Prognostic role of baseline 18F-FDG PET/CT metabolic parameters in mantle cell lymphoma

Clinical Application of 18F-FDG-PET Quantification in Hematological Malignancies: Emphasizing Multiple Myeloma, Lymphoma and Chronic Lymphocytic Leukemia

Most hematological malignancies display heightened glycolytic activity, leading to their detectability through 18F-FDG-PET imaging. PET quantification enables the extraction of metabolic information from tumors. Among various PET measurements, maximum standardized uptake value (SUVmax), which indicates the highest value of 18F-FDG uptake within the tumor, has emerged as the commonly used parameter in clinical oncology. This is because of SUVmax ease of calculation using most available commercial workstations, as well as its simplicity and independence from observer interpretation. Nonetheless, SUVmax represents the increase in activity within a specific small area, which may not fully capture the overall tumor uptake. Volumetric PET parameters have been identified as a potential solution to overcome certain limitations associated with SUVmax. However, these parameters are influenced by the low spatial resolution of PET when assessing small lesions. Another challenge is the high number of lesions observed in some patients, leading to a time-consuming process for evaluating all focal lesions. Some institutions recently have started advocating for CT-based segmentation as a method for measuring radiotracer uptake in the bone marrow and overall bone of the patients. This review article aims to provide insights into clinical application of PET quantification specifically focusing on 3 major hematologic malignancies: multiple myeloma, lymphoma, and chronic lymphocytic leukemia.

The diagnostic value of dual-layer CT in the assessment of lymph nodes in lymphoma patients with PET/CT as a reference standard

This study aimed to evaluate the diagnostic performances of dual-layer CT (DLCT) for the identification of positive lymph nodes (LNs) in patients with lymphoma and retrospectively included 1165 LNs obtained by biopsy from 78 patients with histologically proven lymphoma, who underwent both pretreatment DLCT and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). According to 18F-FDG PET/CT findings as a reference standard, cases were categorized into the LN-negative and LN-positive groups. LNs were then randomly divided at a ratio of 7:3 into the training (n = 809) and validation (n = 356) cohorts. The patients' clinical characteristics and quantitative parameters including spectral curve slope (λHU), iodine concentration (IC) on arterial phase (AP) and venous phase (VP) images were compared between the LN-negative and LN-positive groups using Chi-square test, t-test or Mann-Whitney U test for categorical variables or quantitative parameters. Multivariate logistic regression analysis with tenfold cross-validation was performed to establish the most efficient predictive model in the training cohort. The area under the curve (AUC) was used to evaluate the diagnostic value of the predictive model, and differences in AUC were determined by the DeLong test. Moreover, the predictive model was validated in the validation cohort. Repeatability analysis was performed for LNs using intraclass correlation coefficients (ICCs). In the training cohort, long diameter (LD) had the highest AUC as an independent factors compared to other parameter in differentiating LN positivity from LN negativity (p = 0.006 to p < 0.001), and the AUC of predictive model jointly involving LD and λHU-AP was significantly elevated (AUC of 0.816, p < 0.001). While the AUC of predictive model in the validation cohort was 0.786. Good to excellent repeatability was observed for all parameters (ICC > 0.75). The combination of DLCT with morphological and functional parameters may represent a potential imaging biomarker for detecting LN positivity in lymphoma.

Performance of baseline FDG-PET/CT radiomics for prediction of bone marrow minimal residual disease status in the LyMa-101 trial

The prognostic value of 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) at baseline or the predictive value of minimal residual disease (MRD) detection appear as potential tools to improve mantle cell lymphoma (MCL) patients' management. The LyMa-101, a phase 2 trial of the LYSA group (ClinicalTrials.gov:NCT02896582) reported induction therapy with obinutuzumab, a CD20 monoclonal antibody. Herein, we investigated the added prognostic value of radiomic features (RF) derived from FDG-PET/CT at diagnosis for MRD value prediction. FDG-PET/CT of 59 MCL patients included in the LyMa-101 trial have been independently, blindly and centrally reviewed. RF were extracted from the disease area with the highest uptake and from the total metabolic tumor volume (TMTV). Two models of machine learning were used to compare several combinations for prediction of MRD before autologous stem cell transplant consolidation (ASCT). Each algorithm was generated with or without constrained feature selections for clinical and laboratory parameters. Both algorithms showed better discrimination performances for negative vs positive MRD in the lesion with the highest uptake than in the TMTV. The constrained use of clinical and biological features showed a clear loss in sensitivity for the prediction of MRD status before ASCT, regardless of the machine learning model. These data plead for the importance of FDG-PET/CT RF compared to clinical and laboratory parameters and also reinforced the previously made hypothesis that the prognosis of the disease in MCL patients is linked to the most aggressive contingent, within the lesion with the highest uptake.

Radiomics predictive modeling from dual-time-point FDG PET Ki parametric maps: application to chemotherapy response in lymphoma

BACKGROUND

To investigate the use of dynamic radiomics features derived from dual-time-point (DTP-feature) [¹⁸F]FDG PET metabolic uptake rate K_i parametric maps to develop a predictive model for response to chemotherapy in lymphoma patients.

METHODS

We analyzed 126 lesions from 45 lymphoma patients (responding n = 75 and non-responding n = 51) treated with chemotherapy from two different centers. Static and DTP radiomics features were extracted from baseline static PET images and DTP K_i parametric maps. Spearman's rank correlations were calculated between static and DTP features to identify features with potential additional information. We first employed univariate analysis to determine correlations between individual features, and subsequently utilized multivariate analysis to derive predictive models utilizing DTP and static radiomics features before and after ComBat harmonization. For multivariate modeling, we utilized both the minimum redundancy maximum relevance feature selection technique and the XGBoost classifier. To evaluate our model, we partitioned the patient datasets into training/validation and testing sets using an 80/20% split. Different metrics for classification including area under the curve (AUC), sensitivity (SEN), specificity (SPE), and accuracy (ACC) were reported in test sets.

RESULTS

Via Spearman's rank correlations, there was negligible to moderate correlation between 32 out of 65 DTP features and some static features (ρ < 0.7); all the other 33 features showed high correlations (ρ ≥ 0.7). In univariate modeling, no significant difference between AUC of DTP and static features was observed. GLRLM_RLNU from static features demonstrated a strong correlation (AUC = 0.75, p value = 0.0001, q value = 0.0007) with therapy response. The most predictive DTP features were GLCM_Energy, GLCM_Entropy, and Uniformity, each with AUC = 0.73, p value = 0.0001, and q value < 0.0005. In multivariate analysis, the mean ranges of AUCs increased following harmonization. Use of harmonization plus combining DTP and static features was shown to provide significantly improved predictions (AUC = 0.97 ± 0.02, accuracy = 0.89 ± 0.05, sensitivity = 0.92 ± 0.09, and specificity = 0.88 ± 0.05). All models depicted significant performance in terms of AUC, ACC, SEN, and SPE (p < 0.05, Mann-Whitney test).

CONCLUSIONS

Our results demonstrate significant value in harmonization of radiomics features as well as combining DTP and static radiomics models for predicting response to chemotherapy in lymphoma patients.

Prognostic value of the International Metabolic Prognostic Index for lymphoma patients receiving chimeric antigen receptor T-cell therapy

PURPOSE

Chimeric antigen receptor T-cell therapy (CART) prolongs survival for patients with relapsed/refractory B-cell non-Hodgkin's lymphoma. The recently introduced International Metabolic Prognostic Index (IMPI) was shown to improve prognostication in the first-line treatment of large B-cell lymphoma. Here, we investigate the prognostic value of the IMPI for progression-free (PFS) and overall survival (OS) in the setting of CD19 CART.

