F18-fluorodeoxyglucose positron emission tomography (FDG-PET) is a powerful tool to investigate the role of tumor metabolic activity and its suppression by therapy for cancer survival. As part of Total Therapy 3 for newly diagnosed multiple myeloma, metastatic bone survey, magnetic resonance imaging, and FDG-PET scanning were evaluated in 239 untreated patients. All 3 imaging techniques showed correlations with prognostically relevant baseline parameters: the number of focal lesions (FLs), especially when FDG-avid by PET-computed tomography, was positively linked to high levels of -2-microglobulin, C-reactive protein, and lactate dehydrogenase; among gene expression profiling parameters, high-risk and proliferation-related parameters were positively and low-bone-disease molecular subtype inversely correlated with FL. The presence of more than 3 FDG-avid FLs, related to fundamental features of myeloma biology and genomics, was the leading independent parameter associated with inferior overall and event-free survival. Complete FDG suppression in FL before first transplantation conferred significantly better outcomes and was only opposed by gene expression profilingdefined high-risk status, which together accounted for approximately 50% of survival variability (R 2 test). Our results provide a rationale for testing the hypothesis that myeloma survival can be improved by altering treatment in patients in whom FDG suppression cannot be achieved after induction
Spatial intratumor heterogeneity is frequently seen in multiple myeloma (MM) and poses a significant challenge for risk classifiers, which rely on tumor samples from the iliac crest. Because biopsy-based assessment of multiple skeletal sites is difficult, alternative strategies for risk stratification are required. Recently, the size of focal lesions (FLs) was shown to be a surrogate marker for spatial heterogeneity, suggesting that data from medical imaging could be used to improve risk stratification approaches. Here, we investigated the prognostic value of FL size in 404 transplant-eligible, newly diagnosed MM patients. Using diffusion-weighted magnetic resonance imaging with background suppression, we identified the presence of multiple large FLs as a strong prognostic factor. Patients with at least 3 large FLs with a product of the perpendicular diameters >5 cm were associated with poor progression-free survival (PFS) and overall survival (OS; median, 2.3 and 3.6 years, respectively). This pattern, seen in 13.8% of patients, was independent of the Revised International Staging System (RISS), gene expression profiling (GEP)-based risk score, gain(1q), or extramedullary disease (hazard ratio, 2.7 and 2.2 for PFS and OS in multivariate analysis, respectively). The number of FLs lost its negative impact on outcome after adjusting for FL size. In conclusion, the presence of at least 3 large FL is a feature of high risk, which can be used to refine the diagnosis of this type of disease behavior and as an entry criterion for risk-stratified trials.
Diagnosing bone infection in its acute early stage is of utmost clinical importance as the failure to do so results in a therapeutically recalcitrant chronic infection that can only be resolved with extensive surgical intervention, the end result often being a structurally unstable defect requiring reconstructive procedures. [18F]-FDG-PET has been extensively investigated for this purpose, but the results have been mixed in that, while highly sensitive, its specificity with respect to distinguishing between acute infection and sterile inflammatory processes, including normal recuperative post-surgical healing, is limited. This study investigated the possibility that alternative means of acquiring and analyzing FDG-PET data could be used to overcome this lack of specificity without an unacceptable loss of sensitivity. This was done in the context of an experimental rabbit model of post-surgical osteomyelitis with the objective of distinguishing between acute infection and sterile post-surgical inflammation. Imaging was done 7 and 14 days after surgery with continuous data acquisition for a 90-minute period after administration of tracer. Results were evaluated based on both single and dual time point data analysis. The results suggest that the diagnostic utility of FDG-PET is likely limited to well-defined clinical circumstances. We conclude that, in the complicated clinical context of acute post-surgical or post-traumatic infection, the diagnostic utility accuracy of FDG-PET is severely limited based on its focus on the increased glucose utilization that is generally characteristic of inflammatory processes.
