ISIT-QA: In Silico Imaging Trial to Evaluate a Low-Count Quantitative SPECT Method Across Multiple Scanner-Collimator Configurations for 223Ra-Based Radiopharmaceutical Therapies.

Personalized dose-based treatment planning requires accurate and reproducible noninvasive measurements to ensure safety and effectiveness. Dose estimation using SPECT is possible but challenging for alpha (α)-particle-emitting radiopharmaceutical therapy (α-RPT) because of complex γ-emission spectra, extremely low counts, and various image-degrading artifacts across a plethora of scanner-collimator configurations. Through the incorporation of physics-based considerations and skipping of the potentially lossy voxel-based reconstruction step, a recently developed projection-domain low-count quantitative SPECT (LC-QSPECT) method has the potential to provide reproducible, accurate, and precise activity concentration and dose measures across multiple scanners, as is typically the case in multicenter settings. To assess this potential, we conducted an in silico imaging trial to evaluate the LC-QSPECT method for a 223Ra-based α-RPT, with the trial recapitulating patient and imaging system variabilities. Methods: A virtual imaging trial titled In Silico Imaging Trial for Quantitation Accuracy (ISIT-QA) was designed with the objectives of evaluating the performance of the LC-QSPECT method across multiple scanner-collimator configurations and comparing performance with a conventional reconstruction-based quantification method. In this trial, we simulated 280 realistic virtual patients with bone-metastatic castration-resistant prostate cancer treated with 223Ra-based α-RPT. The trial was conducted with 9 simulated SPECT scanner-collimator configurations. The primary objective of this trial was to evaluate the reproducibility of dose estimates across multiple scanner-collimator configurations using LC-QSPECT by calculating the intraclass correlation coefficient. Additionally, we compared the reproducibility and evaluated the accuracy of both considered quantification methods across multiple scanner-collimator configurations. Finally, the repeatability of the methods was evaluated in a test-retest study. Results: In this trial, data from 268 223RaCl2 treated virtual prostate cancer patients, with a total of 2,903 lesions, were used to evaluate LC-QSPECT. LC-QSPECT provided dose estimates with good reproducibility across the 9 scanner-collimator configurations (intraclass correlation coefficient > 0.75) and high accuracy (ensemble average values of recovery coefficients ranged from 1.00 to 1.02). Compared with conventional reconstruction-based quantification, LC-QSPECT yielded significantly improved reproducibility across scanner-collimator configurations, accuracy, and test-retest repeatability ([Formula: see text] Conclusion: LC-QSPECT provides reproducible, accurate, and repeatable dose estimations in 223Ra-based α-RPT as evaluated in ISIT-QA. These findings provide a strong impetus for multicenter clinical evaluations of LC-QSPECT in dose quantification for α-RPTs.

A Semiautonomous Deep Learning System to Reduce False-Positive Findings in Screening Mammography.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To evaluate the ability of a semiautonomous artificial intelligence (AI) model to identify screening mammograms not suspicious for breast cancer and reduce the number of false-positive examinations. Materials and Methods The deep learning algorithm was trained using 123,248 2D digital mammograms (6,161 cancers) and a retrospective study was performed on three nonoverlapping datasets of 14,831 screening mammography examinations (1,026 cancers) from 2 US and 1 UK institutions (2008-2017). The standalone performance of humans and AI was compared. Human+AI performance was simulated to examine reductions in the cancer detection rate, number of examinations, false positive callbacks, and benign biopsies. Metrics were adjusted to mimic the natural distribution of a screening population, and bootstrapped confidence intervals (CI) and P values were calculated. Results Retrospective evaluation on all datasets showed minimal changes to the cancer detection rate with use of the AI device (US Dataset 1 P = .02, US Dataset 2 P < .001, UK P < .001, noninferiority margin of 0.25 cancers per 1000 examinations). On US Dataset 1 (11,592 mammograms, 101 cancers, 3810 female patients, mean age 57.3 ± [SD] 10.0 years), the device reduced screening examinations requiring radiologist interpretation by 41.6% [95% CI: 40.6%, 42.4%] (P < .001), diagnostic examinations callbacks by 31.1% [28.7%, 33.4%] (P < .001), and benign needle biopsies by 7.4% [4.1%, 12.4%] (P < .001). US Dataset 2 (1362 mammograms, 330 cancers, 1293 female patients, mean age 55.4 ± 10.5 years) had reductions of 19.5% [16.9%, 22.1%] (P < .001), 11.9% [8.6%, 15.7%] (P< .001), and 6.5% [0.0%, 19.0%] (P = .08), respectively. The UK dataset (1877 mammograms, 595 cancers, 1491 female patients, mean age 63.5 ± 7.1 SD) had reductions of 36.8% [34.4%, 39.7%] (P < .001), 17.1% [5.9%, 30.1%] (P < .001), and 5.9% [2.9%, 11.5%] (P < .001), respectively. Conclusion This work demonstrates the potential of a semiautonomous breast cancer screening system to reduce false positives, unnecessary procedures, patient anxiety, and medical expenses. Published under a CC BY 4.0 license.