METHODS

Consecutively treated patients with baseline ¹⁸F-FDG PET/CT imaging and follow-up imaging at 30 days after CART were included. IMPI is composed of age, stage, and metabolic tumor volume (MTV) at baseline and was compared with the International Prognostic Index (IPI). Both indices were grouped into quartiles, as previously described for IPI. In addition, the continuous IMPI was subdivided into tertiaries for better separation of risk groups. Overall response rate (ORR), depth of response (DoR), and PFS were determined based on Lugano criteria. Proportional Cox regression analysis studied association of IMPI and IPI with PFS and OS.

RESULTS

Thirty-nine patients were included. The IPI was 1 in 23%, 2 in 21%, 3 in 26%, 4 in 21%, and 5 in 10% of the patients. IMPI^{low risk}, IMPI^{intermediate risk}, and IMPI^{high risk} patients had 30-day ORR of 69%, 62%, and 62% and 30-day DoR of - 67%, - 66%, and - 54% with a PFS of 187 days, 97 days, and 87 days, respectively. ORR and DoR showed no correlation with lower IMPI (r = 0.065, p = 0.697). Dividing patients into three risk groups showed a significant trend for PFS stratification (p = 0.030), while IPI did not (p = 0.133). Neither IPI nor IMPI yielded a significant association with OS after CART (both p > 0.05).

CONCLUSION

In the context of CART, the IMPI yielded prognostic value regarding PFS estimation. In contrast with IMPI in the first-line DLBCL setting, we did not observe a significant association of IMPI at baseline with OS after CART.

[18F]FDG-PET/CT volumetric parameters can predict outcome in untreated mantle cell lymphoma

Several studies have shown a strong predictive value for pretreatment [¹⁸F]FDG-PET/CT metabolic parameters in different lymphoma subtypes. However, few publications exist concerning the role of metabolic parameters in mantle cell lymphoma (MCL). We retrospectively investigated the prognostic value of baseline metabolic tumor volume (MTV) and lesion dissemination in untreated MCL. We compared it to currently used prognostic factors such as stage, mantle cell lymphoma international prognostic index (MIPI) and KI-67. We report that a higher baseline MTV is a risk factor for worse overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS) in univariate analysis. In multivariate analysis, MTV was significantly associated with DSS, but not with OS and PFS. We found no correlation between lesion dissemination and outcome. The MIPI score remains the strongest predictor of outcome. These results show that MTV is an important prognostic tool and can improve patient risk stratification at staging of untreated MCL.

Application of the Lugano Classification for Initial Evaluation, Staging, and Response Assessment of Hodgkin and Non-Hodgkin Lymphoma: The PRoLoG Consensus Initiative (Part 1-Clinical)

Our objective was to provide consensus recommendations from a consortium of academic and industry experts in the field of lymphoma and imaging for consistent application of the Lugano classification. Methods: Consensus was obtained through a series of meetings from July 2019 until September 2021 sponsored by the Pharma Imaging Network for Therapeutics and Diagnostics (PINTaD) as part of the PINTaD Response Criteria in Lymphoma Working Group (PRoLoG) consensus initiative. Results: Consensus recommendations clarified technical considerations for PET/CT and diagnostic CT from the Lugano classification, including updating the FDG avidity of different lymphoma entities, clarifying the response nomenclature, and refining lesion classification and scoring, especially with regard to scores 4 and 5 and the X category of the 5-point scale. Combination of metabolic and anatomic responses is clarified, as well as response assessment in cases of discordant or missing evaluations. Use of clinical data in the classification, especially the requirement for bone marrow assessment, is further updated on the basis of lymphoma entities. Clarification is provided with regard to spleen and liver measurements and evaluation, as well as nodal response. Conclusion: Consensus recommendations are made to comprehensively address areas of inconsistency and ambiguity in the classification encountered during response evaluation by end users, and such guidance should be used as a companion to the 2014 Lugano classification.

Prospective Evaluation of Different Methods for Volumetric Analysis on [18F]FDG PET/CT in Pediatric Hodgkin Lymphoma

Rationale: Therapy response evaluation by 18F-fluorodeoxyglucose PET/CT (FDG PET) has become a powerful tool for the discrimination of responders from non-responders in pediatric Hodgkin lymphoma (HL). Recently, volumetric analyses have been regarded as a valuable tool for disease prognostication and biological characterization in cancer. Given the multitude of methods available for volumetric analysis in HL, the AIEOP Hodgkin Lymphoma Study Group has designed a prospective analysis of the Italian cohort enrolled in the EuroNet-PHL-C2 trial. Methods: Primarily, the study aimed to compare the different segmentation techniques used for volumetric assessment in HL patients at baseline (PET1) and during therapy: early (PET2) and late assessment (PET3). Overall, 50 patients and 150 scans were investigated for the current analysis. A dedicated software was used to semi-automatically delineate contours of the lesions by using different threshold methods. More specifically, four methods were applied: (1) fixed 41% threshold of the maximum standardized uptake value (SUVmax) within the respective lymphoma site (V41%), (2) fixed absolute SUV threshold of 2.5 (V2.5); (3) SUVmax(lesion)/SUVmean liver >1.5 (Vliver); (4) adaptive method (AM). All parameters obtained from the different methods were analyzed with respect to response. Results: Among the different methods investigated, the strongest correlation was observed between AM and Vliver (rho > 0.9; p < 0.001 for SUVmean, MTV and TLG at all scan timing), along with V2.5 and AM or Vliver (rho 0.98, p < 0.001 for TLG at baseline; rho > 0.9; p < 0.001 for SUVmean, MTV and TLG at PET2 and PET3, respectively). To determine the best segmentation method, we applied logistic regression and correlated different results with Deauville scores at late evaluation. Logistic regression demonstrated that MTV (metabolic tumor volume) and TLG (total lesion glycolysis) computation according to V2.5 and Vliver significantly correlated to response to treatment (p = 0.01 and 0.04 for MTV and 0.03 and 0.04 for TLG, respectively). SUVmean also resulted in significant correlation as absolute value or variation. Conclusions: The best correlation for volumetric analysis was documented for AM and Vliver, followed by V2.5. The volumetric analyses obtained from V2.5 and Vliver significantly correlated to response to therapy, proving to be preferred thresholds in our pediatric HL cohort.

Longitudinal Body Composition Changes Detected by [18F]FDG PET/CT during and after Chemotherapy and Their Prognostic Role in Elderly Hodgkin Lymphoma

The aim of this retrospective study was to investigate the longitudinal body changes in terms of muscle and adipose areas and their prognostic role in elderly (>65 years) patients affected by Hodgkin lymphoma (HL). Skeletal muscle area (SMA), skeletal muscle index (SMI), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intramuscular adipose tissue (IMAT), and total dispose tissue (TAT) were measured using the computed tomography (CT) of fluorine-18-fluorodeoxyglucose positron emission tomography/CT ([18F]FDG PET/CT) in 88 patients who undertook baseline, interim (after two cycles of chemotherapy), and end-of-treatment (after 6 cycles of chemotherapy) PET/CT scans. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured at pre-treatment PET/CT. Metabolic response applying Deauville score was evaluated at interim and end-of-treatment PET/CT. Survival curves, such as progression free survival (PFS) and overall survival (OS), were calculated for the whole population. Fifty-eight (66%) patients had sarcopenia at baseline and sarcopenia rate increased at interim scan with 68 (77%) cases and at end-of-treatment scan with 73 (83%) cases. Muscular areas (SMA and SMI) declined significantly during the treatment (p < 0.001), decreasing from baseline by 5% and 7% at interim and end-of-treatment evaluation, respectively. Instead, VAT, SAT, IMAT, and TAT increased significantly over this time (p < 0.001). Sarcopenia was significantly related with comprehensive geriatric assessment. PET/CT response at interim and end-of-treatment, MTV, TLG, and baseline sarcopenia were independent prognostic factors for PFS. Instead, metabolic response at interim and end-of-treatment PET, baseline sarcopenia, ΔSMI at interim, and ΔSMI at end-of-treatment for OS were independent prognostic factors.

