Search Results (89)

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

Background: The accurate prediction of pathological complete response (pCR) following total neoadjuvant therapy (TNT) is crucial for optimising treatment protocols in locally advanced rectal cancer (LARC). Although conventional imaging techniques such as MRI show limitations in assessing treatment response, metabolic imaging utilising 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET-CT) provides distinctive information by quantifying tumour glycolytic activity. This study investigates the predictive value of sequential 18F-FDG PET-CT parameters, focusing on Total Lesion Glycolysis (TLG), in predicting pCR after TNT. Methods: We conducted a retrospective analysis of 33 LARC patients (T3–4/N0–1) treated with TNT (neoadjuvant-chemoradiation followed by consolidation FOLFOX chemotherapy). Sequential PET-CT scans were performed at baseline, interim (after 4 cycles of FOLFOX), and post-TNT. Metabolic parameters, including maximum standardised uptake value (SUVmax) and TLG, were measured. Receiver operating characteristic (ROC) analysis assessed the predictive performance of these parameters for pCR. Results: The pCR rate was 21.2% (7/33). Post-TNT TLG ≤ 10 demonstrated excellent predictive accuracy for pCR (AUC 0.887, 92.3% sensitivity, 85.7% specificity, and 96.0% PPV), outperforming SUVmax (AUC 0.843). Interim TLG ≤ 10 also showed a strong predictive value (AUC 0.824, 100% sensitivity, and 71.4% specificity). Conclusions: TLG may serve as a reliable metabolic biomarker for predicting pathologic complete response (pCR) after total neoadjuvant therapy (TNT) in locally advanced rectal cancer (LARC). Its inclusion in clinical decision-making could improve patient selection for organ preservation strategies, thereby reducing the need for unnecessary surgeries in the future. However, given that the study is based on a small retrospective design, the findings should be interpreted with caution and used alongside other decision-making tools until more comprehensive data are collected from larger studies. 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/Objectives: Pheochromocytomas and paragangliomas (PPGLs) are rare tumors of neural crest origin that secrete varying levels of catecholamines. [¹⁸F]Fluorodeoxyglucose-positron emission tomography (FDG-PET) is a valuable tool for the detection of metastases and the prediction of prognoses. However, varying FDG avidities in PPGLs raise concerns regarding cost-effectiveness and unnecessary radiation exposure. Catecholamine secretion patterns are associated with metastasis and clinical outcomes. This study aimed to explore the relationships among FDG avidity, catecholamine levels, and clinical factors in patients with PPGLs. Methods: This retrospective study included 25 patients with unresectable or metastatic PPGLs scheduled for [¹³¹I]metaiodobenzylguanidine therapy with FDG-PET data available within 40 days of urine catecholamine measurements. FDG avidity was assessed using semiquantitative parameters such as the maximum standardized uptake value (SUVmax), total metabolic tumor volume (MTV), and total lesion glycolysis (TLG). Urine catecholamine levels were quantified. Logistic regression and Spearman’s correlation were performed to evaluate the relationship between FDG parameters and urinary catecholamine levels. Results: Urinary noradrenaline levels were significantly higher in patients with FDG-avid lesions than in those without (726.25 μg/day vs. 166.3 μg/day, p = 0.001). Noradrenaline levels showed significant positive correlations with SUVmax, MTV, and TLG (ρ = 0.527, 0.541, and 0.557, respectively; all p < 0.01). Urinary noradrenaline levels predicted FDG avidity with an AUC of 0.849; a cutoff value of 647.5 μg/day achieved 55.6% sensitivity and 100% specificity. Conclusions: Urinary noradrenaline levels were significantly associated with FDG avidity in PPGLs, suggesting their potential utility in predicting FDG-PET outcomes. Therefore, FDG-PET may be unnecessary in PPGL patients with low urinary noradrenaline levels. These findings may help optimize imaging strategies for patients with PPGLs. Full article