The aim of this study was to determine the uptake of intravenously administered N-[11CH3]dimethylaminoparthenolide (DMAPT) into orthotopic 9LSF glioblastoma brain tumors in Fisher 344 rats from positron emission tomography (PET) imaging studies. [11C]Methyl iodide (11CH3I) was utilized as a [11C]-labeling reagent to label the precursor methylaminoparthenolide (MAPT) intermediate. From PET imaging studies it was found that brain uptake of N-[11CH3]DMAPT into brain tumor tissue was rapid (30 minutes), and considerably higher than that in the normal brain tissue.
Introduction: Invasive bone marrow sampling is used in multiple myeloma (MM) diagnosis to obtain biological material, which can then be used to generate prognostically important genetic features. Physically sampling the bone marrow can be uncomfortable for the patient. Also, spatial heterogeneity is a common feature in MM, with multiple focal lesions (FLs) occurring throughout the skeleton, meaning a single sample from the iliac crest may be insufficient to capture intrapatient heterogeneity. An alternative strategy is to extract data directly from diagnostic positron emission tomography-computed tomography (PET-CT) scans of patients. These radiomic features can be used as a proxy from which to infer molecular and clinical phenotypes. Compared to physical sampling, there are several advantages, including rapid analysis, minimalizing patient discomfort, reduced cost and widespread availability of the required scanning equipment in hospitals. Methods: A series of 439 newly diagnosed MM patients were selected, all of which had diagnostic PET-CT scans. A radiologist examined these data and identified focal lesions in the axial skeleton of 136/439 (31%) patients. Focal lesions were manually segmented from the PET portion of the original DICOM data using a density-based thresholding method in 3DSlicer version 4.9.0. Pyradiomics version 1.3 was used to resample the voxels in the PET data to 4x4x4 mm and extract radiomic features from each FL. A combination of 10 filters and 7 feature classes were used and a total of 1679 radiomic features were generated per lesion. Radiomic features were a mixture of first order characteristics such as maximum intensity, shape characteristics and gray level matrix features. Hierarchical clustering was applied to the radiomic features, using the Pearson correlation between features as the distance metric and Ward's method for clustering. Next generation sequencing (NGS) data was available for samples from 58/136 (43%) patients with FLs in whole genome (WGS), whole exome (WES) or targeted panel (TP) modalities. The NGS data was used to detect translocations, copy number aberrations and somatic mutations. Results: There were 789 FLs identified in 136 patients, with each patient containing an average of 5.8 FLs. The median FL volume was 4350 mm3, with a median maximum 3D diameter of 29 mm. Hierarchical clustering across all FLs and radiomic features separated the FLs into 5 discrete clusters associated with various clinical and molecular features. However, clustering appeared to be independent of other classification systems based on gene expression profiling (GEP), including the UAMS classification system and GEP70 risk score. Clustering was also independent of the International Staging System (ISS) status suggesting that it can add additional prognostic information. Clusters also appeared to be independent of somatic mutations in genes previously reported as significantly mutated in MM. Patients commonly had FLs occurring in multiple clusters, suggesting that this method takes into account the heterogeneity between lesions in the same patient. Larger FLs were grouped primarily into two clusters consistent with them having distinct features that can be recognized by this approach. Looking across the different clusters distinct differences in clinical outcome were seen between the groups, with significant differences in both PFS (p=0.007) and overall survival (p=0.005), with worse prognosis being led by a cluster of smaller lesions. Conclusions: Radiomics provides a novel method to extract potentially important data from PET-CT scans which can define individual clusters that have different clinical, molecular and prognostic features. This can provide a novel non-invasive method to assess FLs based on both their physical and radiomic characteristics. Larger study sizes will be needed to confirm the differences in outcomes seen between groups. Disclosures Boyle: Celgene: Honoraria, Other: travel grants; Janssen: Honoraria, Other: travel grants; La Fondation de Frace: Research Funding; Abbvie: Honoraria; Amgen: Honoraria, Other: travel grants; Gilead: Honoraria, Other: travel grants; Takeda: Consultancy, Honoraria. Morgan:Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Research Funding; Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Davies:TRM Oncology: Honoraria; MMRF: Honoraria; Abbvie: Consultancy; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; ASH: Honoraria.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.