Search Results (25)

Background: Assessment of the peritoneal cancer burden is crucial for determining the optimal treatment in advanced ovarian cancer (AOC). Effective non-invasive methods to predict tumour load remain limited. This study aimed to assess the applicability of 2-[¹⁸F]FDG PET/CT volumetric parameters, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) for predicting the surgical peritoneal cancer index (PCI) in AOC before primary treatment. Methods: Patients with high-grade serous or undifferentiated AOC who underwent surgical PCI evaluation and 2-[¹⁸F]FDG PET/CT between 01/2013 and 12/2018 were included. MTV and TLG were calculated using thresholds of 40% and 50% (MTV40, MTV50, TLG40, and TLG50). Correlations between the peritoneal carcinomatosis MTV (car_MTV) and TLG (car_TLG) were analysed. The capacity of volumetric parameters to estimate PCIs above or below 14 and 20 was assessed for the whole abdominal cavity and in per-quadrant analysis, specifically for upper-abdomen areas 1, 2, and 3 (MTV40_1, 2, 3 and TLG40_1, 2, 3). Results: MTV40, MTV50, TLG40, and TLG50 significantly correlated with the PCI in the final study population (n = 45). MTV40 showed a Pearson coefficient of 0.41 (p = 0.003). MTV3_40 (AUC 0.79) and TLG3_40 (AUC 0.81) presented the highest AUCs for predicting a PCI above or below 14. The volumetric parameters allowed the prediction of a PCI greater or less than 20, with an AUC of 0.77 for MTV40_1 and 0.78 for TLG40_1. Conclusions: 2-[¹⁸F]FDG PET/CT MTV and TLG correlate significantly with the surgical PCI when assessing peritoneal carcinomatosis or quadrant-specific disease. This approach offers a reliable non-invasive method for evaluating tumour burden in AOC. Full article

Purpose: To investigate associations between 18F-FDG-PET/CT semiquantitative and radiomic features with pathologic axillary lymph node (ALN) status in stages I–III breast cancer patients. Methods: A search was conducted across MEDLINE, EMBASE, and CENTRAL databases. Quality assessment was performed with QUADAS-2 and the radiomics quality score (RQS). Descriptive statistical analysis was performed. Results: Most studies were retrospective cohort studies (27/28) and reported only on semiquantitative features (26/28). Most studies were at high risk of bias in patient selection (22/28) and feature extraction (26/28). Semiquantitative features included maximum standardized uptake value (SUVmax), metabolic tumour volume (MTV), and total lesion glycolysis (TLG). Although associations between tumour semiquantitative features and ALN status were reported, the mean/median reported values of tumour SUVmax (3.2–8.6 vs. 2.4–9.4), MTV (2.7–19.2 vs. 1.9–10.5), and TLG (10.6–59.3 vs. 5.6–29.6) in ALN+ vs. ALN− patients were inconsistent between studies. Fourteen studies reported a significantly higher ALN SUVmax in ALN+ patients. Two studies developed models using tumour radiomic features with high accuracy for predicting ALN metastases (81.2% and 80%) but scored low on the RQS. Conclusions: Feature-based analysis of PET/CT demonstrates potential for predicting pathologic ALN status in breast cancer patients. However, establishing a clinically meaningful relationship requires higher quality evidence. Full article

Background: Patients with low tumour burden follicular lymphoma (FL) are managed with an initial watchful waiting (WW) approach. The way to better predict the time-to-treatment (TTT) is still under investigation for its possible clinical impact. This study explored whether radiomic features extracted from baseline ¹⁸F-FDG PET/CT could predict TTT in FL patients on WW. Methods: Thirty-eight patients on initial WW (grade 1–3a) were retrospectively included from 2010 to 2019. Eighty-one PET/CT morphological and first-level intensity radiomic features were extracted from the total metabolic tumour burden (TMTV), the lesion having the highest SUVmax and a reference volume-of-interest placed on the healthy liver. Models using linear regression (LR) and support vector machine (SVM) were constructed to assess the feasibility of using radiomic features to predict TTT. A leave-one-out cross-validation approach was used to assess the performance. Results: For LR models, we found a root-mean-squared error of 29.4, 28.6, 26.4 and 26.8 and an R² of 0.03, 0.08, 0.21 and 0.20, respectively, incrementing the features from one to four. Accordingly, the best model included three features: the liver minimum SUV value, the liver SUV skewness and the sum of squared SUV values in the TMTV. For SVM models, accuracies of 0.79, 0.63, 0.76 and 0.68 and areas under the curve of 0.80, 0.72, 0.77 and 0.63 were found, respectively, incrementing the features from one to four. The best performing model used one feature, namely the median value of the lesion containing the SUVmax value. Conclusions: The baseline PET/CT radiomic approach has the potential to predict TTT in FL patients on WW. Integrating radiomics with clinical parameters could further aid in patient stratification. Full article