Test-Retest Repeatability of Patlak Slopes versus Standardized Uptake Values for Hypermetabolic Lesions and Normal Organs in an Oncologic PET/CT Population.

PURPOSE: We aimed to determine the test-retest repeatability of quantitative metrics based on the Patlak slope (PS) versus the standardized uptake value (SUV) among lesions and normal organs on oncologic [18F]FDG-PET/CT. PROCEDURES: This prospective, single-center study enrolled adults undergoing standard-of-care oncologic [18F]FDG-PET/CTs. Early (35-50 min post-injection) and late (75-90 min post-injection) SUV and PS images were reconstructed from dynamic whole-body PET data. Repeat imaging occurred within 7 days. Relevant quantitative metrics were extracted from lesions and normal organs. Repeatability was assessed via mean test-retest percent changes [T-RT %Δ], within-subject coefficients of variation (wCVs), and intra-class correlation coefficients (ICCs). RESULTS: Nine subjects (mean age, 61.7 ± 6.2 years; 6 females) completed the test-retest protocol. Four subjects collectively had 17 [18F]FDG-avid lesions. Lesion wCVs were higher (i.e., worse repeatability) for PS-early-max (16.2%) and PS-early-peak (15.6%) than for SUV-early-max (8.9%) and SUV-early-peak (8.1%), with similar early metric ICCs (0.95-0.98). Lesion wCVs were similar for PS-late-max (8.5%) and PS-late-peak (6.4%) relative to SUV-late-max (9.7%) and SUV-late-peak (7.2%), with similar late metric ICCs (0.93-0.98). There was a significant bias toward higher retest SUV and PS values in the lesion analysis (T-RT %Δ [95% CI]: SUV-late-max, 10.0% [2.6%, 17.0%]; PS-late-max, 20.4% [14.3%, 26.4%]) but not in the normal organ analysis. CONCLUSIONS: Among [18F]FDG-avid lesions, the repeatability of PS-based metrics is similar to equivalent SUV-based metrics at late post-injection time points, indicating that PS-based metrics may be suitable for tracking response to oncologic therapies. However, further validation is required in light of our study's limitations, including small sample size and bias toward higher retest values for some metrics.

Very-low-density lipoprotein triglyceride and free fatty acid plasma kinetics in women with high or low brown adipose tissue volume and overweight/obesity.

Although a high amount of brown adipose tissue (BAT) is associated with low plasma triglyceride concentration, the mechanism responsible for this relationship in people is not clear. Here, we evaluate the interrelationships among BAT, very-low-density lipoprotein triglyceride (VLDL-TG), and free fatty acid (FFA) plasma kinetics during thermoneutrality in women with overweight/obesity who had a low (<20 mL) or high (≥20 mL) volume of cold-activated BAT (assessed by using positron emission tomography in conjunction with 2-deoxy-2-[18F]-fluoro-glucose). We find that plasma TG and FFA concentrations are lower and VLDL-TG and FFA plasma clearance rates are faster in women with high BAT than low BAT volume, whereas VLDL-TG and FFA appearance rates in plasma are not different between the two groups. These findings demonstrate that women with high BAT volume have lower plasma TG and FFA concentrations than women with low BAT volumes because of increased VLDL-TG and FFA clearance rates. This study was registered at ClinicalTrials.gov (NCT02786251).

Joint regional uptake quantification of Thorium-227 and Radium-223 using a multiple-energy-window projection-domain quantitative SPECT method.

