Understanding the differences between prognostic and predictive indices is imperative for medical research advances. We have developed a new prognostic measure that will identify the strengths, limitations, and potential applications in clinical practice.
Peptide receptor radionuclide therapy (PRRT) is a treatment option for patients with advanced meningioma. Recently, intraarterial application of the radiolabeled somatostatin receptor agonists has been introduced as an alternative to standard intravenous administration. In this study, we assessed the safety and efficacy of intraarterial PRRT in patients with advanced, progressive meningioma. Methods: Patients with advanced, progressive meningioma underwent intraarterial PRRT with [177Lu]Lu-HA-DOTATATE. The safety of PRRT was evaluated according to the Common Terminology Criteria for Adverse Events version 5.0. Treatment response was assessed according to the proposed Response Assessment in Neuro-Oncology criteria for meningiomas and somatostatin receptor–directed PET/CT. Results: Thirteen patients (8 women, 5 men; mean age, 65 ± 13 y) with advanced meningioma underwent 1–4 cycles (median, 4 cycles) of intraarterial PRRT with [177Lu]Lu-HA-DOTATATE (mean activity per cycle, 7,428 ± 237 MBq; range, 6,000–7,700 MBq). Treatment was well tolerated with mainly grade 1–2 hematologic toxicity. Ten of 13 patients showed radiologic disease control at follow-up after therapy (1/10 complete remission, 1/10 partial remission, 8/10 stable disease), and 9 of 13 patients showed good control of clinical symptoms. Conclusion: Intraarterial PRRT in patients with advanced meningioma is feasible and safe. It may result in improved radiologic and clinical disease control compared with intravenous PRRT. Further research to validate these initial findings and to investigate long-term outcomes is highly warranted.
Radiopharmaceutical cocktails have been developed over the years to treat cancer. Cocktails of agents are attractive because 1 radiopharmaceutical is unlikely to have the desired therapeutic effect because of nonuniform uptake by the targeted cells. Therefore, multiple radiopharmaceuticals targeting different receptors on a cell is warranted. However, past implementations in vivo have not met with convincing results because of the absence of optimization strategies. Here we present artificial intelligence (AI) tools housed in a new version of our software platform, MIRDcell V4, that optimize a cocktail of radiopharmaceuticals by minimizing the total disintegrations needed to achieve a given surviving fraction (SF) of tumor cells. Methods: AI tools are developed within MIRDcell V4 using an optimizer based on the sequential least-squares programming algorithm. The algorithm determines the molar activities for each drug in the cocktail that minimize the total disintegrations required to achieve a specified SF. Tools are provided for populations of cells that do not cross-irradiate (e.g., circulating or disseminated tumor cells) and for multicellular clusters (e.g., micrometastases). The tools were tested using model data, flow cytometry data for suspensions of single cells labeled with fluorochrome-labeled antibodies, and 3-dimensional spatiotemporal kinetics in spheroids for fluorochrome-loaded liposomes. Results: Experimental binding distributions of 4 211At-antibodies were considered for treating suspensions of MDA-MB-231 human breast cancer cells. A 2-drug combination reduced the number of 211At decays required by a factor of 1.6 relative to the best single antibody. In another study, 2 radiopharmaceuticals radiolabeled with 195mPt were each distributed lognormally in a hypothetical multicellular cluster. Here, the 2-drug combination required 1.7-fold fewer decays than did either drug alone. Finally, 2 225Ac-labeled drugs that provide different radial distributions within a spheroid require about one half of the disintegrations required by the best single agent. Conclusion: The MIRDcell AI tools determine optimized drug combinations and corresponding molar activities needed to achieve a given SF. This approach could be used to analyze a sample of cells obtained from cell culture, animal, or patient to predict the best combination of drugs for maximum therapeutic effect with the least total disintegrations.
Researchers use dynamic PET imaging with target-selective tracer molecules to probe molecular processes. Kinetic models have been developed to describe these processes. The models are typically fitted to the measured PET data with the assumption that the brain is in a steady-state condition for the duration of the scan. The end results are quantitative parameters that characterize the molecular processes. The most common kinetic modeling endpoints are estimates of volume of distribution or the binding potential of a tracer. If the steady state is violated during the scanning period, the standard kinetic models may not apply. To address this issue, time-variant kinetic models have been developed for the characterization of dynamic PET data acquired while significant changes (e.g., short-lived neurotransmitter changes) are occurring in brain processes. These models are intended to extract a transient signal from data. This work in the PET field dates back at least to the 1990s. As interest has grown in imaging nonsteady events, development and refinement of time-variant models has accelerated. These new models, which we classify as belonging to the first, second, or third generation according to their innovation, have used the latest progress in mathematics, image processing, artificial intelligence, and statistics to improve the sensitivity and performance of the earliest practical time-variant models to detect and describe nonsteady phenomena. This review provides a detailed overview of the history of time-variant models in PET. It puts key advancements in the field into historical and scientific context. The sum total of the methods is an ongoing attempt to better understand the nature and implications of neurotransmitter fluctuations and other brief neurochemical phenomena.
