Full automation of total metabolic tumor volume from FDG-PET/CT in DLBCL for baseline risk assessments

BACKGROUND: Current radiological assessments of (18)fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging data in diffuse large B-cell lymphoma (DLBCL) can be time consuming, do not yield real-time information regarding disease burden and organ involvement, and hinder the use of FDG-PET to potentially limit the reliance on invasive procedures (e.g. bone marrow biopsy) for risk assessment. METHODS: Our aim is to enable real-time assessment of imaging-based risk factors at a large scale and we propose a fully automatic artificial intelligence (AI)-based tool to rapidly extract FDG-PET imaging metrics in DLBCL. On availability of a scan, in combination with clinical data, our approach generates clinically informative risk scores with minimal resource requirements. Overall, 1268 patients with previously untreated DLBCL from the phase III GOYA trial (NCT01287741) were included in the analysis (training: n = 846; hold-out: n = 422). RESULTS: Our AI-based model comprising imaging and clinical variables yielded a tangible prognostic improvement compared to clinical models without imaging metrics. We observed a risk increase for progression-free survival (PFS) with hazard ratios [HR] of 1.87 (95% CI: 1.31–2.67) vs 1.38 (95% CI: 0.98–1.96) (C-index: 0.59 vs 0.55), and a risk increase for overall survival (OS) (HR: 2.16 (95% CI: 1.37–3.40) vs 1.40 (95% CI: 0.90–2.17); C-index: 0.59 vs 0.55). The combined model defined a high-risk population with 35% and 42% increased odds of a 4-year PFS and OS event, respectively, versus the International Prognostic Index components alone. The method also identified a subpopulation with a 2-year Central Nervous System (CNS)-relapse probability of 17.1%. CONCLUSION: Our tool enables an enhanced risk stratification compared with IPI, and the results indicate that imaging can be used to improve the prediction of central nervous system relapse in DLBCL. These findings support integration of clinically informative AI-generated imaging metrics into clinical workflows to improve identification of high-risk DLBCL patients. TRIAL REGISTRATION: Registered clinicaltrials.gov number: NCT01287741. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40644-022-00476-0

Peroxisome proliferator-activated receptor α (PPARα) mRNA expression in human hepatocellular carcinoma tissue and non-cancerous liver tissue

<p>Abstract</p> <p>Background</p> <p>Peroxisome proliferator-activated receptor α (PPARα) regulates lipid metabolism in the liver. It is unclear, however, how this receptor changes in liver cancer tissue. On the other hand, mouse carcinogenicity studies showed that PPARα is necessary for the development of liver cancer induced by peroxisome proliferators, and the relationship between PPARα and the development of liver cancer have been the focus of considerable attention. There have been no reports, however, demonstrating that PPARα is involved in the development of human liver cancer.</p> <p>Methods</p> <p>The subjects were 10 patients who underwent hepatectomy for hepatocellular carcinoma. We assessed the expression of PPARα mRNA in human hepatocellular carcinoma tissue and non-cancerous tissue, as well as the expression of target genes of PPARα, carnitine palmitoyltransferase 1A and cyclin D1 mRNAs. We also evaluated glyceraldehyde 3-phosphate dehydrogenase, a key enzyme in the glycolytic system.</p> <p>Results</p> <p>The amounts of PPARα, carnitine palmitoyltransferase 1A and glyceraldehyde 3-phosphate dehydrogenase mRNA in cancerous sections were significantly increased compared to those in non-cancerous sections. The level of cyclin D1 mRNA tends to be higher in cancerous than non-cancerous sections. Although there was a significant correlation between the levels of PPARα mRNA and cyclin D1 mRNA in both sections, however the correlation was higher in cancerous sections.</p> <p>Conclusion</p> <p>The present investigation indicated increased expression of PPARα mRNA and mRNAs for PPARα target genes in human hepatocellular carcinoma. These results might be associated with its carcinogenesis and characteristic features of energy production.</p

Role of Imaging in the Staging and Response Assessment of Lymphoma:Consensus of the International Conference on Malignant Lymphomas Imaging Working Group

This article comprises the consensus reached to update guidance on the use of PET-CT for staging and response assessment for 18F FDG-avid lymphomas in clinical practice and late-phase trials

Impact of combined 18F-FDG PET/CT in head and neck tumours

To compare the interobserver agreement and degree of confidence in anatomical localisation of lesions using 2-[fluorine-18]fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) and 18F-FDG PET alone in patients with head and neck tumours. A prospective study of 24 patients (16 male, eight female, median age 59 years) with head and neck tumours was undertaken. 18F-FDG PET/CT was performed for staging purposes. 2D images were acquired over the head and neck area using a GE Discovery LS™ PET/CT scanner. 18F-FDG PET images were interpreted by three independent observers. The observers were asked to localise abnormal 18F-FDG activity to an anatomical territory and score the degree of confidence in localisation on a scale from 1 to 3 (1=exact region unknown; 2=probable; 3=definite). For all 18F-FDG-avid lesions, standardised uptake values (SUVs) were also calculated. After 3 weeks, the same exercise was carried out using 18F-FDG PET/CT images, where CT and fused volume data were made available to observers. The degree of interobserver agreement was measured in both instances. A total of six primary lesions with abnormal 18F-FDG uptake (SUV range 7.2–22) were identified on 18F-FDG PET alone and on 18F-FDG PET/CT. In all, 15 nonprimary tumour sites were identified with 18F-FDG PET only (SUV range 4.5–11.7), while 17 were identified on 18F-FDG PET/CT. Using 18F-FDG PET only, correct localisation was documented in three of six primary lesions, while 18F-FDG PET/CT correctly identified all primary sites. In nonprimary tumour sites, 18F-FDG PET/CT improved the degree of confidence in anatomical localisation by 51%. Interobserver agreement in assigning primary and nonprimary lesions to anatomical territories was moderate using 18F-FDG PET alone (kappa coefficients of 0.45 and 0.54, respectively), but almost perfect with 18F-FDG PET/CT (kappa coefficients of 0.90 and 0.93, respectively). We conclude that 18F-FDG PET/CT significantly increases interobserver agreement and confidence in disease localisation of 18F-FDG-avid lesions in patients with head and neck cancers