Background. CXCR4 is a chemokine receptor that is frequently overexpressed in invasive breast cancer and plays a major role in tumor proliferation, aggressiveness and metastasis. The aim of this prospective study was to establish the value of CXCR4-directed PET imaging in patients with breast cancer using the novel CXCR4-targeted PET probe ⁶⁸Ga-Pentixafor by comparing it with ¹⁸F-FDG PET/CT (n = 40). Materials and methods. In this prospective cross-sectional study, fifty-one patients with breast cancer aged 36–81 (median (Q1-Q3) 51 (42.5–63)), n = 47 (92%) with initially diagnosed and n = 4 (8%) patients with recurrent breast cancer, underwent CXCR4-targeted PET imaging using ⁶⁸Ga-Pentixafor. Maximum standardized uptake values (SUVmax), total lesion glycolysis (TLG) or total lesion uptake (TLU), metabolic tumor volume (MTV) and tumor-to-background ratios (TBR) of tumor lesions were measured and correlated with pathological prognostic factors, molecular subtypes and CXCR4 immunohistochemistry (IHC) staining. ¹⁸F-FDG PET/CT images were available in 40 of 51 cases (82%) and were compared semi-quantitatively. The patients were followed up for a median of 11 months (range 4–80 months) to determine whether CXCR4 expression correlated with survival. Results. ⁶⁸Ga-Pentixafor-PET/CT was visually positive in 49/51 (96%) of the cases; in addition, [¹⁸F]FDG demonstrated a higher SUVmax compared to ⁶⁸Ga-Pentixafor. The mean SUVmax was 7.26 ± 2.84 and 18.8 ± 9.1 for ⁶⁸Ga-Pentixafor and [¹⁸F]FDG, respectively. Thirty-seven percent (18/51) of patients had triple-negative breast cancer and 25/51 (49%) had estrogen receptor (ER+) disease. There was a statistically significant correlation between tumor grade, proliferative index (Ki-67) and SUVmax obtained from ⁶⁸Ga-Pentixafor PET p = 0.002. There was no correlation between the SUVmax obtained from ⁶⁸Ga-Pentixafor and PET molecular subtypes, estrogen receptor (ER), progesterone receptor (PR) or human epidermal growth factor receptor 2 (HER2) status; however, triple-negative breast cancers had more avid ⁶⁸Ga-Pentixafor accumulation compared to luminals A and B. The median (Q1–Q3) ⁶⁸Ga-Pentixafor TLU was significantly higher in HIV-positive (376 (219–881)) compared to HIV-negative (174 (105–557)) breast cancer patients. Conclusions. In conclusion, ⁶⁸Ga-Pentixafor had a sensitivity of 96% and a specificity of 100% for detecting primary breast cancer; in addition, ⁶⁸Ga-Pentixafor exhibited significantly higher uptake in patients with higher tumor grade, high proliferative index and triple-negative breast cancer (TNBC), as well as HIV-infected breast cancer patients, highlighting the potential clinical utility and prognostic role of CXCR4-targeted PET imaging in aggressive breast cancer. Notably, ⁶⁸Ga-Pentixafor complements ¹⁸F-FDG by detecting more metastasis in the brain and the skull where FDG has limitations, while ¹⁸F-FDG remains superior for detecting skeletal metastasis. Future research should further explore the potential of CXCR4-targeted PET imaging in selecting patients with triple-negative breast cancer and high-grade breast cancer who may benefit from CXCR4-targeted therapies, particularly in the context of HIV co-infection. Full article

Aim: To assess the prognostic value of pretreatment ¹⁸F-FDG-PET/CT quantitative metabolic parameters in patients with advanced high-grade serous ovarian cancer (HGSOC). Methods: A review of 47 patients diagnosed with advanced HGSOC between 2012 and 2020 in our center was performed, evaluating pretreatment ¹⁸F-FDG-PET/CT metabolic parameters: maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG) and metabolic tumoral volume (MTV). Two experienced nuclear medicine physicians evaluated the images, thereby obtaining quantitative parameters semiautomatically classifying the volume of interest (VOI) as the target (t): VOI with the highest SUVmax normalized by lean body mass (SUVmax(lbm)), non target (nt) and total (sum of target and non-target VOIs). The disease-free survival (DFS) and overall survival (OS) were calculated. Optimal cutoff values with ROC curves/median values were used. The Correlation between metabolic parameters and DFS/OS was determined using univariate and survival-curves analysis. Results: The median DFS was 18 months (2.5–55) and the OS 33.6 months (2.5–92). The MTVtotal, MTV(t), TLGtotal and TLG(t) were significantly associated with DFS (p = 0.005, 0.01, 0.04 and 0.04, respectively). The patients with MTVtotal > 427.8 cm³ and MTVtarget > 434 cm³ had shorter DFS than the patients with lower values (18.8 versus 31 months and 15.6 versus 30, p = 0.02 and 0.01, respectively). The patients with higher TLGtotal and TLG(t) values tended to have worse DFS (p = 0.26 and 0.31, respectively). In a multivariate analysis, the MTVtotal was statistically significantly associated with DFS (p = 0.003). No correlation was found with OS. Conclusions: Pretreatment MTVtotal and MTV(t) appear to be predictive of relapse in patients with advanced HGSOC. Full article