Treatment of Mantle Cell Lymphoma in the Frontline Setting: Are We Ready for a Risk-Adapted Approach?

Mantle cell lymphoma (MCL), a type of B-cell non-Hodgkin lymphoma characterized by the t(11;14)(q13q32) translocation, is a clinically heterogenous disease which can range from indolent to highly aggressive. Numerous prognostic factors have been identified, including blastoid histology, the Mantle Cell Lymphoma International Prognostic Index (MIPI) score, high proliferation index, p53 deletions and/or mutations, complex karyotype, minimal residual disease, and several others. However, using these prognostic factors to guide treatment selection has largely remained elusive. Given the heterogeneous behavior of this disease and varying patient characteristics, we suggest that the time has come for a more risk-adapted approach to this disease. In this article, we review the numerous prognostic factors that have been described for MCL, both at the time of diagnosis and following first-line treatment. We then propose a risk-adapted approach to first-line therapy for MCL, which would reserve intensive therapy for the highest risk patients and spare others excessive toxicity.

Deep Neural Networks and Machine Learning Radiomics Modelling for Prediction of Relapse in Mantle Cell Lymphoma

Simple Summary

Mantle cell lymphoma (MCL) is an aggressive lymphoid tumour with a poor prognosis. There exist no routine biomarkers for the early prediction of relapse. Our study compared the potential of radiomics-based machine learning and 3D deep learning models as non-invasive biomarkers to risk-stratify MCL patients, thus promoting precision imaging in clinical oncology.

Abstract

Mantle cell lymphoma (MCL) is a rare lymphoid malignancy with a poor prognosis characterised by frequent relapse and short durations of treatment response. Most patients present with aggressive disease, but there exist indolent subtypes without the need for immediate intervention. The very heterogeneous behaviour of MCL is genetically characterised by the translocation t(11;14)(q13;q32), leading to Cyclin D1 overexpression with distinct clinical and biological characteristics and outcomes. There is still an unfulfilled need for precise MCL prognostication in real-time. Machine learning and deep learning neural networks are rapidly advancing technologies with promising results in numerous fields of application. This study develops and compares the performance of deep learning (DL) algorithms and radiomics-based machine learning (ML) models to predict MCL relapse on baseline CT scans. Five classification algorithms were used, including three deep learning models (3D SEResNet50, 3D DenseNet, and an optimised 3D CNN) and two machine learning models based on K-nearest Neighbor (KNN) and Random Forest (RF). The best performing method, our optimised 3D CNN, predicted MCL relapse with a 70% accuracy, better than the 3D SEResNet50 (62%) and the 3D DenseNet (59%). The second-best performing method was the KNN-based machine learning model (64%) after principal component analysis for improved accuracy. Our optimised CNN developed by ourselves correctly predicted MCL relapse in 70% of the patients on baseline CT imaging. Once prospectively tested in clinical trials with a larger sample size, our proposed 3D deep learning model could facilitate clinical management by precision imaging in MCL.

Prognostic Value of Heterogeneity Index Derived from Baseline 18F-FDG PET/CT in Mantle Cell Lymphoma

Objectives

Mantle cell lymphoma (MCL) represents a group of highly heterogeneous tumors, leading to a poor prognosis. Early prognosis prediction may guide the choice of therapeutic regimen. Thus, the purpose of this study was to investigate the potential application value of heterogeneity index (HI) in predicting the prognosis of MCL.

Methods

A total of 83 patients with histologically proven MCL who underwent baseline fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) were retrospectively enrolled. The clinicopathologic index and PET/CT metabolic parameters containing maximum and mean standard uptake value (SUVmax and SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and HI were evaluated. Receiver operating characteristic (ROC) curve analyses were performed to determine the optimal cutoff values of the parameters for progression-free survival (PFS) and overall survival (OS). Univariate and multivariate Cox regression were used to assess relationships between risk factors and recurrence. Kaplan–Meier plots were applied for survival analyses.

Results

In univariate analyses, age [HR = 2.51, 95% CI = 1.20–5.24, p = 0.041 for body weight (BW)] and HI-BW (HR = 4.17, 95% CI = 1.00–17.38, p = 0.050) were significantly correlated with PFS. In multivariate analyses, age (HR = 2.61, 95% CI = 1.25–5.47, p = 0.011 for BW) and HI-BW (HR = 4.41, 95% CI = 1.06–18.41, p = 0.042) were independent predictors for PFS, but not for OS. B symptoms (HR = 5.00, 95% CI = 1.16–21.65, p = 0.031 for BW) were an independent prognostic factor for OS, but not for PFS. The other clinicopathologic index and PET/CT metabolic parameters were not related to outcome survival in MCL.

Conclusion

The age and HI derived from baseline PET/CT parameters were significantly correlated with PFS in MCL patients.

Lesion-Based Radiomics Signature in Pretherapy 18F-FDG PET Predicts Treatment Response to Ibrutinib in Lymphoma

PURPOSE

The aim of this study was to develop a pretherapy PET/CT-based prediction model for treatment response to ibrutinib in lymphoma patients.

PATIENTS AND METHODS

One hundred sixty-nine lymphoma patients with 2441 lesions were studied retrospectively. All eligible lymphomas on pretherapy 18F-FDG PET images were contoured and segmented for radiomic analysis. Lesion- and patient-based responsiveness to ibrutinib was determined retrospectively using the Lugano classification. PET radiomic features were extracted. A radiomic model was built to predict ibrutinib response. The prognostic significance of the radiomic model was evaluated independently in a test cohort and compared with conventional PET metrics: SUVmax, metabolic tumor volume, and total lesion glycolysis.

RESULTS

The radiomic model had an area under the receiver operating characteristic curve (ROC AUC) of 0.860 (sensitivity, 92.9%, specificity, 81.4%; P < 0.001) for predicting response to ibrutinib, outperforming the SUVmax (ROC AUC, 0.519; P = 0.823), metabolic tumor volume (ROC AUC, 0.579; P = 0.412), total lesion glycolysis (ROC AUC, 0.576; P = 0.199), and a composite model built using all 3 (ROC AUC, 0.562; P = 0.046). The radiomic model increased the probability of accurately predicting ibrutinib-responsive lesions from 84.8% (pretest) to 96.5% (posttest). At the patient level, the model's performance (ROC AUC = 0.811; P = 0.007) was superior to that of conventional PET metrics. Furthermore, the radiomic model showed robustness when validated in treatment subgroups: first (ROC AUC, 0.916; P < 0.001) versus second or greater (ROC AUC, 0.842; P < 0.001) line of defense and single treatment (ROC AUC, 0.931; P < 0.001) versus multiple treatments (ROC AUC, 0.824; P < 0.001).

CONCLUSIONS

We developed and validated a pretherapy PET-based radiomic model to predict response to treatment with ibrutinib in a diverse cohort of lymphoma patients.

Prognostic Role of Pre-Treatment Metabolic Parameters and Sarcopenia Derived by 2-[18F]-FDG PET/CT in Elderly Mantle Cell Lymphoma

The goal of this retrospective study was to analyze and compare the prognostic role of fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (2-[¹⁸F]-FDG PET/CT) features and sarcopenia, estimated by CT of PET in elderly (≥65 years) Mantle Cell Lymphoma (MCL). We recruited 53 patients, who underwent pre-treatment 2-[¹⁸F]-FDG PET/CT and end-of-treatment PET/CT, and the main semiquantitative parameters were calculated. Sarcopenia was measured as skeletal muscle index (SMI, cm²/m²) and derived by low-dose PET/CT images at the L3 level. Specific cut-offs for SMI were calculated by receiver operator curve and divided by gender. Metabolic response was evaluated at end-of-treatment PET/CT, applying the Deauville score. Progression Free Survival (PFS) and Overall Survival (OS) were calculated for the whole population and for different subgroups, defined as per different sarcopenia cut-off levels. The specific cut-offs to define sarcopenia were 53 cm²/m² for male and 45.6 cm²/m² for female. Thirty-two (60%) patients were defined as sarcopenic. The 3-year and 5-year PFS rates were 29% and 23%, while the 3-year and 5-year OS rates were 43% and 33%. Metabolic response, total metabolic tumor volume (tMTV), total lesion glycolysis (tTLG) and sarcopenia were independent prognostic factors for PFS. Considering OS, no variable was significantly associated. Combination between PET features and sarcopenia may help to predict PFS.

