectors were applied proximal to the injection site and on the same location on the opposing arm, and readings were acquired continuously during radiotracer uptake. Patients were imaged with their arms in the PET field of view and total extravasation activity quantified from static PET images through a volume of interest approach. The image-derived activities were considered ground truth and used to calibrate and assess quantification of topical detector readings extrapolated to the start of PET imaging. The classifier utilizes the calibrated detector readings to produce four extravasation severity classes: none, minor, moderate, and severe. In a blinded study, a radiologist qualitatively labeled PET images for extravasation severity using the same classifications. The radiologist's interpretations and topical detector classifications were compared to the ground truth PET results. RESULTS: Linear regression of log-transformed image-derived versus topical detector tracer extravasation activity estimates showed a strong correlation (R2 = 0.75). A total of 24 subject scans were cross-validated with the quantitatively based classifier through a leave-one-out methodology. For binary classification (none vs. extravasated), the topical detector classifier had the highest overall diagnostic performance for identifying extravasations. Specificity, sensitivity, accuracy, and positive predictive value were 100.0%, 80.0%, 95.8%, and 100.0%, respectively, for the topical detector classifier and 31.6%, 100.0%, 45.8%, and 27.8%, respectively, for the radiological analysis. The topical detector classifier, with an optimal detection threshold, produced a significantly higher Matthews correlation coefficient (MCC) than the radiological analysis (0.87 vs. 0.30). CONCLUSIONS: The topical detector binary classifier, calibrated using quantitative static PET measurements, significantly improves extravasation detection compared to qualitative image analysis.

Patient-specific Extravasation Dosimetry Using Uptake Probe Measurements.

ABSTRACT: Extravasation is a common problem in radiopharmaceutical administration and can result in significant radiation dose to underlying tissue and skin. The resulting radiation effects are rarely studied and should be more fully evaluated to guide patient care and meet regulatory obligations. The purpose of this work was to show that a dedicated radiopharmaceutical injection monitoring system can help clinicians characterize extravasations for calculating tissue and skin doses. We employed a commercially available radiopharmaceutical injection monitoring system to identify suspected extravasation of 18F-fluorodeoxyglucose and 99mTc-methylene diphosphonate in 26 patients and to characterize their rates of biological clearance. We calculated the self-dose to infiltrated tissue using Monte Carlo simulation and standard MIRD dosimetry methods, and we used VARSKIN software to calculate the shallow dose equivalent to the epithelial basal-cell layer of overlying skin. For 26 patients, injection-site count rate data were used to characterize extravasation clearance. For each, the absorbed dose was calculated using representative tissue geometries. Resulting tissue-absorbed doses ranged from 0.6 to 11.2 Gy, and the shallow dose equivalent to a 10 cm2 area of adjacent skin in these patients ranged from about 0.1 to 5.4 Sv. Extravasated injections of radiopharmaceuticals can result in unintentional doses that exceed well-established radiation protection and regulatory limits; they should be identified and characterized. An external injection monitoring system may help to promptly identify and characterize extravasations and improve dosimetry calculations. Patient-specific characterization can help clinicians determine extravasation severity and whether the patient should be followed for adverse tissue reactions that may present later in time.

The Scientific and Clinical Case for Reviewing Diagnostic Radiopharmaceutical Extravasation Long-Standing Assumptions.

Background: The patient benefit from a diagnostic nuclear medicine procedure far outweighs the associated radiation risk. This benefit/risk ratio assumes a properly administered radiopharmaceutical. However, a significant diagnostic radiopharmaceutical extravasation can confound the procedure in many ways. We identified three current extravasation hypotheses espoused by medical societies, advisory committees, and hundreds of individual members of the nuclear medicine community: diagnostic extravasations do not cause harm, do not result in high absorbed dose to tissue, and require complex dosimetry methods that are not readily available in nuclear medicine centers. We tested these hypotheses against a framework of current knowledge, recent developments, and original research. We conducted a literature review, searched regulatory databases, examined five clinical cases of extravasated patients, and performed dosimetry on those extravasations to test these globally accepted hypotheses. Results: A literature review found 58 peer-reviewed documents suggesting patient harm. Adverse event/vigilance report database reviews for extravasations were conducted and revealed 38 adverse events which listed diagnostic radiopharmaceutical extravasation as a factor, despite a regulatory exemption for required reporting. In our own case material, assessment of care was evaluated for five extravasated patients who underwent repeat imaging. Findings reflected results of literature review and included mis- or non-identification of lesions, underestimation of Standardized Uptake Values (SUVs) by 19-73%, classification of scans as non-diagnostic, and the need to repeat imaging with the associated additional radiation exposure, inconvenience, or delays in care. Dosimetry was performed for the same five cases of diagnostic radiopharmaceutical extravasation. Absorbed doses to 5 cm3 of tissue were between 1.1 and 8.7 Gy, and shallow dose equivalent for 10 cm2 of skin was as high as 4.2 Sv. Conclusions: Our findings suggest that significant extravasations can or have caused patient harm and can irradiate patients' tissue with doses that exceed medical event reporting limits and deterministic effect thresholds. Therefore, diagnostic radiopharmaceutical injections should be monitored, and dosimetry of extravasated tissue should be performed in certain cases where thresholds are thought to have been exceeded. Process improvement efforts should be implemented to reduce the frequency of extravasation in nuclear medicine.