Background: This study assessed the prognostic value of tumor burden in bone marrow (BM) and total disease (TD), as depicted on 18F-FDG PET/CT in 140 DLBCL patients, for complete remission after first-line systemic treatment (iCR) and 3- and 5-year overall survival (OS3 and OS5). Methods: Baseline 18F-FDG PET/CT scans of 140 DLBCL patients were segmented to quantify metabolic tumor volume (MTV), total lesion glycolysis (TLG), and SUVmax in BMI, findings elsewhere (XL), and TD. Results: Bone marrow involvement (BMI) presented in 35 (25%) patients. Median follow-up time was 47 months; 79 patients (56%) achieved iCR. iCR was significantly associated with TD MTV, XL MTV, BM PET positivity, and International Prognostic Index (IPI). OS3 was significantly worse with TD MTV, XL MTV, IPI, and age. OS5 was significantly associated with IPI, but not with MTVs and TLGs. Univariate factors predicting OS3 were XL MTV (hazard ratio [HR] = 1.29), BMI SUVmax (HR = 0.56), and IPI (HR = 1.92). By multivariate analysis, higher IPI (HR = 2.26) and BMI SUVmax (HR = 0.91) were significant independent predictors for OS3. BMI SUVmax resulted in a negative coefficient and hence indicated a protective effect. Conclusions: Baseline 18F-FDG PET/CT MTV is significantly associated with survival. BMI identified on 18F-FDG PET/CT allows appropriate treatment that may improve survival. Full article

Background/Objectives: The augmentation of [¹⁷⁷Lu]Lu-PSMA-617 radioligand therapy by alpha emitting [²²⁵Ac]Ac-PSMA-617, known as the tandem therapy concept, is a promising escalating treatment option in advanced mCRPC. In this study, we evaluated the value of [¹⁸F]FDG PET/CT-derived molecular imaging biomarkers for predicting response and outcome to PSMA tandem RLT in n = 33 patients with insufficient response on [¹⁷⁷Lu]Lu-PSMA-617 monotherapy. Methods: Six different molecular imaging parameters at baseline, i.e., before initiation of PSMA tandem RLT with respect to SUV_max, SUV_peak, SUV₅, SUV_mean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were tested for association with response and overall survival (OS). Results: After the initiation of augmentation, 24.2% of patients with a previously insufficient response experienced partial remission, and 39.4% experienced stable disease. The median OS was 7 months (95% CI: 4–11 months). None of the tested parameters were able to predict the response (all p > 0.529). In contrast, the [¹⁸F]FDG PET/CT-derived whole-body molecular imaging parameter TLG was significantly (p = 0.029) associated with OS of patients undergoing [²²⁵Ac]Ac-PSMA-617 augmented [¹⁷⁷Lu]Lu-PSMA-617 RLT after insufficient response to [¹⁷⁷Lu]Lu-PSMA-617 monotherapy. Conclusion: Implementing [¹⁸F]FDG PET/CT in the management of PSMA-RLT in clinical practice may contribute to outcome prediction and provide a route to more individualized management in mCRPC. Full article

Background: Positron emission tomography/computed tomography (PET/CT) with ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) is a firmly established tool in oncology and is gaining importance in dermato-oncology. However, its use in advanced basal cell carcinoma (BCC) is limited, with only a few case reports and a single study focused on vismodegib. This study evaluates the role of ¹⁸F-FDG PET/CT in advanced BCC treated with sonidegib. Methods: We retrospectively assessed the clinical data of patients with advanced BCC who underwent ¹⁸F-FDG PET/CT between January 2022 and January 2024. Inclusion criteria included histologically confirmed BCC, FDG-avid lesions on baseline PET/CT, and a minimum follow-up of 6 months. Metabolic response was assessed using the PET Response Criteria in Solid Tumors (PERCIST). Results: Four patients with advanced BCC treated with sonidegib were included, presenting with a total of 10 hypermetabolic lesions at baseline PET/CT. The mean interval between baseline and follow-up scans was 8.7 ± 1.6 months. According to PERCIST, two patients achieved a complete metabolic response (CMR), while the other two had stable metabolic disease (SMD). Low baseline-standardized uptake values (i.e., SUVmax, SUVmean) and reduced total lesion glycolysis (TLG) were associated with CMR. No relapses were observed during follow-up. Conclusions: This study suggests that ¹⁸F-FDG PET/CT may help identify advanced BCC patients who are likely to benefit from sonidegib treatment. Further research is needed to fully explore the potential of PET/CT in this specific clinical context. Full article