Circulating Tumor DNA Predicts Therapeutic Outcome in Mantle Cell Lymphoma

Early changes in ctDNA dynamics are prognostic in untreated MCL.

Bortezomib maintenance after bortezomib-based induction therapy does not improve outcome in untreated MCL.

Mantle cell lymphoma (MCL) is biologically and clinically heterogeneous and would benefit from prognostic biomarkers to guide management. Circulating tumor DNA (ctDNA) is a novel prognostic biomarker in diffuse large B-cell lymphoma that may have applicability in MCL. We analyzed ctDNA dynamics in previously untreated patients with MCL who received induction therapy with bortezomib and DA-EPOCH-R for 6 cycles followed by random assignment to observation or bortezomib maintenance in responding patients in a prospective phase 2 study. Most patients also underwent initial treatment window of bortezomib alone prior to induction. Serum was collected pretreatment, after the window, after cycles 1 and 2, at the end of induction, and at each follow-up visit along with restaging computed tomography scans. Next-generation sequencing was used to identify and quantify ctDNA encoding the immunoglobulin receptor sequences in serum as markers of minimal residual disease. Fifty-three patients were enrolled, with a median follow-up of 12.7 years. Patients without detectable ctDNA after 2 cycles of induction had longer progression-free survival (PFS) and overall survival (OS) compared with those with detectable ctDNA (median PFS, 2.7 vs 1.8 years; overall P = .005; median OS, 13.8 vs 7.4 years; overall P = .03). Notably, in vivo assessment of ctDNA dynamics during the bortezomib window was not prognostic, and there was no difference in PFS or OS with bortezomib maintenance. ctDNA monitoring after induction showed that molecular relapse preceded clinical relapse in some cases. In conclusion, interim ctDNA negativity strongly correlates with improved survival and supports the investigation of response-adapted strategies. This trial was registered at www.clinicaltrials.gov as #NCT00114738.

Pre-treatment total metabolic tumour volumes in lymphoma: Does quantity matter?

Positron emission tomography/computed tomography (PET/CT) is used for the staging of lymphomas. Clinical information, such as Ann Arbor stage and number of involved sites, is derived from baseline staging and correlates with tumour volume. With modern imaging software, exact measures of total metabolic tumour volumes (tMTV) can be determined, in a semi- or fully-automated manner. Several technical factors, such as tumour segmentation and PET/CT technology influence tMTV and there is no consensus on a standardized uptake value (SUV) thresholding method, or how to include the volumes in the bone marrow and spleen. In diffuse large B-cell lymphoma, follicular lymphoma, peripheral T-cell lymphoma, and Hodgkin lymphoma, tMTV has been shown to predict progression-free survival and/or overall survival, after adjustments for clinical risk scores. However, most studies have used receiver operating curves to determine the optimal cut-off for tMTV and many studies did not include a training-validation approach, which led to the risk of overestimation of the independent prognostic value of tMTV. The identified cut-off values are heterogeneous, even when the same SUV thresholding method is used. Future studies should focus on testing tMTV in homogeneously-treated cohorts and seek to validate identified cut-off values externally so that a prognostic value can be documented, over and above currently used clinical surrogates for tumour volume.

Metabolic tumour volume on 18F-FDG PET/CT predicts extended pathological T stages in patients with renal cell carcinoma at staging

We evaluated the predictive value of ¹⁸F-fluorodeoxyglucose (FDG) uptake on positron emission tomography/CT (PET/CT) for extended pathological T (pT) stages (≥ pT3a) in Renal cell carcinoma (RCC) patients at staging. Thirty-eight RCC patients who underwent ¹⁸F-FDG PET/CT at staging, followed by radical nephrectomy between September 2016 and September 2018, were included in this prospective study. Patients were classified into two groups (limited pT stage: stage T1/2, n = 17; extended pT stage: T3/4, n = 21). Univariate and multivariate logistic regression analyses were performed to identify clinicopathological and metabolic variables to predict extended pT stages. ¹⁸F-FDG metabolic parameters were compared in relation to International Society of Urological Pathology (ISUP) grade and lymphovascular invasion (LVI). In univariate analysis, maximum standardised uptake value, metabolic tumour volume (MTV), and ISUP grade were significant. In multivariate analysis, MTV was the only significant factor of extended pT stages. With a cut-off MTV of 21.2, an area under the curve was 0.944, which was higher than 0.824 for clinical T stages (p = 0.037). In addition, high MTV, but not tumour size, was significantly correlated with aggressive pathologic features (ISUP grade and LVI). High glycolytic tumour volume on ¹⁸F-FDG PET/CT in RCC patients at staging is predictive of extended pT stages which could aid decision-making regarding the best type of surgery.

The optimal use of PET/CT in the management of lymphoma patients

¹⁸F-fluoro-deoxyglucose positron emission tomography (PET)/computed tomography (CT) scans play an important role in the management of lymphoma patients. They are critical to accurately stage disease and assess its response to therapy. In addition, PET/CT scans enable precise target delineation for radiation therapy planning. In this review, we describe the use of PET/CT scans in lymphoma, with a focus on their role in staging disease, assessing response to therapy, predicting prognosis, and planning RT.

Prognostic value of baseline metabolic tumor volume in children and adolescents with intermediate-risk Hodgkin lymphoma treated with chemo-radiation therapy: FDG-PET parameter analysis in a subgroup from COG AHOD0031

BACKGROUND

Positron emission tomography (PET)-based measures of baseline total-body tumor burden may improve risk stratification in intermediate-risk Hodgkin lymphoma (HL).

MATERIALS AND METHODS

Evaluable patients were identified from a cohort treated homogeneously with the same combined modality regimen on the Children's Oncology Group AHOD0031 study. Eligible patients had high-quality baseline PET scans. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were each measured based on 15 thresholds for every patient. Univariate and multivariable Cox regression and Kaplan-Meier survival analyses assessed for an association of MTV and TLG with event-free survival (EFS).

RESULTS

From the AHOD0031 cohort (n = 1712), 86 patients were identified who (i) were treated with four cycles of doxorubicin, bleomycin, vincristine, etoposide, prednisone, cyclophosphamide (ABVE-PC) chemotherapy followed by involved field radiotherapy, and (ii) had a baseline PET scan that was amenable to quantitative analysis. Based on univariate Cox regression analysis, six PET-derived parameters were significantly associated with EFS. For each of these, Kaplan-Meier analyses and the log-rank test were used to compare patients with highest tumor burden (i.e., highest 15%) to the remainder of the cohort. EFS was significantly associated with all six PET parameters (all p < .029). In a multivariable model controlling for important covariates including disease bulk and response to chemotherapy, MTV_2BP was significantly associated with EFS (p = .012).

CONCLUSION

Multiple baseline PET-derived volumetric parameters were associated with EFS. MTV_2BP was highly associated with EFS when controlling for disease bulk and response to chemotherapy. Incorporation of baseline MTV into risk-based treatment algorithms may improve outcomes in intermediate-risk HL.

Correlation of 18F-FDG PET/CT SUVmax with clinical features, D-dimer and LDH in patients with primary intestinal lymphoma

Objective

To investigate the characteristics of fluorine-18-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) maximum standardized uptake value (SUVmax) in primary intestinal lymphoma (PIL) and its correlation with D-dimer and lactate dehydrogenase (LDH).