Thorium-227-based alpha-particle radiopharmaceutical therapies ({\alpha}-RPTs) are being investigated in several clinical and pre-clinical studies. After administration, Thorium-227 decays to Radium-223, another alpha-particle-emitting isotope, which redistributes within the patient. Reliable dose quantification of both Thorium-227 and Radium-223 is clinically important, and SPECT may perform this quantification as these isotopes also emit X- and gamma-ray photons. However, reliable quantification is challenged by the orders-of-magnitude lower activity compared to conventional SPECT, resulting in a very low number of detected counts, the presence of multiple photopeaks, substantial overlap in the emission spectra of these isotopes, and the image-degrading effects in SPECT. To address these issues, we propose a multiple-energy-window projection-domain quantification (MEW-PDQ) method that jointly estimates the regional activity uptake of both Thorium-227 and Radium-223 directly using the SPECT projection from multiple energy windows. We evaluated the method with realistic simulation studies using anthropomorphic digital phantoms, in the context of imaging patients with bone metastases of prostate cancer and treated with Thorium-227-based {\alpha}-RPTs. The proposed method yielded reliable (accurate and precise) regional uptake estimates of both isotopes and outperformed state-of-the-art methods across different lesion sizes and contrasts, in a virtual imaging trial, as well as with moderate levels of intra-regional heterogeneous uptake and with moderate inaccuracies in the definitions of the support of various regions. Additionally, we demonstrated the effectiveness of using multiple energy windows and the variance of the estimated uptake using the proposed method approached the Cram\'er-Rao-lower-bound-defined theoretical limit.

Ethical Considerations for Artificial Intelligence in Medical Imaging: Data Collection, Development, and Evaluation.

The development of artificial intelligence (AI) within nuclear imaging involves several ethically fraught components at different stages of the machine learning pipeline, including during data collection, model training and validation, and clinical use. Drawing on the traditional principles of medical and research ethics, and highlighting the need to ensure health justice, the AI task force of the Society of Nuclear Medicine and Molecular Imaging has identified 4 major ethical risks: privacy of data subjects, data quality and model efficacy, fairness toward marginalized populations, and transparency of clinical performance. We provide preliminary recommendations to developers of AI-driven medical devices for mitigating the impact of these risks on patients and populations.

Correlation of SUV on Early Interim PET with Recurrence-Free Survival and Overall Survival in Primary Operable HER2-Positive Breast Cancer (the TBCRC026 Trial).

Predictive biomarkers of response to human epidermal growth factor receptor 2 (HER2)-directed therapy are essential to inform treatment decisions. The TBCRC026 trial reported that early declines in tumor SUVs corrected for lean body mass (SULmax) on 18F-FDG PET/CT predicted a pathologic complete response (pCR) to HER2 therapy with neoadjuvant trastuzumab and pertuzumab (HP) without chemotherapy in estrogen receptor (ER)-negative, HER2-positive breast cancer. We hypothesized that 18F-FDG PET/CT SULmax parameters would predict recurrence-free survival (RFS) and overall survival (OS). Methods: Patients with stage II/III ER-negative, HER2-positive breast cancer received neoadjuvant HP (n = 88). pCR after HP alone was 22% (18/83), additional nonstudy neoadjuvant therapy was administered in 28% (25/88), and the majority received adjuvant therapy per physician discretion. 18F-FDG PET/CT was performed at baseline and at cycle 1, day 15 (C1D15). RFS and OS were summarized using the Kaplan-Meier method and compared between subgroups using logrank tests. Associations between 18F-FDG PET/CT (≥40% decline in SULmax between baseline and C1D15, or C1D15 SULmax ≤ 3) and pCR were evaluated using Cox regressions, where likelihood ratio CIs were reported because of the small numbers of events. Results: Median follow-up was 53.7 mo (83/88 evaluable), with 6 deaths and 14 RFS events. Estimated RFS and OS at 3 y was 84% (95% CI, 76%-92%) and 92% (95% CI, 87%-98%), respectively. A C1D15 SULmax of 3 or less was associated with improved RFS (hazard ratio [HR], 0.36; 95% CI, 0.11-1.05; P = 0.06) and OS (HR, 0.14; 95% CI, 0.01-0.85; P = 0.03), the latter statistically significant. The association of an SULmax decline of at least 40% (achieved in 59%) with RFS and OS did not reach statistical significance. pCR was associated with improved RFS (HR, 0.25; 95% CI, 0.01-1.24; P = 0.10) but did not reach statistical significance. Conclusion: For the first time, we report a potential association between a C1D15 SULmax of 3 or less on 18F-FDG PET/CT and RFS and OS outcomes in patients with ER-negative, HER2-positive breast cancer receiving neoadjuvant HP alone. If confirmed in future studies, this imaging-based biomarker may facilitate early individualization of therapy.