Recent research has suggested that one novel mechanism of action for anti-obesity medications is to stimulate the activation of brown adipose tissue (BAT). ¹⁸FDG PET/CT remains the gold standard for defining and quantifying BAT. SUVmax is the most often used quantification tool in clinical practice. However, this parameter does not reflect the entire BAT volume. As a potential method for precisely evaluating BAT, we have utilised metabolic tumour volume (MTV) and total lesion glycolysis (TLG) to answer the question: Are MTV and TLG accurate in quantifying the intensity of BAT activation? After analysing the total number of oncological ¹⁸F-FDG PET/CT scans between 2021–2023, we selected patients with active BAT. Based on the BAT SUVmax, the patients were divided into BAT-moderate activation (MA) vs. BAT-high activation (HA). Furthermore, we statistically analysed the accuracy of TLG and MTV in assessing BAT activation intensity. The results showed that both parameters increased their predictive value regarding BAT activation, and presented a significantly high sensitivity and specificity for the correct classification of BAT activation intensity. To conclude, these parameters could be important indicators with increased accuracy for classifying BAT expression, and could bring additional information about the volume of BAT to complement the limitations of the SUVmax. Full article

Although urgently needed, no significant improvements in osteosarcoma (OS) therapy have been achieved within the last decades. Here, we present a new therapeutic approach based on drug combinations consisting of mitochondrial complex I (MCI) inhibitors and ionophores that induce cancer cell-specific cell death based on a modulation of cellular energy metabolism and intracellular pH (pHi) named the Warburg Trap (WT). The effects of several drug combinations on intracellular pH, cell viability, colony-forming capacity and expression of WNT-target genes were analysed using OS cell lines and primary human osteoblasts (HOB). Tumour take rates and tumour volumes were analysed in vivo using a chicken chorioallantoic membrane assay (CAM). Several WT drug combinations induced the intracellular acidification and apoptotic cell death in OS cells, whereas HOBs tolerated the treatment. A significant inhibition of the colony-forming ability of OS cells and downregulation of WNT-target genes suggest that cancer stem cells (CSCs) are also targeted by the WT approach. In vivo, we observed a significant reduction in the tumour take rates in response to WT drug treatment. Our data suggest that the Warburg Trap is a promising approach for the development of a novel and effective OS therapy to replace or supplement the current OS chemotherapy. Full article

The aim of this prospective clinical study was to evaluate the potential of the prostate specific membrane antigen (PSMA) targeting ligand, [⁶⁸Ga]-PSMA–Glu–NH–CO–NH–Lys-2-naphthyl-L-Ala-cyclohexane-DOTA ([⁶⁸Ga]Ga-PSMA-617) as a positron emission tomography (PET) imaging biomarker in recurrent glioblastoma patients. Patients underwent [⁶⁸Ga]Ga-PSMA-617 and O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine ([¹⁸F]FET) PET scans on two separate days. [⁶⁸Ga]Ga-PSMA-617 tumour selectivity was assessed by comparing tumour volume delineation and by assessing the intra-patient correlation between tumour uptake on [⁶⁸Ga]Ga-PSMA-617 and [¹⁸F]FET PET images. [⁶⁸Ga]Ga-PSMA-617 tumour specificity was evaluated by comparing its tumour-to-brain ratio (TBR) with [¹⁸F]FET TBR and its tumour volume with the magnetic resonance imaging (MRI) contrast-enhancing (CE) tumour volume. Ten patients were recruited in this study. [⁶⁸Ga]Ga-PSMA-617-avid tumour volume was larger than the [¹⁸F]FET tumour volume (p = 0.063). There was a positive intra-patient correlation (median Pearson r = 0.51; p < 0.0001) between [⁶⁸Ga]Ga-PSMA-617 and [¹⁸F]FET in the tumour volume. [⁶⁸Ga]Ga-PSMA-617 had significantly higher TBR (p = 0.002) than [¹⁸F]FET. The [⁶⁸Ga]Ga-PSMA-617-avid tumour volume was larger than the CE tumour volume (p = 0.0039). Overall, accumulation of [⁶⁸Ga]-Ga-PSMA-617 beyond [¹⁸F]FET-avid tumour regions suggests the presence of neoangiogenesis in tumour regions that are not overly metabolically active yet. Higher tumour specificity suggests that [⁶⁸Ga]-Ga-PSMA-617 could be a better imaging biomarker for recurrent tumour delineation and secondary treatment planning than [¹⁸F]FET and CE MRI. Full article