Background/Objectives: The inhibitory effects of tyrosine kinase inhibitors (TKIs) on glucose uptake through their binding to human glucose transporter-1 (GLUT-1) have been well documented. Thus, our research aimed to explore the potential impact of various TKIs of GLUT-1 on the standard [¹⁸F]FDG-PET monitoring of tumor response in patients. Methods: To achieve this, we conducted an analysis on three patients who were undergoing treatment with different TKIs and harbored actionable alterations. Alongside the assessment of FDG data (including SUVmax, total lesion glycolysis (TLG), and metabolic tumor volume (MTV)), we also examined the changes in tumor sizes through follow-up [¹⁸F]FDG-PET/CT imaging. Notably, our patients harbored alterations in BRAFV600, RET, and c-KIT and exhibited positive responses to the targeted treatment. Results: Our analysis revealed that FDG data derived from SUVmax, TLG, and MTV offered quantifiable outcomes that were consistent with the measurements of tumor size. Conclusions: These findings lend support to the notion that the inhibition of GLUT-1, as a consequence of treatment efficacy, could be indirectly gauged through [¹⁸F] FDG-PET/CT imaging in cancer patients undergoing TKI therapy. Full article

Objectives: Accurate outcome prediction is important for making informed clinical decisions in cancer treatment. In this study, we assessed the feasibility of using changes in radiomic features over time (Delta radiomics: absolute and relative) following chemotherapy, to predict relapse/progression and time to progression (TTP) of primary mediastinal large B-cell lymphoma (PMBCL) patients. Material and Methods: Given the lack of standard staging PET scans until 2011, only 31 out of 103 PMBCL patients in our retrospective study had both pre-treatment and end-of-treatment (EoT) scans. Consequently, our radiomics analysis focused on these 31 patients who underwent [¹⁸F]FDG PET-CT scans before and after R-CHOP chemotherapy. Expert manual lesion segmentation was conducted on their scans for delta radiomics analysis, along with an additional 19 EoT scans, totaling 50 segmented scans for single time point analysis. Radiomics features (on PET and CT), along with maximum and mean standardized uptake values (SUVmax and SUVmean), total metabolic tumor volume (TMTV), tumor dissemination (Dmax), total lesion glycolysis (TLG), and the area under the curve of cumulative standardized uptake value-volume histogram (AUC-CSH) were calculated. We additionally applied longitudinal analysis using radial mean intensity (RIM) changes. For prediction of relapse/progression, we utilized the individual coefficient approximation for risk estimation (ICARE) and machine learning (ML) techniques (K-Nearest Neighbor (KNN), Linear Discriminant Analysis (LDA), and Random Forest (RF)) including sequential feature selection (SFS) following correlation analysis for feature selection. For TTP, ICARE and CoxNet approaches were utilized. In all models, we used nested cross-validation (CV) (with 10 outer folds and 5 repetitions, along with 5 inner folds and 20 repetitions) after balancing the dataset using Synthetic Minority Oversampling TEchnique (SMOTE). Results: To predict relapse/progression using Delta radiomics between the baseline (staging) and EoT scans, the best performances in terms of accuracy and F1 score (F1 score is the harmonic mean of precision and recall, where precision is the ratio of true positives to the sum of true positives and false positives, and recall is the ratio of true positives to the sum of true positives and false negatives) were achieved with ICARE (accuracy = 0.81 ± 0.15, F1 = 0.77 ± 0.18), RF (accuracy = 0.89 ± 0.04, F1 = 0.87 ± 0.04), and LDA (accuracy = 0.89 ± 0.03, F1 = 0.89 ± 0.03), that are higher compared to the predictive power achieved by using only EoT radiomics features. For the second category of our analysis, TTP prediction, the best performer was CoxNet (LASSO feature selection) with c-index = 0.67 ± 0.06 when using baseline + Delta features (inclusion of both baseline and Delta features). The TTP results via Delta radiomics were comparable to the use of radiomics features extracted from EoT scans for TTP analysis (c-index = 0.68 ± 0.09) using CoxNet (with SFS). The performance of Deauville Score (DS) for TTP was c-index = 0.66 ± 0.09 for n = 50 and 0.67 ± 03 for n = 31 cases when using EoT scans with no significant differences compared to the radiomics signature from either EoT scans or baseline + Delta features (p-value> 0.05). Conclusion: This work demonstrates the potential of Delta radiomics and the importance of using EoT scans to predict progression and TTP from PMBCL [¹⁸F]FDG PET-CT scans. Full article