Methods

Fifty-two patients diagnosed with PIL from June 2016 to December 2019 were analyzed. All patients underwent 18F-FDG PET/CT. The relationships between SUVmax and different pathological subtypes, clinical stages and risk grades were analyzed. The correlations between SUVmax and Ki-67, LDH and D-dimer were determined. Additionally, PET/CT imaging results were collected from 35 patients with primary intestinal cancer (PIC) and compared with the imaging features of PIL.

Results

SUVmax was significantly different between PIL and PIC groups and various PIL pathological subgroups. Patients in the high-risk PIL group had markedly higher SUVmax values than the intermediate-risk and low-risk groups. A significant positive correlation was observed between SUVmax and Ki-67 in patients with PIL. SUVmax was significantly different between the elevated and normal D-dimer groups. D-dimer showed a positive correlation with SUVmax.

Conclusion

18F-FDG PET/CT SUVmax reflects the aggressiveness of lymphoma to a certain degree, is correlated with Ki-67 and determines the risk grades of PIL. Moreover, it facilitates differential diagnosis, clinical staging and treatment based on D-dimer levels.

Value of baseline and end of chemotherapy 18F-FDG PET/CT in pediatric patients with Burkitt lymphoma

The aim of this study was to analyze whether the baseline metabolic parameters of ¹⁸F-FDG PET/CT in pediatric patients with Burkitt lymphoma (BL) can predict treatment response and prognosis. We retrospectively analyzed 68 pediatric patients with BL who underwent PET/CT before treatment. PET images were analyzed semi-quantitatively by measuring the maximum standardized uptake (SUVmax), total metabolic tumor volume (tMTV), and total lesion glycolysis (TLG). Survival curves were plotted according to the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards regression models were used to assess the relation between potential variables and outcomes. tMTV and TLG were significantly lower in patients with complete response compared with those with partial response at the end of treatment. PET metabolic parameters (tMTV and TLG) were the independent prognostic values for outcome. TMTV and TLG were significantly connected with treatment response and prognosis in pediatric with BL.

Prognostic Impact of Pretreatment 2-[18F]-FDG PET/CT Parameters in Primary Gastric DLBCL

Background and Objectives: Primary gastric diffuse large-B cell lymphoma (DLBCL) is an aggressive lymphoma subtype with high ¹⁸F-FDG avidity but unclear criteria for 2-[¹⁸F]-FDG PET/CT in the evaluation of treatment response and prognostication. Our aim was to investigate whether the pretreatment 2-[¹⁸F]-FDG PET/CT variables may predict treatment response (at end of first-line therapy) and prognosis in primary gastric DLBCL. Materials and Methods: we included 57 patients with a diagnosis of primary gastric DLBCL and a baseline 2-[¹⁸F]-FDG PET/CT and an end of treatment PET/CT after 6 cycles of R-CHOP chemotherapy. We analyzed PET images qualitatively and semi-quantitatively by deriving the maximum standardized uptake value body weight (SUVbw), the maximum standardized uptake value lean body mass (SUVlbm), the maximum standardized uptake value body surface area (SUVbsa), lesion to liver SUVmax ratio (L-L SUV R), lesion to blood-pool SUVmax ratio (L-BP SUV R), metabolic tumor volume and total lesion glycolysis of gastric lesion (gMTV and gTLG), and total MTV (tMTV) and TLG. Survival curves were plotted according to the Kaplan–Meier analysis. Results: at a median follow up of 80 months, the median PFS and OS were 69 and 80 months. Baseline gMTV, gTLG, tMTV, and TLG were significantly higher in patients with incomplete response (partial response and progression) compared to complete response group. tMTV and TLG were confirmed to be independent prognostic factors both for PFS (p = 0.023 and p = 0.038) and OS (p = 0.038 and p = 0.026); instead, the other metabolic parameters were not related to outcome survival. Conclusions: high tMTV and TLG were significantly correlated with shorter survival (PFS and OS) and may predict incomplete response after therapy.

The Role of 2-[18F]-FDG PET/CT in Detecting Richter Transformation in Chronic Lymphocytic Leukemia: A Systematic Review

Richter transformation (RT) is a condition wherein B cell chronic lymphocytic leukemia (CLL) transforms into a more aggressive lymphoma variant. The incidence and the significance of RT detected by 2-[18F]-FDG PET/CT is a clinical challenge and it is not widely investigated in the literature. The aim of this systematic review was to analyze published data about the potential role of 2-[18F]-FDG PET/CT in detecting RT. A comprehensive computer literature search of the PubMed/MEDLINE, Embase and Cochrane library databases was conducted up to December 2020. Thirteen studies (1336 patients with CLL) were selected. The maximum standardized uptake value (SUVmax) was the most common metabolic parameter used to detect RT. An SUVmax of 5 had an average overall sensitivity of 87% (range: 71–96%), an average overall specificity of 49% (range: 4–80%), an average positive predictive value of 41% (range: 16–53%) and an average negative predictive value of 84% (range: 33–97%). Other metabolic variables were only marginally investigated, with promising results. 2-[18F]-FDG PET/CT imaging may play an important role in the detection of RT in CLL, based on the high metabolic activity of the nodal lesions that transformed into aggressive lymphomas. 2-[18F]-FDG PET/CT has high negative predictive value for evaluating RT.

18F-FDG-PET/CT in laryngeal cancer: Comparison with conventional imaging and prognostic role

OBJECTIVE

The aim of this study was to investigate the diagnostic accuracy of staging ¹⁸F-FDG-PET/CT in laryngeal cancer, compare these results with conventional imaging (CI) and assess the value of ¹⁸F-FDG-PET/CT features to predict survival.

METHODS

Fifty-four patients with laryngeal squamous cell cancer and baseline ¹⁸F-FDG-PET/CT were retrospectively enrolled. The PET images were analyzed visually and semi-quantitatively by measuring several metabolic parameters. A combination of clinical follow-up/imaging follow-up and/or histopathology was taken as reference standard. Progression free survival (PFS) and disease specific survival (DSS) were computed using Kaplan-Meier curves.

RESULTS

All primary tumors were clearly identified by CI, and 52/54 by ¹⁸F-FDG-PET/CT with a sensitivity of 96.3%. Cervical nodal metastases were detected in 40/54 patients at ¹⁸F-FDG-PET/CT and in 34/49 patients at CI. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy on a patient-based analysis for nodal disease were 100%, 85.7%, 94.6%, 100% and 95.9% at ¹⁸F-FDG-PET/CT, and 91.4%, 85.7%, 94.1%, 80%, 89.8% at CI. Diagnostic performances of PET/CT and CI were not significantly different on a patient-based, side-by-side and level-by-level analysis. ¹⁸F-FDG-PET/CT recognized distant metastases in 7 patients allowing to an upstaging. At a median follow-up of 27 months, relapse/progression of disease occurred in 31 patients and death occurred in 32. Metabolic tumor volume (MTV T), MTV total and total lesion glycolysis (TLG) showed to be independent prognostic factors for PFS.

CONCLUSIONS

Both CI and PET/CT had good diagnostic performances for the staging of laryngeal cancer; baseline metabolic features (MTV and TLG) showed an important prognostic value in assessing the rate of PFS.

Evaluation of an Automatic Classification Algorithm Using Convolutional Neural Networks in Oncological Positron Emission Tomography

Introduction: Our aim was to evaluate the performance in clinical research and in clinical routine of a research prototype, called positron emission tomography (PET) Assisted Reporting System (PARS) (Siemens Healthineers) and based on a convolutional neural network (CNN), which is designed to detect suspected cancer sites in fluorine-18 fluorodeoxyglucose (¹⁸F-FDG) PET/computed tomography (CT).

Method: We retrospectively studied two cohorts of patients. The first cohort consisted of research-based patients who underwent PET scans as part of the initial workup for diffuse large B-cell lymphoma (DLBCL). The second cohort consisted of patients who underwent PET scans as part of the evaluation of miscellaneous cancers in clinical routine. In both cohorts, we assessed the correlation between manually and automatically segmented total metabolic tumor volumes (TMTVs), and the overlap between both segmentations (Dice score). For the research cohort, we also compared the prognostic value for progression-free survival (PFS) and overall survival (OS) of manually and automatically obtained TMTVs.