Background: Antibodies that inhibit the programmed cell death protein 1 (PD-1) receptor offer a significant survival benefit, potentially cure (i.e., durable disease-free survival following treatment discontinuation), a substantial proportion of patients with advanced melanoma. Most patients however fail to respond to such treatment or acquire resistance. Previously, we reported that baseline total metabolic tumour volume (TMTV) determined by whole-body [${}^{18}$F]FDG PET/CT was independently correlated with survival and able to predict the futility of treatment. Manual delineation of [${}^{18}$F]FDG-avid lesions is however labour intensive and not suitable for routine use. A predictive survival model is proposed based on automated analysis of baseline, whole-body [${}^{18}$F]FDG images. Methods: Lesions were segmented on [${}^{18}$F]FDG PET/CT using a deep-learning approach and derived features were investigated through Kaplan–Meier survival estimates with univariate logrank test and Cox regression analyses. Selected parameters were evaluated in multivariate Cox survival regressors. Results: In the development set of 69 patients, overall survival prediction based on TMTV, lactate dehydrogenase levels and presence of brain metastases achieved an area under the curve of 0.78 at one year, 0.70 at two years. No statistically significant difference was observed with respect to using manually segmented lesions. Internal validation on 31 patients yielded scores of 0.76 for one year and 0.74 for two years. Conclusions: Automatically extracted TMTV based on whole-body [${}^{18}$F]FDG PET/CT can aid in building predictive models that can support therapeutic decisions in patients treated with immune-checkpoint blockade. Full article

A meta-analysis of 1470 isolated pancreatic metastases of renal cell carcinoma revealed, that, in addition to the unusual exclusive occurrence of pancreatic metastases and the favourable treatment results, the isPMRCC is characterised by further peculiarities of the clinical course: The lack of prognostic significance of volume and growth rate dependent risk factors and the independence of treatment results from standard or local resections. As an explanation for all these peculiarities, according to today’s knowledge, a strong acting seed and soil mechanism can serve, which allows embolized tumour cells to grow to metastases only in the pancreas, and prevents them definitively or for years in all other organs. The good prognosis affects not only isolated PM, but also multi-organ metastases of the RCC, in which the additional occurrence of PM is also associated with a better prognosis. Genetic studies revealed specific changes in cases of PM of RCC: Lack of loss of 9p21.3 and 14q31.2, which are otherwise specific gene mutations at the onset of generalization, a low weight genome instability index, i.e., high genetic stability, and a low rate of PAB1 and a high rate of BPRM1 alterations, which signal a more favourable course. The cause of pancreatic organotropism in isPMRCC is still unclear, so only those factors that have been identified as promoting organotropism in other, more frequent tumour entities can be presented: Formation of the pre-metastatic niche, chemokine receptor–ligand mechanism, ability to metabolic adaptation, and immune surveillance. Full article

Purpose: to investigate the preoperative role of ML-based classification using conventional ¹⁸F-FDG PET parameters and clinical data in predicting features of EC aggressiveness. Methods: retrospective study, including 123 EC patients who underwent ¹⁸F-FDG PET (2009–2021) for preoperative staging. Maximum standardized uptake value (SUVmax), SUVmean, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were computed on the primary tumour. Age and BMI were collected. Histotype, myometrial invasion (MI), risk group, lymph-nodal involvement (LN), and p53 expression were retrieved from histology. The population was split into a train and a validation set (80–20%). The train set was used to select relevant parameters (Mann-Whitney U test; ROC analysis) and implement ML models, while the validation set was used to test prediction abilities. Results: on the validation set, the best accuracies obtained with individual parameters and ML were: 61% (TLG) and 87% (ML) for MI; 71% (SUVmax) and 79% (ML) for risk groups; 72% (TLG) and 83% (ML) for LN; 45% (SUVmax; SUVmean) and 73% (ML) for p53 expression. Conclusions: ML-based classification using conventional ¹⁸F-FDG PET parameters and clinical data demonstrated ability to characterize the investigated features of EC aggressiveness, providing a non-invasive way to support preoperative stratification of EC patients. Full article