The aim of our study was to predict the occurrence of distant metastases in non-small-cell lung cancer (NSCLC) patients using machine learning methods and texture analysis of ¹⁸F-labeled 2-deoxy-d-glucose Positron Emission Tomography/Computed Tomography {[¹⁸F]FDG PET/CT} images. In this retrospective and single-center study, we evaluated 79 patients with advanced NSCLC who had undergone [¹⁸F]FDG PET/CT scan at diagnosis before any therapy. Patients were divided into two independent training (n = 44) and final testing (n = 35) cohorts. Texture features of primary tumors and lymph node metastases were extracted from [¹⁸F]FDG PET/CT images using the LIFEx program. Six machine learning methods were applied to the training dataset using the entire panel of features. Dedicated selection methods were used to generate different combinations of five features. The performance of selected machine learning methods applied to the different combinations of features was determined using accuracy, the confusion matrix, receiver operating characteristic (ROC) curves, and area under the curve (AUC). A total of 104 and 78 lesions were analyzed in the training and final testing cohorts, respectively. The support vector machine (SVM) and decision tree methods showed the highest accuracy in the training cohort. Seven combinations of five features were obtained and introduced in the models and subsequently applied to the training and final testing cohorts using the SVM and decision tree. The accuracy and the AUC of the decision tree method were higher than those obtained with the SVM in the final testing cohort. The best combination of features included shape sphericity, gray level run length matrix_run length non-uniformity (GLRLM_RLNU), Total Lesion Glycolysis (TLG), Metabolic Tumor Volume (MTV), and shape compacity. The combination of these features with the decision tree method could predict the occurrence of distant metastases with an accuracy of 74.4% and an AUC of 0.63 in NSCLC patients. Full article

Background and Objectives: Chronic lymphocytic leukemia (CLL) is the most common type of leukemia in developed countries, which can evolve into aggressive lymphoma variants, a process called Richter transformation (RT). The aim of this retrospective study was to analyze the role of 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (2-[18F]-FDG PET/CT) and its semiquantitative and radiomics features in detecting RT and evaluate the impact on overall survival (OS). Materials and Methods: One hundred and thirty-seven patients with histologically proven CLL were retrospectively recruited. PET/CT images were qualitatively and semiquantitatively examined by estimating the main metabolic parameters (the maximum standardized uptake value body weight (SUVbw), lean body mass (SUVlbm), body surface area (SUVbsa), lesion-to-blood-pool SUV ratio (L-BP SUV R), lesion-to-liver SUV ratio (L-L SUV R), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) and radiomics first- and second- order variables of the lesion with highest uptake. The role of these parameters in predicting RT and OS was analyzed. Results: One hundred and thirty (95%) PET/CT scans were positive, showing an increased tracer uptake at the site of disease, whereas the remaining 7 (5%) scans were negative. SUVbw, SUVlbm, SUVbsa, L-L SUV ratio, and L-BP SUV ratio were significantly higher in the RT group (p < 0.001 in all cases). Radiomics first- and second-order features were not significantly associated with RT. After a median follow-up of 44 months, 56 patients died; OS was significantly shorter in patients with RT than patients without RT (28 vs. 34 months; p = 0.002). Binet-stage, RT, and L-BP SUV R were shown to be independent prognostic features. Conclusions: Semiquantitative PET/CT parameters such as SUVbw, SUVlbm, SUVbsa, L-L SUV ratio and L-BP SUV ratio may be useful in discriminating patients with a high risk of developing RT, whereas Binet-stage, RT, and L-BP SUV R are also significant in predicting OS. 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

The primary objective of this study was to investigate the potential role of tissue osteopontin, also known as secreted phosphoprotein 1 (SPP1), as a contributing factor to an unfavorable prognosis in classical Hodgkin’s lymphoma (HL) patients who received the same treatment protocol. The study involved 44 patients aged 4–22 years, with a median follow-up period of 3 years. Patients with higher levels of SPP1 were associated with tissue necrosis and inflammation, and there was a trend toward a poorer prognosis in this group. Before therapy, we found a correlation between positron emission tomography (PET) scans and logarithmic SPP1 levels (p = 0.035). However, the addition of SPP1 levels did not significantly enhance the predictive capacity of PET scans for recurrence or progression. Elevated SPP levels were associated with tissue mRNA counts of chemotactic and inflammatory chemokines, as well as specific monocyte/dendritic cell subtypes, defined by IL-17RB, PLAUR, CXCL8, CD1A, CCL13, TREM1, and CCL24 markers. These findings contribute to a better understanding of the potential factors influencing the prognosis of HL patients and the potential role of SPP1 in the disease. While the predictive accuracy of PET scans did not substantially improve during the study, the results underscore the complexity of HL and highlight the relationships between SPP1 and other factors in the context of HL relapse. Full article