Technical Note: Characterization of technology to detect residual injection site radioactivity.

PURPOSE: Each year in the United States, approximately 18.5 million nuclear medicine procedures are performed. Various quality control measures are implemented to reduce image errors and improve quantification of radiotracer distribution. However, there is currently no routine or timely feedback about the quality of the radiotracer injection. One potential solution to evaluate the injection quality is to place a topical scintillation sensor near the injection site to record the presence of residual activity. This work investigates a sensor design for identification of injections where the prescribed radioactive activity is not fully delivered into the patient's circulation (an infiltration). METHODS: The sensor consists of a single unshielded bismuth germanate (BGO) crystal (3 mm × 3 mm × 3 mm). Using radioactive sources with gamma energies that span the range commonly used in nuclear medicine, we quantified energy resolution and linearity. Additionally, we computed sensitivity by comparing the calculated incident activity to the activity measured by the sensor. Sensor output linearity was calculated by comparing measured data against the radioactive decay of a source over multiple half-lives. The sensor incorporates internal temperature feedback used to compensate for ambient temperature fluctuations. We investigated the performance of this compensation over the range of 15°C-35°C. RESULTS: Energy spectra from four sensors were used to calculate the energy resolution: 67% for 99m Tc (141 keV), 67% for 133 Ba (344 keV), 42% for 18 F (511 keV), and 32% for 137 Cs (662 keV). Note that the energy used for 133 Ba is a weighted average of the three photon emissions nearest to the most abundant (356 keV). Sensor energy response was linear with a difference of 1%-2% between measured and predicted values. Energy-dependent detector sensitivity, defined as the ratio of measured photons to incident photons for a given isotope, decreased with increasing photon energy from 55.4% for 99m Tc (141 keV) to 3.3% for 137 Cs (662 keV). Without compensation, error due to temperature change was as high as 53%. Temperature compensation reduced the error to less than 1.4%. Sensor output linearity was tested to as high as 210 kcps and the maximum magnitude error was 4%. CONCLUSIONS: The performance of the sensor was adequate for identification of excessive residual activity at an injection site. Its ability to provide feedback may be useful as a quality control measure for nuclear medicine injections.

Practical Clinical Measurement of Radiotracer Concentration in Blood: Initial Device Concept and Feasibility Testing.

Kinetic analysis of PET data requires continuous measurement of radioactivity in the arterial blood throughout the acquisition time, termed the arterial input function. The arterial input function is used as an input to compartmental modeling, which can be a better predictor of disease progression than SUV measurements from static PET images. Current common methods of measuring blood concentrations include image-derived, population-based, and manual sampling. These all have challenges due to logistical and technologic issues, as well as patient burden. The aim of this study was to design, develop, and assess a device that is practical and effective for the routine measurement of ß-emitting radiotracer concentration in blood without the drawbacks of current methods and for which metabolite analysis is not required. Methods: Designs that integrated a scintillating fiber and a silicon photomultiplier with a general-purpose venous access catheter for in vivo measurement were considered. Other design requirements included miniaturization, high sampling rates, and stopping power for ß-particles. Preliminary prototypes were designed to test the feasibility of the concept. Phantom tests were developed to mimic human vasculature. Tests of linearity, sensitivity, signal-to-noise ratios, the impact of vein diameter, and the influence of γ-radiation were conducted. Results: Prototype sensors were constructed using 2 different diameters of polystyrene-based scintillating fibers. Fibers were custom-polished and fixed to a silicon photomultiplier. Sensor output was linear, with R 2 = 0.999 over the range from 0.037 to 9.25 MBq/mL. Absolute sensitivity was approximately 450 counts per second per MBq/mL. Measured signal-to-noise ratios ranged from 1.2:1 to 3.2:1 using a blood-to-tissue concentration ratio of 1:1. Sensor output increased with vein diameter and showed no sensitivity to γ-radiation. Conclusion: In experiments with phantom models, the prototype provided accurate measurements of ß-emitting radiotracer concentration. The design will be refined for in vivo testing. The ability to routinely gather blood input function data would facilitate the adoption of kinetic modeling of PET data.