The Role and Limitations of 18-Fluoro-2-deoxy-d-glucose Positron Emission Tomography (FDG-PET) Scan and Computerized Tomography (CT) in Restaging Patients with Hepatic Colorectal Metastases Following Neoadjuvant Chemotherapy: Comparison with Operative and Pathological Findings

BACKGROUND: Recent data confirmed the importance of 18-fluoro-2-deoxy-d-glucose positron emission tomography (FDG-PET) in the selection of patients with colorectal hepatic metastases for surgery. Neoadjuvant chemotherapy before hepatic resection in selected cases may improve outcome. The influence of chemotherapy on the sensitivity of FDG-PET and CT in detecting liver metastases is not known. METHODS: Patients were assigned to either neoadjuvant treatment or immediate hepatic resection according to resectability, risk of recurrence, extrahepatic disease, and patient preference. Two-thirds of them underwent FDG-PET/CT before chemotherapy; all underwent preoperative contrast-enhanced CT and FDG-PET/CT. Those without extensive extrahepatic disease underwent open exploration and resection of all the metastases according to original imaging findings. Operative and pathological findings were compared to imaging results. RESULTS: Twenty-seven patients (33 lesions) underwent immediate hepatic resection (group 1), and 48 patients (122 lesions) received preoperative neoadjuvant chemotherapy (group 2). Sensitivity of FDG-PET and CT in detecting colorectal (CR) metastases was significantly higher in group 1 than in group 2 (FDG-PET: 93.3 vs 49%, P < 0.0001; CT: 87.5 vs 65.3, P = 0.038). CT had a higher sensitivity than FDG-PET in detecting CR metastases following neoadjuvant therapy (65.3 vs 49%, P < 0.0001). Sensitivity of FDG-PET, but not of CT, was lower in group 2 patients whose chemotherapy included bevacizumab compared to patients who did not receive bevacizumab (39 vs 59%, P = 0.068). CONCLUSIONS: FDG-PET/CT sensitivity is lowered by neoadjuvant chemotherapy. CT is more sensitive than FDG-PET in detecting CR metastases following neoadjuvant therapy. Surgical decision-making requires information from multiple imaging modalities and pretreatment findings. Baseline FDG-PET and CT before neoadjuvant therapy are mandatory

GLUT 5 Is Not Over-Expressed in Breast Cancer Cells and Patient Breast Cancer Tissues

F18 2-Fluoro 2-deoxyglucose (FDG) has been the gold standard in positron emission tomography (PET) oncologic imaging since its introduction into the clinics several years ago. Seeking to complement FDG in the diagnosis of breast cancer using radio labeled fructose based analogs, we investigated the expression of the chief fructose transporter-GLUT 5 in breast cancer cells and human tissues. Our results indicate that GLUT 5 is not over-expressed in breast cancer tissues as assessed by an extensive immunohistochemistry study. RT-PCR studies showed that the GLUT 5 mRNA was present at minimal amounts in breast cancer cell lines. Further knocking down the expression of GLUT 5 in breast cancer cells using RNA interference did not affect the fructose uptake in these cell lines. Taken together these results are consistent with GLUT 5 not being essential for fructose uptake in breast cancer cells and tissues

An artificial intelligence method using FDG PET to predict treatment outcome in diffuse large B cell lymphoma patients

Convolutional neural networks (CNNs) may improve response prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study was to investigate the feasibility of a CNN using maximum intensity projection (MIP) images from 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) baseline scans to predict the probability of time-to-progression (TTP) within 2&nbsp;years and compare it with the International Prognostic Index (IPI), i.e. a clinically used score. 296 DLBCL 18F-FDG PET/CT baseline scans collected from a prospective clinical trial (HOVON-84) were analysed. Cross-validation was performed using coronal and sagittal MIPs. An external dataset (340 DLBCL patients) was used to validate the model. Association between the probabilities, metabolic tumour volume and Dmaxbulk was assessed. Probabilities for PET scans with synthetically removed tumors were also assessed. The CNN provided a 2-year TTP prediction with an&nbsp;area under the curve (AUC) of 0.74, outperforming the IPI-based model (AUC = 0.68). Furthermore, high probabilities (&gt; 0.6) of the original MIPs were considerably decreased after removing the tumours (&lt; 0.4, generally). These findings suggest that MIP-based CNNs are able to predict treatment outcome in DLBCL