Ethical Considerations for Artificial Intelligence in Medical Imaging: Deployment and Governance.

The deployment of artificial intelligence (AI) has the potential to make nuclear medicine and medical imaging faster, cheaper, and both more effective and more accessible. This is possible, however, only if clinicians and patients feel that these AI medical devices (AIMDs) are trustworthy. Highlighting the need to ensure health justice by fairly distributing benefits and burdens while respecting individual patients' rights, the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging has identified 4 major ethical risks that arise during the deployment of AIMD: autonomy of patients and clinicians, transparency of clinical performance and limitations, fairness toward marginalized populations, and accountability of physicians and developers. We provide preliminary recommendations for governing these ethical risks to realize the promise of AIMD for patients and populations.

Discrepant Assessments of Progressive Disease in Clinical Trials between Routine Clinical Reads and Formal RECIST 1.1 Interpretations.

Purpose To analyze the frequency of discrepant interpretations of progressive disease (PD) between routine clinical and formal Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 interpretations in patients enrolled in solid tumor clinical trials and investigate the causes of discordance. Materials and Methods This retrospective study included patients in solid tumor clinical trials undergoing imaging response assessments based on RECIST 1.1 from January to July 2021. Routine clinical interpretations (RCIs) performed as part of standard workflow and not requiring formal use of any established response criteria were compared with separate local core laboratory interpretations (CLIs) by specially trained radiologists who used software that tracks target lesion measurements, changes in nontarget lesions, and appearance of new lesions longitudinally. The comparison focused on discordant interpretations of PD. Results Among 1053 patients who had both RCIs and CLIs performed, PD was diagnosed on one or both reads in 327 patients (median age, 63.6 [range, 22.4-83.2] years; 57.8% female patients). The RCIs and CLIs agreed with PD status in 65% (213 of 327) of assessments. In 32% (105 of 327) of assessments, RCIs overdiagnosed PD when CLIs diagnosed stable disease, and in 3% (nine of 327), CLIs diagnosed PD when RCIs diagnosed stable disease. Reasons for discrepant RCIs of PD included erroneous target lesion measurements (58%, 61 of 105), erroneous diagnosis of nontarget progression (30%, 32 of 105), and misclassification of new lesions as cancer (11%, 12 of 105). Most patients (93%, 98 of 105) with RCI overdiagnosis of PD remained in the clinical trial for one or more treatment cycles. Conclusion PD was frequently overdiagnosed on RCIs versus formal RECIST 1.1 CLIs which could result in patients removed from the clinical trial inappropriately. Keywords: Oncology, Cancer, Tumor Response, MR Imaging, CT © RSNA, 2023 See also commentary by Margolis and Ruchalski in this issue.

Evaluation of Candidate Theranostics for 227Th/89Zr Paired Radioimmunotherapy of Lymphoma.

227Th is a promising radioisotope for targeted α-particle therapy. It produces 5 α-particles through its decay, with the clinically approved 223Ra as its first daughter. There is an ample supply of 227Th, allowing for clinical use; however, the chemical challenges of chelating this large tetravalent f-block cation are considerable. Using the CD20-targeting antibody ofatumumab, we evaluated chelation of 227Th4+ for α-particle-emitting and radiotheranostic applications. Methods: We compared 4 bifunctional chelators for thorium radiopharmaceutical preparation: S-2-(4-Isothiocyanatobenzyl)-1,4,7,10-tetraazacyclododecane tetraacetic acid (p-SCN-Bn-DOTA), 2-(4-isothicyanatobenzyl)-1,2,7,10,13-hexaazacyclooctadecane-1,4,7,10,13,16-hexaacetic acid (p-SCN-Bn-HEHA), p-isothiacyanatophenyl-1-hydroxy-2-oxopiperidine-desferrioxamine (DFOcyclo*-p-Phe-NCS), and macrocyclic 1,2-HOPO N-hydroxysuccinimide (L804-NHS). Immunoconstructs were evaluated for yield, purity, and stability in vitro and in vivo. Tumor targeting of the lead 227Th-labeled compound in vivo was performed in CD20-expressing models and compared with a companion 89Zr-labeled PET agent. Results: 227Th-labeled ofatumumab-chelator constructs were synthesized to a radiochemical purity of more than 95%, excepting HEHA. 227Th-HEHA-ofatumumab showed moderate in vitro stability. 227Th-DFOcyclo*-ofatumumab presented excellent 227Th labeling efficiency; however, high liver and spleen uptake was revealed in vivo, indicative of aggregation. 227Th-DOTA-ofatumumab labeled poorly, yielding no more than 5%, with low specific activity (0.08 GBq/g) and modest long-term in vitro stability (<80%). 227Th-L804-ofatumumab coordinated 227Th rapidly and efficiently at high yields, purity, and specific activity (8 GBq/g) and demonstrated extended stability. In vivo tumor targeting confirmed the utility of this chelator, and the diagnostic analog, 89Zr-L804-ofatumumab, showed organ distribution matching that of 227Th to delineate SU-DHL-6 tumors. Conclusion: Commercially available and novel chelators for 227Th showed a range of performances. The L804 chelator can be used with potent radiotheranostic capabilities for 89Zr/227Th quantitative imaging and α-particle therapy.