Results: For the first cohort (research cohort), data from 119 patients were retrospectively analyzed. The median Dice score between automatic and manual segmentations was 0.65. The intraclass correlation coefficient between automatically and manually obtained TMTVs was 0.68. Both TMTV results were predictive of PFS (hazard ratio: 2.1 and 3.3 for automatically based and manually based TMTVs, respectively) and OS (hazard ratio: 2.4 and 3.1 for automatically based and manually based TMTVs, respectively). For the second cohort (routine cohort), data from 430 patients were retrospectively analyzed. The median Dice score between automatic and manual segmentations was 0.48. The intraclass correlation coefficient between automatically and manually obtained TMTVs was 0.61.

Conclusion: The TMTVs determined for the research cohort remain predictive of total and PFS for DLBCL. However, the segmentations and TMTVs determined automatically by the algorithm need to be verified and, sometimes, corrected to be similar to the manual segmentation.

Early Interim Chemotherapy Response Evaluation by F-18 FDG PET/CT in Diffuse Large B Cell Lymphoma

Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) after one cycle of standard chemotherapy in patients with diffuse large B cell lymphoma (DLBCL) was assessed. Prospectively enrolled 51 patients had four PET/CT studies using the same protocol and system: at baseline and after one, three, and six cycles of chemotherapy (PET0, PET1, PET3, PET6). The PET1 and PET6 Deauville five-point score (D5PS) agreed in 60.8%, while PET3 and PET6 D5PS agreed in 90.2%. The absolute and percent changes of peak standard uptake value corrected for lean body mass (SULpeak) compared to baseline were significantly different between PET1 and PET3 (p = 0.001, p < 0.001) and PET1 and PET6 (p = 0.002, p = 0.001), but not between PET3 and PET6 (p = 0.276, p = 0.181). The absolute SULpeak from PET1 predicted treatment failure with accuracy of 78.4% (area under the curve 0.73, p = 0.023). D5PS, SULpeak, and metabolic tumor volume (MTV) were not statistically different between responders versus non-responders, or the one year disease-free versus relapse groups. D5PS and PERCIST responses showed 100% agreement at end-of-therapy. In conclusion, the responses after three and six cycles of therapy showed high degree of agreement. D5PS or MTV after one cycle of chemotherapy could not predict response or one-year disease-free status, but the SULpeak from PET1 was associated with response to first line therapy in DLBCL. Deauville and PERCIST criteria show high concordance.

Fully automatic segmentation of diffuse large B cell lymphoma lesions on 3D FDG-PET/CT for total metabolic tumour volume prediction using a convolutional neural network

PURPOSE

Lymphoma lesion detection and segmentation on whole-body FDG-PET/CT are a challenging task because of the diversity of involved nodes, organs or physiological uptakes. We sought to investigate the performances of a three-dimensional (3D) convolutional neural network (CNN) to automatically segment total metabolic tumour volume (TMTV) in large datasets of patients with diffuse large B cell lymphoma (DLBCL).

METHODS

The dataset contained pre-therapy FDG-PET/CT from 733 DLBCL patients of 2 prospective LYmphoma Study Association (LYSA) trials. The first cohort (n = 639) was used for training using a 5-fold cross validation scheme. The second cohort (n = 94) was used for external validation of TMTV predictions. Ground truth masks were manually obtained after a 41% SUVmax adaptive thresholding of lymphoma lesions. A 3D U-net architecture with 2 input channels for PET and CT was trained on patches randomly sampled within PET/CTs with a summed cross entropy and Dice similarity coefficient (DSC) loss. Segmentation performance was assessed by the DSC and Jaccard coefficients. Finally, TMTV predictions were validated on the second independent cohort.

RESULTS

Mean DSC and Jaccard coefficients (± standard deviation) in the validations set were 0.73 ± 0.20 and 0.68 ± 0.21, respectively. An underestimation of mean TMTV by - 12 mL (2.8%) ± 263 was found in the validation sets of the first cohort (P = 0.27). In the second cohort, an underestimation of mean TMTV by - 116 mL (20.8%) ± 425 was statistically significant (P = 0.01).

CONCLUSION

Our CNN is a promising tool for automatic detection and segmentation of lymphoma lesions, despite slight underestimation of TMTV. The fully automatic and open-source features of this CNN will allow to increase both dissemination in routine practice and reproducibility of TMTV assessment in lymphoma patients.

Tumor metabolic volume by 18F-FDG-PET as a prognostic predictor of first-line pembrolizumab for NSCLC patients with PD-L1 ≥ 50

There is a lack of markers for predicting favorable outcomes after pembrolizumab therapy in patients with non-small cell lung cancer (NSCLC) with programmed death ligand-1 (PD-L1) expression ≥ 50%. This retrospective study examined the prognostic significance of 2-deoxy-2-[18F] fluoro-d-glucose (¹⁸F-FDG) uptake as a predictive marker of first-line pembrolizumab. Forty-eight patients with previously untreated NSCLC and PD-L1 expression levels ≥ 50% who underwent ¹⁸F-FDG-positron emission tomography (PET) just before administration of pembrolizumab monotherapy were eligible and underwent assessment of metabolic tumor volume (MTV), total lesion glycolysis (TLG), and maximum of standardized uptake value (SUV_max) on ¹⁸F-FDG uptake. The objective response rate, median progression-free survival, and median overall survival were 51.1%, 7.1 months, and 18.6 months, respectively. In univariate survival analyses, high MTV was barely a significant prognostic predictor and was confirmed as an independent factor linked to worse outcomes in multivariate analysis, predominantly in patients with a histological diagnosis of adenocarcinoma. A high MTV was significantly associated with distant metastases (especially bone metastasis), C-reactive protein (CRP) level, and PD-L1 expression ≥ 75%. Metabolic tumor activity assessed as MTV from ¹⁸F-FDG uptake predicted the prognosis after first-line pembrolizumab treatment in patients with NSCLC and PD-L1 expression ≥ 50%, especially for adenocarcinoma.

The PET-Derived Tumor-to-Liver Standard Uptake Ratio (SUV TLR ) Is Superior to Tumor SUVmax in Predicting Tumor Response and Survival After Chemoradiotherapy in Patients With Locally Advanced Esophageal Cancer

Background: The maximum standardized uptake values (SUVmax) derived from ¹⁸F-fluorodeoxy-glucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) have some well-known shortcomings in predicting treatment response and prognosis in oncology. The standardized SUVmax with an appropriate reference background may overcome this problem in some instances. This study explored the prognostic value of the tumor-to-liver SUVmax ratio (SUV_TLR) and the tumor-to-blood pool SUVmax ratio (SUV_TBR) in predicting the objective response (OR) and overall survival (OS) in patients with locally advanced esophageal cancer after concurrent chemoradiotherapy (CCRT).

Methods: We retrospectively analyzed 128 newly diagnosed esophageal squamous cell carcinoma (ESCC) patients who were treated with CCRT. The SUVmax of primary tumor, SUV_TLR, SUV_TBR and clinicopathologic features data were analyzed. Univariate and multivariate analyses were used to determine the predictors of tumor response. Survival analysis was performed using the Kaplan–Meier method and Cox proportional hazards model.

Results: Receiver operating characteristic (ROC) curve analysis demonstrated that SUV_TLR was superior to SUVmax and SUV_TBR in predicting treatment response. Univariate and multivariate analyses revealed that advanced tumor stage (hazard ratio [HR] = 9.67; 95% CI: 1.15-81.28; P = 0.037) and high SUV_TLR (HR = 21.92; 95% CI: 2.26-212.96; P = 0.008) were independent predictors of poor treatment response. Cox regression analysis showed that good clinical tumor response (p < 0.014, HR =0.501; 95% CI: 0.288–0.871) was a favorable independent predictive factor for OS, while an advanced tumor stage (p = 0.018, HR = 1.796; 95% CI: 1.107-2.915) and a high SUV_TLR (p < 0.002, HR = 2.660; 95% CI: 1.425–4.967) were prognostic factors for poor OS. The median OS of patients in the low SUV_TLR and high SUV_TLR groups was 13.47 vs. 19.30 months, respectively.