Despite the systemic impact of both cancer and the associated immune response, immuno-PET is predominantly centered on assessment of the immune milieu within the tumor microenvironment. The aim of this study was to assess the value of [18F]F-AraG PET imaging as a noninvasive method for evaluation of system-wide immune status of patients with non–small cell lung cancer before starting immunotherapy. Methods: Eleven patients with advanced non–small cell lung cancer were imaged with [18F]F-AraG before starting immunotherapy. Diagnostic [18F]FDG PET/CT scans were analyzed to assess differences in the extent of disease among patients. SUVmax, SUVmean, and total SUV (SUVtotal) from all tumor lesions, active lymph nodes, spleen, vertebral bone marrow, liver, thyroid, heart, and bowel were extracted from the baseline [18F]F-AraG scans, and discriminant and Kaplan–Meier analyses were performed to test their ability to predict patient response and overall survival. Results: The extent of the disease was variable in the patient cohort, but none of the [18F]FDG biomarkers associated with tumor burden (SUVmax, total metabolic tumor volume, and total lesion glycolysis) was predictive of patient survival. The differences in the [18F]F-AraG and [18F]FDG distribution were observed both within and between lesions, confirming that they capture distinct aspects of the tumor microenvironment. Of the 3 SUV parameters studied, [18F]F-AraG SUVtotal provided a dynamic range suitable for stratifying tumors or patients according to their immune activity. [18F]F-AraG SUVtotal measured in the lumbar and sacral vertebrae differentiated between patients who progressed on therapy and those who did not with 90.9% and 81.8% accuracy, respectively. The Kaplan–Meier analysis revealed that patients with high [18F]F-AraG SUVtotal in the lumbar bone marrow had significantly lower probability of survival than those with a low signal (P = 0.0003). Conclusion: This study highlights the significance of assessing systemic immunity and indicates the potential of the [18F]F-AraG bone marrow signal as a predictive imaging biomarker for patient stratification and treatment guidance.
Gastrointestinal stromal tumors (GISTs) are the most common stromal tumors in the gastrointestinal tract. This study was designed to evaluate a gastrin-releasing peptide receptor antagonist PET tracer, [68Ga]Ga-NOTA-RM26, and compare it with [18F]FDG PET/CT in the assessment of patients with GISTs. Methods: With institutional review board approval and informed consent, 30 patients with suspected or proven GISTs based on abdominal CT or gastroscopy were recruited. All patients underwent [68Ga]Ga-NOTA-RM26 and [18F]FDG PET/CT scans. Pathology and other patient information were collected. Results: No radiopharmaceutical-related adverse events were observed in the patients. In total, 18 lesions in 16 patients were diagnosed as GIST, 3 patients were diagnosed with schwannoma, and 4 patients were diagnosed with leiomyoma. In 18 GISTs, the mean SUVmax of [68Ga]Ga-NOTA-RM26 PET was significantly higher than that of [18F]FDG PET (17.07 ± 19.57 vs. 2.28 ± 1.65; P < 0.01), and [68Ga]Ga-NOTA-RM26 PET/CT had a higher tumor detection rate than did [18F]FDG PET/CT (88.9% vs. 50%; P < 0.01). The uptake of [68Ga]Ga-NOTA-RM26 in GISTs was significantly higher than that in 2 other benign tumors (leiomyoma or schwannoma) (17.07 ± 19.57 vs. 4.23 ± 1.77; P = 0.014). With the SUVmax cutoff value of 6.0, the sensitivity of 68Ga-NOTA-RM26 PET/CT in diagnosing GISTs is 72% and the specificity is 85.7%. Conclusion: Compared with [18F]FDG PET/CT, [68Ga]Ga-NOTA-RM26 PET/CT is a promising and effective imaging modality for the detection of GISTs.