A Projection-Domain Low-Count Quantitative SPECT Method for α-Particle-Emitting Radiopharmaceutical Therapy.

Single-photon emission-computed tomography (SPECT) provides a mechanism to estimate regional isotope uptake in lesions and at-risk organs after administration of α-particle-emitting radiopharmaceutical therapies (α-RPTs). However, this estimation task is challenging due to the complex emission spectra, the very low number of detected counts (~20 times lower than in conventional SPECT), the impact of stray-radiation-related noise at these low counts, and the multiple image-degrading processes in SPECT. The conventional reconstruction-based quantification methods are observed to be erroneous for α-RPT SPECT. To address these challenges, we developed a low-count quantitative SPECT (LC-QSPECT) method that directly estimates the regional activity uptake from the projection data (obviating the reconstruction step), compensates for stray-radiation-related noise, and accounts for the radioisotope and SPECT physics, including the isotope spectra, scatter, attenuation, and collimator-detector response, using a Monte Carlo-based approach. The method was validated in the context of 3-D SPECT with 223Ra, a commonly used radionuclide for α-RPT. Validation was performed using both realistic simulation studies, including a virtual clinical trial, and synthetic and 3-D-printed anthropomorphic physical-phantom studies. Across all studies, the LC-QSPECT method yielded reliable regional-uptake estimates and outperformed the conventional ordered subset expectation-maximization (OSEM)-based reconstruction and geometric transfer matrix (GTM)-based post-reconstruction partial-volume compensation methods. Furthermore, the method yielded reliable uptake across different lesion sizes, contrasts, and different levels of intralesion heterogeneity. Additionally, the variance of the estimated uptake approached the Cramér-Rao bound-defined theoretical limit. In conclusion, the proposed LC-QSPECT method demonstrated the ability to perform reliable quantification for α-RPT SPECT.

Cure of Disseminated Human Lymphoma with [225Ac]Ac-Ofatumumab in a Preclinical Model.