Conclusions: PET-derived SUV_TLR is superior to tumor SUVmax and SUV_TBR in predicting treatment response and overall survival in patients with ESCC undergoing CCRT. High SUV_TLR was an independent predictor of poor treatment response and shorter overall survival.

18F-FDG-PET/CT in laryngeal cancer: comparison with conventional imaging and prognostic role

OBJECTIVE

The aim of this study was to investigate the diagnostic accuracy of staging 18 F-FDG-PET/CT in laryngeal cancer, compare these results with conventional imaging (CI) and assess the value of 18 F-FDG-PET/CT features to predict survival.

METHODS

Fifty-four patients with laryngeal squamous cell cancer and baseline 18 F-FDG-PET/CT were retrospectively enrolled. The PET images were analyzed visually and semi-quantitatively by measuring several metabolic parameters. A combination of clinical follow-up/imaging follow-up and/or histopathology was taken as reference standard. Progression free survival (PFS) and disease specific survival (DSS) were computed using Kaplan-Meier curves.

RESULTS

All primary tumors were clearly identified by CI, and 52/54 by 18 F-FDG-PET/CT with a sensitivity of 96.3%. Cervical nodal metastases were detected in 40/54 patients at 18 F-FDG-PET/CT and in 34/49 patients at CI. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy on a patient-based analysis for nodal disease were 100%, 85.7%, 94.6%, 100% and 95.9% at 18 F-FDG-PET/CT, and 91.4%, 85.7%, 94.1%, 80%, 89.8% at CI. Diagnostic performances of PET/CT and CI were not significantly different on a patient-based, side-by-side and level-by-level analysis. 18 F-FDG-PET/CT recognized distant metastases in 7 patients allowing to an upstaging. At a median follow-up of 27 months, relapse/progression of disease occurred in 31 patients and death occurred in 32. Metabolic tumor volume (MTV T), MTV total and total lesion glycolysis (TLG) showed to be independent prognostic factors for PFS.

CONCLUSIONS

Both CI and PET/CT had good diagnostic performances for the staging of laryngeal cancer; baseline metabolic features (MTV and TLG) showed an important prognostic value in assessing the rate of PFS.

Utility of [18F] Fluoro-Deoxyglucose Positron Emission Tomography/Computed Tomography for Staging and Therapy Response Evaluation in Pediatric Rhabdomyosarcoma: A Case Series and Literature Review

Background: The role of [¹⁸F] fluoro-deoxyglucose [[¹⁸F] FDG] positron emission tomography (PET)/computed tomography (CT) in pediatric rhabdomyosarcoma (RMS) is not well-established. This manuscript explores the role of staging and therapy response evaluation of PET/CT in a series of patients with RMS.

Methods: Thirteen consecutive patients with pathologically proven RMS underwent baseline PET/CT scan and a second PET/CT for evaluation of therapy response. Maximum standardized uptake value (SUV_max), mean standardized uptake value (SUV_mean), highest standardized uptake peak value (SUV_peak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained from baseline PET/CT and were used as potential predictors for evaluation of metabolic treatment response.

Results: On baseline PET/CT, most RMSs are located in the pelvic cavity, and upper arms ranked second. The primary lesions were large and showed invasion to the surrounding tissues. Lymph node metastases were seen in eight patients, and eight patients showed distant metastasis to the lung, liver, and bone. The median SUV_max, SUV_mean, and SUV_peak of primary sites were 7.1, 4.0, and 5.9, respectively. The median MTV and TLG were 196.6 cm³ and 780.2, respectively. After therapy, six patients received complete metabolic response (CMR) and non-CMR occurred in seven patients on the second PET/CT. SUV_max, SUV_peak, MTV, and TLG in patients with CMR were significantly lower than those in patients with non-CMR.

Conclusions: Primary sites and metastatic lesions of RMS demonstrate increased glycolytic activity, which may allow them to be imaged using [¹⁸F] FDG PET/CT. Metabolic parameters derived from the baseline PET/CT have potential value for predicting CMR to therapy in pediatric RMS.

Metabolic behavior and prognostic role of pretreatment 18F-FDG PET/CT in gist

AIM

The metabolic behavior and the prognostic value of ¹⁸ F-FDG-PET/CT in gastrointestinal stromal tumor (GIST) is not well investigated. The aim of this study was to analyze the metabolic behavior of GIST and the prognostic role of pretreatment PET/CT features.

METHODS

In this retrospective study, we included 35 patients with a diagnosis of GIST who underwent a pretreatment ¹⁸ F-FDG-PET/CT scan. We analyzed PET images visually and semiquantitatively by measuring several metabolic parameters as the maximum standardized uptake value corrected for body weight (SUVbw), for lean body mass (SUVlbm), for body surface area (SUVbsa), metabolic tumor volume (MTV) and total lesion glycolysis (TLG). The Kaplan-Meier method was used to measure the progression free survival (PFS) and overall survival curves.

RESULTS

Twenty-nine (82%) patients showed a positive ¹⁸ F-FDG-PET/CT, whereas the remaining 6 had no hypermetabolic lesions. ¹⁸ F-FDG-avidity was significantly related with mitotic index, tumor stage and tumor risk group. Instead, semiquantitative PET/CT parameters correlated only with tumor risk group. Disease progression occurred in 16 patients whereas death in seven. ¹⁸ F-FDG-avidity, MTV and TLG were the only variables significantly associated with PFS.

CONCLUSION

An 82% rate of PET avidity in GIST was found and it was correlated with stage, tumor risk group and mitotic index. Only baseline ¹⁸ F-FDG-avidity, MTV and TLG were independently correlated with PFS.

Prognostic Value of 18F-FDG PET/CT Metabolic Parameters in Splenic Marginal Zone Lymphoma

INTRODUCTION

Splenic marginal zone lymphoma (SMZL) is an indolent non-Hodgkin lymphoma usually with a good prognosis, but no clear metabolic behavior at fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). The aim of our analysis was to investigate the prognostic role of baseline 18F-FDG PET/CT parameters in SMZL.

MATERIALS AND METHODS

We retrospectively included 42 patients who received 18F-FDG-PET/CT before any treatments, and PET images were evaluated visually and semi-quantitatively by measuring lesion to liver (L-L) maximum standardized uptake volume (SUVmax) ratio (L-L SUV R), lesion to blood-pool SUVmax ratio (L-BP SUV R), metabolic tumor volume, and total lesion glycolysis. Progression-free (PFS) and overall survival (OS) curves were plotted according to the Kaplan-Meier method.

RESULTS

In all patients, an increased splenic FDG uptake (higher than the background) was identified, showing the presence of diffuse spleen uptake in 35 patients and focal uptake in the remaining 7 patients. At a median follow-up of 51 months, relapse or progression of disease occurred in 23 patients with an average time of 38.1 months from the baseline 18F-FDG PET/CT, and death occurred in 4 patients with an average time of 26.8 months. The estimated 2-year PFS and OS rates were 78% and 90%, respectively, whereas 5-year PFS and OS rates were 63% and 82%, respectively. At multivariate analysis, only L-L SUV R and L-BP SUV R were independent prognostic factors for PFS. In addition, no significant association was discovered for OS, considering all features.

CONCLUSIONS

L-L SUV R and L-BP SUV R were independently correlated with PFS.