Methods to shorten [18F]FDG Patlak PET imaging procedures ranging from 65–90 to 20–30 min after injection, using a population-averaged input function (PIF) scaled to patient-specific image-derived input function (IDIF) values, were recently evaluated. The aim of the present study was to explore the feasibility of ultrashort 10-min [18F]FDG Patlak imaging at 55–65 min after injection using a PIF combined with direct Patlak reconstructions to provide reliable quantitative accuracy of lung tumor uptake, compared with a full-duration 65-min acquisition using an IDIF. Methods: Patients underwent a 65-min dynamic PET acquisition on a long-axial-field-of-view (LAFOV) Biograph Vision Quadra PET/CT scanner. Subsequently, direct Patlak reconstructions and image-based (with reconstructed dynamic images) Patlak analyses were performed using both the IDIF (time to relative kinetic equilibrium between blood and tissue concentration (t*) = 30 min) and a scaled PIF at 30–60 min after injection. Next, direct Patlak reconstructions were performed on the system console using only the last 10 min of the acquisition, that is, from 55 to 65 min after injection, and a scaled PIF using maximum crystal ring difference settings of both 85 and 322. Tumor lesion and healthy-tissue uptake was quantified and compared between the differently obtained parametric images to assess quantitative accuracy. Results: Good agreement was obtained between direct- and image-based Patlak analyses using the IDIF (t* = 30 min) and scaled PIF at 30–60 min after injection, performed using the different approaches, with no more than 8.8% deviation in tumor influx rate value (Ki) (mean difference ranging from −0.0022 to 0.0018 mL/[min × g]). When direct Patlak reconstruction was performed on the system console, excellent agreement was found between the use of a scaled PIF at 30–60 min after injection versus 55–65 min after injection, with 2.4% deviation in tumor Ki (median difference, −0.0018 mL/[min × g]; range, −0.0047 to 0.0036 mL/[min × g]). For different maximum crystal ring difference settings using the scan time interval of 55–65 min after injection, only a 0.5% difference (median difference, 0.0000 mL/[min × g]; range, −0.0004 to 0.0013 mL/[min × g]) in tumor Ki was found. Conclusion: Ultrashort whole-body [18F]FDG Patlak imaging is feasible on an LAFOV Biograph Vision Quadra PET/CT system without loss of quantitative accuracy to assess lung tumor uptake compared with a full-duration 65-min acquisition. The ultrashort 10-min direct Patlak reconstruction with PIF allows for its implementation in clinical practice.
Neoadjuvant therapy in patients with locally advanced rectal cancer (LARC) has achieved good pathologic complete response (pCR) rates, potentially eliminating the need for surgical intervention. This study investigated preoperative methods for predicting pCR after neoadjuvant short-course radiotherapy (SCRT) combined with immunochemotherapy. Methods: Treatment-naïve patients with histologically confirmed LARC were enrolled from February 2023 to July 2023. Before surgery, the patients received neoadjuvant SCRT followed by 2 cycles of capecitabine and oxaliplatin plus camrelizumab. 68Ga-labeled fibroblast activation protein inhibitor ([68Ga]Ga-FAPI-04) PET/MRI, [18F]FDG PET/CT, and contrast-enhanced MRI were performed before treatment initiation and before surgery in each patient. PET and MRI features and the size and number of lesions were also collected from each scan. Each parameter’s sensitivity, specificity, and diagnostic cutoff were derived via receiver-operating-characteristic curve analysis. Results: Twenty eligible patients (13 men, 7 women; mean age, 60.2 y) were enrolled and completed the entire trial, and all patients had proficient mismatch repair or microsatellite-stable LARC. A postoperative pCR was achieved in 9 patients (45.0%). In the visual evaluation, both [68Ga]Ga-FAPI-04 PET/MRI and [18F]FDG PET/CT were limited to forecasting pCR. Contrast-enhanced MRI had a low sensitivity of 55.56% to predict pCR. In the quantitative evaluation, [68Ga]Ga-FAPI-04 change in SULpeak percentage, where SULpeak is SUVpeak standardized by lean body mass, had the largest area under the curve (0.929) with high specificity (sensitivity, 77.78%; specificity, 100.0%; cutoff, 63.92%). Conclusion: [68Ga]Ga-FAPI-04 PET/MRI is a promising imaging modality for predicting pCR after SCRT combined with immunochemotherapy. The SULpeak decrease exceeding 63.92% may provide valuable guidance in selecting patients who can forgo surgery after neoadjuvant therapy.
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：