Immunotherapies that target the CD20 protein expressed on most non-Hodgkin lymphoma cells have improved clinical outcomes, but relapse is common. We prepared 225Ac-labeled anti-CD20 ofatumumab and evaluated its in vitro characteristics and therapeutic efficacy in a murine model of disseminated human lymphoma. Methods: 225Ac was chelated by DOTA-ofatumumab, and radiochemical yield, purity, immunoreactivity, stability, and chelate number were determined. In vitro cell killing of CD20-positive, human B-cell lymphoma Raji-Luc cells was assayed. Biodistribution was determined as percentage injected activity per gram (%IA/g) in mice with subcutaneous Raji-cell tumors (n = 4). [225Ac]Ac-ofatumumab biodistribution in C57BL/6N mice was performed to estimate projected human dosimetry. Therapeutic efficacy was tested in mice with systemically disseminated Raji-Luc cells, tracking survival, bioluminescence, and animal weight for a targeted 200 d, with single-dose therapy initiated 8, 12, or 16 d after cell injection, comparing no treatment, ofatumumab, and low (3.7 kBq/mouse) and high (9.25 kBq/mouse) doses of [225Ac]Ac-IgG and [225Ac]Ac-ofatumumab (n = 8-10/cohort). Results: Radiochemical yield and purity were 32% ± 9% and more than 95%, respectively. Specific activity was more than 5 MBq/mg. Immunoreactivity was preserved, and more than 90% of the 225Ac remained chelated after 10 d in serum. Raji-Luc cell killing in vitro was significant, specific, and dose-dependent. In tumor-bearing mice, [225Ac]Ac-ofatumumab displayed low liver (7 %IA/g) and high tumor (28 %IA/g) uptake. Dosimetry estimates indicated that bone marrow is likely the dose-limiting organ. When therapy was initiated 8 d after cell injection, untreated mice and mice treated with cold ofatumumab or low- or high-dose [225Ac]Ac-IgG showed indistinguishable median survivals of 20-24 d, with extensive cancer-cell burden before death. Low- and high-dose [225Ac]Ac-ofatumumab profoundly (P < 0.05) extended median survival to 190 d and more than 200 d (median not determinable), with 5 and 9 of 10 mice, respectively, surviving at study termination with no detectable cancer cells. Surviving mice treated with high-dose [225Ac]Ac-ofatumumab showed reduced weight gain versus naïve mice. When therapy was initiated 12 d, but not 16 d, after cell injection, high-dose [225Ac]Ac-ofatumumab significantly extended median survival to 40 d but was not curative. Conclusion: In an aggressive disseminated tumor model, [225Ac]Ac-ofatumumab was effective at cancer-cell killing and curative when administered 8 d after cell injection. [225Ac]Ac-ofatumumab has substantial potential for clinical translation as a next-generation therapeutic for treatment of patients with non-Hodgkin lymphoma.

Need for objective task-based evaluation of deep learning-based denoising methods: A study in the context of myocardial perfusion SPECT.

BACKGROUND: Artificial intelligence-based methods have generated substantial interest in nuclear medicine. An area of significant interest has been the use of deep-learning (DL)-based approaches for denoising images acquired with lower doses, shorter acquisition times, or both. Objective evaluation of these approaches is essential for clinical application. PURPOSE: DL-based approaches for denoising nuclear-medicine images have typically been evaluated using fidelity-based figures of merit (FoMs) such as root mean squared error (RMSE) and structural similarity index measure (SSIM). However, these images are acquired for clinical tasks and thus should be evaluated based on their performance in these tasks. Our objectives were to: (1) investigate whether evaluation with these FoMs is consistent with objective clinical-task-based evaluation; (2) provide a theoretical analysis for determining the impact of denoising on signal-detection tasks; and (3) demonstrate the utility of virtual imaging trials (VITs) to evaluate DL-based methods. METHODS: A VIT to evaluate a DL-based method for denoising myocardial perfusion SPECT (MPS) images was conducted. To conduct this evaluation study, we followed the recently published best practices for the evaluation of AI algorithms for nuclear medicine (the RELAINCE guidelines). An anthropomorphic patient population modeling clinically relevant variability was simulated. Projection data for this patient population at normal and low-dose count levels (20%, 15%, 10%, 5%) were generated using well-validated Monte Carlo-based simulations. The images were reconstructed using a 3-D ordered-subsets expectation maximization-based approach. Next, the low-dose images were denoised using a commonly used convolutional neural network-based approach. The impact of DL-based denoising was evaluated using both fidelity-based FoMs and area under the receiver operating characteristic curve (AUC), which quantified performance on the clinical task of detecting perfusion defects in MPS images as obtained using a model observer with anthropomorphic channels. We then provide a mathematical treatment to probe the impact of post-processing operations on signal-detection tasks and use this treatment to analyze the findings of this study. RESULTS: Based on fidelity-based FoMs, denoising using the considered DL-based method led to significantly superior performance. However, based on ROC analysis, denoising did not improve, and in fact, often degraded detection-task performance. This discordance between fidelity-based FoMs and task-based evaluation was observed at all the low-dose levels and for different cardiac-defect types. Our theoretical analysis revealed that the major reason for this degraded performance was that the denoising method reduced the difference in the means of the reconstructed images and of the channel operator-extracted feature vectors between the defect-absent and defect-present cases. CONCLUSIONS: The results show the discrepancy between the evaluation of DL-based methods with fidelity-based metrics versus the evaluation on clinical tasks. This motivates the need for objective task-based evaluation of DL-based denoising approaches. Further, this study shows how VITs provide a mechanism to conduct such evaluations computationally, in a time and resource-efficient setting, and avoid risks such as radiation dose to the patient. Finally, our theoretical treatment reveals insights into the reasons for the limited performance of the denoising approach and may be used to probe the effect of other post-processing operations on signal-detection tasks.