The Incremental Prognostic Value of Baseline 18F-FDG PET/CT Imaging in Angioimmunoblastic T-Cell Lymphoma

Methods

From January 2010 to October 2019, a total of 23 patients who pathologically confirmed to have AITL were retrospectively analyzed. All patients underwent whole-body ¹⁸F-FDG PET/CT scan before chemotherapy. The ¹⁸F-FDG PET/CT features, clinical data, laboratory indicators, Ki67 labeling index, and survival status were collected and analyzed.

Results

The median follow-up was 22 months. The expected 1-, 2-, and 3-year survival rate was 72.2%, 49.6%, and 42.5%, respectively. The median overall survival (OS) was 23 months (95% confidence interval (CI): 8.459~37.541). AITL is prone to extranodal infiltration, in addition to nodal infiltration (6 patients had nodal infiltration alone, and 17 patients had both nodal and extranodal infiltration). The SUV_max of nodal lesions were higher than that for the extranodal lesions (10.43 ± 4.45, 6.64 ± 3.51, F = 2.78, t = 4.39, P < 0.01). On multivariate survival analysis, the Eastern Cooperative Oncology Group (ECOG) and SUV_max of extranodal lesions were independent predictors of OS.

Conclusion

Baseline ¹⁸F-FDG PET/CT results and SUV_max of extranodal lesions showed an incremental prognostic value in addition to clinical prognostic factors.

18F-FDG PET or PET/CT in Mantle Cell Lymphoma

The aim of this systematic review was to examine published data about the potential role of Fluorine-18-fluorodeoxyglucose positron emission tomography or positron emission tomography/computed tomography (¹⁸F-FDG PET or PET/CT) in patients affected by mantle cell lymphoma (MCL). A comprehensive computer literature search of Scopus, PubMed/MEDLINE, and Embase databases was conducted, including articles indexed up to November, 2019; 25 studies or subsets in studies analyzing the value of ¹⁸F-FDG PET or PET/CT in patients with MCL were eligible for inclusion. From the analyses of the selected studies, the following main findings are described: (1) MCL are ¹⁸F-FDG-avid in most of cases, especially nodal lesions, but bone marrow and gastrointestinal disease localizations have low ¹⁸F-FDG avidity; (2) ¹⁸F-FDG PET/CT seems to be helpful in staging setting, showing a better diagnostic performance than conventional imaging and a positive impact on clinical stage; (3) ¹⁸F-FDG PET/CT is useful in evaluating treatment response, especially after chemotherapy and transplantation; and (4) metabolic response after therapy seems to have a prognostic role. Despite several limitations affecting this analysis, especially related to the heterogeneity of the studies included, MCL is an ¹⁸F-FDG-avid lymphoma in most of the cases, with the exception of bone marrow and gastrointestinal disease. Moreover, ¹⁸F-FDG PET/CT seems to be useful in evaluating treatment response and prognosis.

The Role of 18F-FDG PET/CT in Staging and Prognostication of Mantle Cell Lymphoma: An Italian Multicentric Study

Mantle cell lymphoma (MCL) is an aggressive lymphoma subtype with poor prognosis in which 18F-FDG-PET/CT role in treatment response evaluation and prediction of outcome is still unclear. The aim of this multicentric study was to investigate the role of 18F-FDG-PET/CT in staging MCL and the prognostic role of Deauville criteria (DC) in terms of progression-free survival (PFS) and overall survival (OS). We retrospectively enrolled 229 patients who underwent baseline and end-of-treatment (eot) 18F-FDG-PET/CT after first-line therapy. EotPET/CT scans were visually interpreted according to DC. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of PET/CT for evaluation of bone marrow (BM) were 27%, 100%, 100%, 48% and 57%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of PET/CT for evaluation of the gastrointestinal (GI) tract were 60%, 99%, 93%, 90% and 91%, respectively. At a median follow-up of 40 months, relapse occurred in 104 cases and death in 49. EotPET/CT results using DC significantly correlated with PFS, not with OS. Instead, considering OS, only MIPI score was significantly correlated. In conclusion, we demonstrated that MCL is an FDG-avid lymphoma and 18F-FDG-PET/CT is a useful tool for staging purpose, showing good specificity for BM and GI evaluation, but suboptimal sensitivity. EotPET/CT result was the only independent significant prognostic factor that correlated with PFS.

Radiomic features of glucose metabolism enable prediction of outcome in mantle cell lymphoma

PURPOSE

To determine whether [¹⁸F]FDG PET/CT-derived radiomic features alone or in combination with clinical, laboratory and biological parameters are predictive of 2-year progression-free survival (PFS) in patients with mantle cell lymphoma (MCL), and whether they enable outcome prognostication.

METHODS

Included in this retrospective study were 107 treatment-naive MCL patients scheduled to receive CD20 antibody-based immuno(chemo)therapy. Standardized uptake values (SUV), total lesion glycolysis, and 16 co-occurrence matrix radiomic features were extracted from metabolic tumour volumes on pretherapy [¹⁸F]FDG PET/CT scans. A multilayer perceptron neural network in combination with logistic regression analyses for feature selection was used for prediction of 2-year PFS. International prognostic indices for MCL (MIPI and MIPI-b) were calculated and combined with the radiomic data. Kaplan-Meier estimates with log-rank tests were used for PFS prognostication.

RESULTS

SUVmean (OR 1.272, P = 0.013) and Entropy (heterogeneity of glucose metabolism; OR 1.131, P = 0.027) were significantly predictive of 2-year PFS: median areas under the curve were 0.72 based on the two radiomic features alone, and 0.82 with the addition of clinical/laboratory/biological data. Higher SUVmean in combination with higher Entropy (SUVmean >3.55 and entropy >3.5), reflecting high "metabolic risk", was associated with a poorer prognosis (median PFS 20.3 vs. 39.4 months, HR 2.285, P = 0.005). The best PFS prognostication was achieved using the MIPI-bm (MIPI-b and metabolic risk combined): median PFS 43.2, 38.2 and 20.3 months in the low-risk, intermediate-risk and high-risk groups respectively (P = 0.005).

CONCLUSION

In MCL, the [¹⁸F]FDG PET/CT-derived radiomic features SUVmean and Entropy may improve prediction of 2-year PFS and PFS prognostication. The best results may be achieved using a combination of metabolic, clinical, laboratory and biological parameters.

Diagnostic and Clinical Impact of Staging 18F-FDG PET/CT in Mantle-Cell Lymphoma: A Two-Center Experience

INTRODUCTION

The diagnostic accuracy of fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in staging mantle-cell lymphoma has not yet investigated. The aim of this 2-center retrospective study was to investigate the utility of ¹⁸F-FDG PET/CT in assessing nodal, splenic, bone marrow (BM), and gastrointestinal (GI) disease compared to CT, BM, and GI endoscopy; and to assess its clinical impact.

PATIENTS AND METHODS

One hundred twenty-two patients with histologically proven mantle-cell lymphoma were included. PET/CT BM findings were considered positive if isolated/multiple focal uptake in the BM not explained by benign findings and/or diffuse BM uptake higher than liver with/without focal uptakes were present. PET/CT findings were considered positive for GI involvement in the presence of isolated/multiple focal uptake in the GI organ.

RESULTS

All patients had positive PET/CT showing the presence of at least one hypermetabolic lesion, with the exception of one case. PET/CT results, compared to CT, detected more nodal and/or splenic lesions in 26 patients. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of PET/CT for BM were 52%, 98%, 97%, 65%, and 74%; for GI 64%, 91%, 69%, 90%, and 85%; and for GI excluding diabetic patients, 78%, 92%, 72%, 94%, and 89%. PET/CT permitted upstaging of 21 cases and downstaging of 2.

CONCLUSION

¹⁸F-FDG PET/CT showed excellent detection rate in nodal and splenic disease-a rate better than CT. For BM and GI evaluation, in order to reach good accuracy, the selection of patients and the use of specific criteria for evaluation of these organs seems to be crucial. Moreover, PET/CT altered the management and therapeutic approach in about 20% of patients.