Background: Approximately 30% of patients with diffuse large B-cell lymphoma (DLBCL) will have recurrence. The aim of this study was to develop a radiomic based model derived from baseline PET/CT to predict 2-year event free survival (2-EFS). Methods: Patients with DLBCL treated with R-CHOP chemotherapy undergoing pre-treatment PET/CT between January 2008 and January 2018 were included. The dataset was split into training and internal unseen test sets (ratio 80:20). A logistic regression model using metabolic tumour volume (MTV) and six different machine learning classifiers created from clinical and radiomic features derived from the baseline PET/CT were trained and tuned using four-fold cross validation. The model with the highest mean validation receiver operator characteristic (ROC) curve area under the curve (AUC) was tested on the unseen test set. Results: 229 DLBCL patients met the inclusion criteria with 62 (27%) having 2-EFS events. The training cohort had 183 patients with 46 patients in the unseen test cohort. The model with the highest mean validation AUC combined clinical and radiomic features in a ridge regression model with a mean validation AUC of 0.75 ± 0.06 and a test AUC of 0.73. Conclusions: Radiomics based models demonstrate promise in predicting outcomes in DLBCL patients. Full article

Purpose To evaluate the role of 2-[¹⁸F]FDGPET/CT in the follow-up of radioiodine refractory thyroid cancer (RR-TC). Methods Forty-six 2-[¹⁸F]FDGPET/CT scans from 14 RR-TC patients were considered. Thyroid function tests: thyroglobulin (Tg), levothyroxine (LT4), and tyrosine-kinases inhibitors (TKIs) assumptions were recorded. Metabolic tumour volume (MTV) and total lesion glycolysis (TLG) were calculated from each scan and correlated with clinical parameters and the overall survival (OS). Results Baseline TLG and MTV predicted OS (p = 0.027 and p = 0.035), and negative correlation with OS was also confirmed when the same parameters were measured in follow-up scans (p = 0.015 and p = 0.021). Tg also correlated with the OS; (p = 0.014; p = 0.019 and p = 0.009). However, TLG and MTV were not significantly correlated with Tg levels. MTV and TLG variation in time were reduced during TKI therapy (p = 0.045 and p = 0.013). Conclusions 2-[¹⁸F]FDGPET/CT confirmed its prognostic role at the first assessment and during the follow-up of RR-TC patients. 2-[¹⁸F]FDGPET/CT parameters seem at least partially independent from Tg. TKI therapy resulted in a measurable effect on the variation of 2-[¹⁸F]FDGPET/CT parameters over time. Full article

Background: High uptake of F18-fluorodeoxyglucose parameters for glucose metabolism is related to shorter survival in sinonasal tract cancer with various histological classifications. We investigated whether F18-fluorodeoxyglucose uptake parameters are associated with survival outcomes for patients with only squamous cell carcinoma (SCC) in the sinonasal tract that are treated either with surgery or nonsurgery. Methods: We retrospectively observed F18-fluorodeoxyglucose uptake parameters on positron emission tomography with computed tomography for the primary tumour of SCC in 39 patients. Log-rank test or a Cox regression model with 95% confidence interval (95%CI) and hazard ratio (HR) were used for monovariable or multivariable analysis, respectively. We determined cut-off values of the F18-fluorodeoxyglucose uptake parameters using the lowest p value for monovariable sinonasal tract cancer-specific survival analysis. Results: Monovariable analysis showed that patients with metabolic tumour volume (MTV) ≥ 21.8 had a shorter cancer-specific, disease-free and local recurrence-free survival than those with MTV < 21.8. After adjusting for age, gender, clinical stage and treatment group in the multivariable analysis, MTV (≥21.8/<21.8) was related to shorter cancer-specific (HR: 3.69, 95%CI: 1.17–12.0), disease-free (HR: 3.38, 95%CI: 1.19–9.71) and local recurrence-free (HR: 5.42, 95%CI: 1.59–20.3) survivals. Conclusions: MTV as advances in diagnostics of sinonasal tract SCC is a predictor. Full article