Need for Objective Task-based Evaluation of Deep Learning-Based Denoising Methods: A Study in the Context of Myocardial Perfusion SPECT.

Artificial intelligence-based methods have generated substantial interest in nuclear medicine. An area of significant interest has been using deep-learning (DL)-based approaches for denoising images acquired with lower doses, shorter acquisition times, or both. Objective evaluation of these approaches is essential for clinical application. DL-based approaches for denoising nuclear-medicine images have typically been evaluated using fidelity-based figures of merit (FoMs) such as RMSE and SSIM. However, these images are acquired for clinical tasks and thus should be evaluated based on their performance in these tasks. Our objectives were to (1) investigate whether evaluation with these FoMs is consistent with objective clinical-task-based evaluation; (2) provide a theoretical analysis for determining the impact of denoising on signal-detection tasks; (3) demonstrate the utility of virtual clinical trials (VCTs) to evaluate DL-based methods. A VCT to evaluate a DL-based method for denoising myocardial perfusion SPECT (MPS) images was conducted. The impact of DL-based denoising was evaluated using fidelity-based FoMs and AUC, which quantified performance on detecting perfusion defects in MPS images as obtained using a model observer with anthropomorphic channels. Based on fidelity-based FoMs, denoising using the considered DL-based method led to significantly superior performance. However, based on ROC analysis, denoising did not improve, and in fact, often degraded detection-task performance. The results motivate the need for objective task-based evaluation of DL-based denoising approaches. Further, this study shows how VCTs provide a mechanism to conduct such evaluations using VCTs. Finally, our theoretical treatment reveals insights into the reasons for the limited performance of the denoising approach.

FDG PET/CT-based Response Assessment in Malignancies.

Response is the logical outcome measure of a treatment in a clinical or research setting. Objective response assessment involves the use of a test to segregate patients who are likely to experience improved survival from those who are not. Early and accurate response assessment is critical for determining therapy effectiveness in clinical settings, for effective trial designs comparing two or more therapies, and for modulating treatment on the basis of response (ie, response-adapted therapy). 2-[fluorine 18]fluoro-2-deoxy-d-glucose (FDG) PET/CT can provide both functional and structural information about a disease process. It has been used at several stages of patient management, including imaging-based tumor response assessment, for various malignancies. FDG PET/CT can be used to differentiate patients with lymphoma who have a residual mass but no residual disease after treatment (ie, complete responders) from those who have a residual mass and residual disease after treatment. Similarly, in solid malignancies, the functional changes in glucose uptake and metabolism precede the structural changes (commonly seen as tumor shrinkage) and necrosis. Response assessment criteria have been developed on the basis of findings on FDG PET/CT images and are continuously being revised to ensure standardization and improve their predictive performance. Published under a CC BY 4.0 license. Quiz questions for this article are available through the Online Learning Center.

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials.

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients' tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.

Harnessing imaging tools to guide immunotherapy trials: summary from the National Cancer Institute Cancer Imaging Steering Committee workshop.

As the immuno-oncology field continues the rapid growth witnessed over the past decade, optimising patient outcomes requires an evolution in the current response-assessment guidelines for phase 2 and 3 immunotherapy clinical trials and clinical care. Additionally, investigational tools-including image analysis of standard-of-care scans (such as CT, magnetic resonance, and PET) with analytics, such as radiomics, functional magnetic resonance agents, and novel molecular-imaging PET agents-offer promising advancements for assessment of immunotherapy. To document current challenges and opportunities and identify next steps in immunotherapy diagnostic imaging, the National Cancer Institute Clinical Imaging Steering Committee convened a meeting with diverse representation among imaging experts and oncologists to generate a comprehensive review of the state of the field.

Diagnostic Accuracy of 99mTc-Sestamibi SPECT/CT for Characterization of Solid Renal Masses.

Our objective was to assess the diagnostic accuracy of 99mTc-sestamibi SPECT/CT for characterizing solid renal masses. Methods: Imaging and clinical records of patients who underwent 99mTc-sestamibi SPECT/CT for clinical work-up of their solid renal masses from September 2018 to October 2021 were retrospectively reviewed. Histopathology formed the reference standard, and the diagnoses were categorized as malignant/concerning (renal cell carcinomas [RCCs] other than chromophobe histology) and benign/nonconcerning (oncocytic tumors including chromophobe RCC, other benign diagnoses) to calculate the sensitivity and specificity of 99mTc-sestamibi SPECT/CT and contrast-enhanced CT (ceCT). The clinical reads of the SPECT/CT images were used for visual classification of the lesions. Additionally, the SPECT images were manually segmented to obtain the maximum and mean counts of the lesion and adjacent renal cortex and maximum and mean lesion Hounsfield units. Results: 99mTc-sestamibi SPECT/CT was performed on 42 patients with 62 renal masses. A histopathologic diagnosis was available for 27 patients (18 male, 9 female) with 36 solid renal masses. ceCT findings were available for 20 of these patients. The most commonly identified single histologic type was clear cell RCC (13/36; 36.1%). Oncocytic tumors were the most common group of nonconcerning lesions (15/36), with oncocytoma as the predominant histologic type (n = 6). The sensitivity and specificity of SPECT/CT for diagnosing a nonconcerning lesion were 66.7% and 89.5%, respectively, compared with 10% and 75%, respectively, for ceCT. The lesion-to-kidney ratios for maximum and mean counts and maximum lesion Hounsfield units showed significant differences between the 2 groups (P < 0.05). The lesion-to-kidney mean count ratio at a cutoff of 0.46 showed a sensitivity and specificity of 87.5% and 86.67%, respectively, for detecting nonconcerning lesions, which was significantly higher than that of ceCT. Conclusion: The current literature on the utility of 99mTc-sestamibi SPECT/CT for characterization of solid renal masses is limited. We offer additional evidence of the incremental value of 99mTc-sestamibi SPECT/CT over ceCT for differentiating malignant or aggressive renal tumors from benign or indolent ones, thereby potentially avoiding overtreatment and its associated complications. Quantitative assessment can further increase the diagnostic accuracy of SPECT/CT and may be used in conjunction with visual interpretation.

Adverse Clinical Events at the Injection Site Are Exceedingly Rare After Reported Radiopharmaceutical Extravasation in Patients Undergoing 99mTc-MDP Whole-Body Bone Scintigraphy: A 12-Year Experience.

The deleterious effects of high-dose radiation on normal tissue are sometimes extrapolated to diagnostic (SPECT and PET) radiopharmaceutical extravasation (RPE). It has been hypothesized that diagnostic RPE can have gradually evolving local tissue injury and a potentially increased risk of local dermatologic or oncologic diseases over a longer period. However, data on clinical adverse events after diagnostic RPE are limited. Therefore, our primary aim was to study the occurrence of short-term and long-term clinical adverse events in patients who underwent 99mTc-methylene diphosphonate (99mTc-MDP) whole-body bone scintigraphy (WBBS) with reported RPE. Methods: The records of 99mTc-MDP WBBS performed from June 2010 to January 2022 were retrospectively examined for RPE documented in the scan reports. The clinical records of patients with a documented RPE were extensively reviewed for any related short-term adverse events (within 2 wk of the WBBS: local symptoms and care sought for local dermatologic or musculoskeletal issues) and long-term adverse events (until the last follow-up: local deleterious effects and related consults for dermatology, plastic surgery, oncology, or orthopedics). Results: Retrospective review of the records of 31,679 99mTc-MDP WBBS studies showed RPE documented in 118 (0.37%). Medical records were not retrievable for 22 patients, yielding a final cohort of 96 patients with reported RPE. The median follow-up was 18.9 mo (interquartile range, 7.8-45.7 mo). Short-term events were noted in 4 patients, of whom one was asymptomatic. Of the 3 symptomatic patients, 2 experienced mild discomfort at the injection site, and 1 had tender swelling. Three of the 4 events were in patients who had a prior intravenous contrast extravasation for contrast-enhanced CT performed earlier during the day and a 99mTc-MDP injection later at the same site, likely leading to RPE. None of the long-term local events had any plausible link with the RPE event. Conclusion: Reported RPE was rare, and 3 patients (0.009%) had short-term local symptoms, all of which were likely related to the prior higher-volume intravenous contrast extravasation. The smaller-volume diagnostic radiopharmaceutical injections for WBBS are highly unlikely to cause local symptoms on their own. No patient had any long-term adverse event with a plausible link to the RPE.