The purpose of this study is to discuss how to use an external radio-opaque template in the Diffusing Alpha-emitters Radiation Therapy (DaRT) technique’s pre-planning and treatment stages. This device would help to determine the proper number of sources for tumour coverage, accounting for subcutaneous invasion and augmenting DaRT safety. The procedure will be carried out in a first phase on a phantom and then applied to a clinical case. A typical DaRT procedure workflow comprises steps like tumour measurements and delineation, source number assessment, and therapy administration. As a first step, an adhesive fiberglass mesh (spaced by 2 mm) tape was applied on the skin of the patient and employed as frame of reference. A physician contoured the lesion and marked the entrance points for the needles with a radio opaque ink marker. According to the radio opaque marks and metabolic uptake the clinical target volume was defined, and with a commercial brachytherapy treatment planning system (TPS) it was possible to simulate and adjust the spatial seeds distribution. After the implant procedure a CT was again performed to check the agreement between simulations and seeds positions. With the procedure described above it was possible to simulate a DaRT procedure on a phantom in order to train physicians and subsequently apply the novel approach on patients, outlining the major issues involved in the technique. The present work innovates and supports DaRT technique for the treatment of cutaneous cancers, improving its efficacy and safety. Full article

The aim of this retrospective study was to investigate the ability of 18 fluorine-fluorodeoxyglucose positron emission tomography/CT (¹⁸F-FDG-PET/CT) metrics and radiomics features (RFs) in predicting the final diagnosis of solitary pulmonary nodules (SPN). We retrospectively recruited 202 patients who underwent a ¹⁸F-FDG-PET/CT before any treatment in two PET scanners. After volumetric segmentation of each lung nodule, 8 PET metrics and 42 RFs were extracted. All the features were tested for significant differences between the two PET scanners. The performances of all features in predicting the nature of SPN were analyzed by testing three classes of final logistic regression predictive models: two were built/trained through exploiting the separate data from the two scanners, and the other joined the data together. One hundred and twenty-seven patients had a final diagnosis of malignancy, while 64 were of a benign nature. Comparing the two PET scanners, we found that all metabolic features and most of RFs were significantly different, despite the cross correlation being quite similar. For scanner 1, a combination between grey level co-occurrence matrix (GLCM), histogram, and grey-level zone length matrix (GLZLM) related features presented the best performances to predict the diagnosis; for scanner 2, it was GLCM and histogram-related features and metabolic tumour volume (MTV); and for scanner 1 + 2, it was histogram features, standardized uptake value (SUV) metrics, and MTV. RFs had a significant role in predicting the diagnosis of SPN, but their accuracies were directly related to the scanner. Full article

Gastrointestinal stromal tumour has already been well explored at the genome level; however, little is known about metabolic processes occurring in the sarcoma. Sample preparation is a crucial step in untargeted metabolomics workflow, highly affecting the metabolome coverage and the quality of the results. In this study, four liquid-liquid extraction methods for the isolation of endogenous compounds from gastrointestinal stromal tumours were compared and evaluated. The protocols covered two-step or stepwise extraction with methyl-tert-butyl ether (MTBE) or dichloromethane. The extracts were subjected to LC-MS analysis by the application of reversed-phase and hydrophilic interaction liquid chromatography to enable the separation and detection of both polar and nonpolar analytes. The extraction methods were compared in terms of efficiency (total number of detected metabolites) and reproducibility. The method was based on the stepwise extraction with MTBE, methanol, and water proved to be the most reproducible, and thus, its robustness to fluctuations in experimental conditions was assessed employing Plackett–Burman design and hierarchical modelling. While most studied factors had no effect on the metabolite abundance, the highest coefficient value was observed for the volume of MTBE added during extraction. Herein, we demonstrate the application and the feasibility of the selected protocol for the analysis of gastrointestinal stromal tumour samples. The method selected could be considered as a reference for the best characterization of underlying molecular changes associated with complex tissue extracts of GIST. Full article