Influence of Software Tool and Methodological Aspects of Total Metabolic Tumor Volume Calculation on Baseline [18F]FDG PET to Predict Survival in Hodgkin Lymphoma

Prognostic value of the combination of volume, massiveness and fragmentation parameters measured on baseline FDG pet in high-burden follicular lymphoma

The prognostic value of radiomic quantitative features measured on pre-treatment 18F-FDG PET/CT was investigated in patients with follicular lymphoma (FL). We conducted a retrospective study of 126 FL patients (grade 1-3a) diagnosed between 2006 and 2020. A dozen of PET/CT-derived features were extracted via a software (Oncometer3D) from baseline 18F-FDG PET/CT images. The receiver operating characteristic (ROC) curve, Kaplan-Meier method and Cox analysis were used to assess the prognostic factors for progression of disease within 24 months (POD24) and progression-free survival at 24 months. Four different clusters were identified among the twelve PET parameters analyzed: activity, tumor burden, fragmentation-massiveness and dispersion. On ROC analyses, TMTV, the total metabolic tumor volume, had the highest AUC (0.734) followed by medPCD, the median distance between the centroid of the tumors and their periphery (AUC: 0.733). Patients with high TMTV (HR = 4.341; p < 0.001), high Tumor Volume Surface Ratio (TVSR) (HR = 3.204; p < 0.003) and high medPCD (HR = 4.507; p < 0.001) had significantly worse prognosis in both Kaplan-Meier and Cox univariate analyses. Furthermore, a synergistic effect was observed in Kaplan-Meier and Cox analyses combining these three PET/CT-derived parameters (HR = 12.562; p < 0.001). Having two or three high parameters among TMTV, TVSR and medPCD was able to predict POD24 status with a specificity of 68% and a sensitivity of 75%. TMTV, TVSR and baseline medPCD are strong prognostic factors in FL and their combination better predicts disease prognosis.

Texture analysis of 18F-FDG PET/CT and CECT: Prediction of refractoriness of Hodgkin lymphoma with mediastinal bulk involvement

To recognize patients at high risk of refractory disease, the identification of novel prognostic parameters improving stratification of newly diagnosed Hodgkin Lymphoma (HL) is still needed. This study investigates the potential value of metabolic and texture features, extracted from baseline 18F-FDG Positron Emission Tomography/Computed Tomography (PET) and Contrast-Enhanced Computed Tomography scan (CECT), together with clinical data, in predicting first-line therapy refractoriness (R) of classical HL (cHL) with mediastinal bulk involvement. We reviewed 69 cHL patients who underwent staging PET and CECT. Lesion segmentation and texture parameter extraction were performed using the freeware software LIFEx 6.3. The prognostic significance of clinical and imaging features was evaluated in relation to the development of refractory disease. Receiver operating characteristic curve, Cox proportional hazard regression and Kaplan-Meier analyses were performed to examine the potential independent predictors and to evaluate their prognostic value. Among clinical characteristics, only stage according to the German Hodgkin Group (GHSG) classification system significantly differed between R and not-R. Among CECT variables, only parameters derived from second order matrices (gray-level co-occurrence matrix (GLCM) and gray-level run length matrix (GLRLM) demonstrated significant prognostic power. Among PET variables, SUVmean, several variables derived from first (histograms, shape), and second order analyses (GLCM, GLRLM, NGLDM) exhibited significant predictive power. Such variables obtained accuracies greater than 70% at receiver operating characteristic analysis and their PFS curves resulted statistically significant in predicting refractoriness. At multivariate analysis, only HISTO_EntropyPET extracted from PET (HISTO_EntropyPET ) and GHSG stage resulted as significant independent predictors. Their combination identified 4 patient groups with significantly different PFS curves, with worst prognosis in patients with higher HISTO_EntropyPET values, regardless of the stage. Imaging radiomics may provide a reference for prognostic evaluation of patients with mediastinal bulky cHL. The best prognostic value in the prediction of R versus not-R disease was reached by combining HISTO_EntropyPET with GHSG stage.

Challenges for quality and utilization of real-world data for diffuse large B-cell lymphoma in REALYSA, a LYSA cohort

ABSTRACT

Real-world data (RWD) are essential to complement clinical trial (CT) data, but major challenges remain, such as data quality. REal world dAta in LYmphoma and Survival in Adults (REALYSA) is a prospective noninterventional multicentric cohort started in 2018 that included patients newly diagnosed with lymphoma in France. Herein is a proof-of-concept analysis on patients with first-line diffuse large B-cell lymphoma (DLBCL) to (1) evaluate the capacity of the cohort to provide robust data through a multistep validation process; (2) assess the consistency of the results; and (3) conduct an exploratory transportability assessment of 2 recent phase 3 CTs (POLARIX and SENIOR). The analysis population comprised 645 patients with DLBCL included before 31 March 2021 who received immunochemotherapy and for whom 3589 queries were generated, resulting in high data completeness (<4% missing data). Median age was 66 years, with mostly advanced-stage disease and high international prognostic index (IPI) score. Treatments were mostly rituximab, cyclophosphamide, doxorubicin hydrochloride, vincristine, and prednisone (R-CHOP 75%) and reduced dose R-CHOP (13%). Estimated 1-year event-free survival (EFS) and overall survival rates were 77.9% and 90.0%, respectively (median follow-up, 9.9 months). Regarding transportability, when applying the CT's main inclusion criteria (age, performance status, and IPI), outcomes seemed comparable between patients in REALYSA and standard arms of POLARIX (1-year progression-free survival 79.8% vs 79.8%) and SENIOR (1-year EFS, 64.5% vs 60.0%). With its rigorous data validation process, REALYSA provides high-quality RWD, thus constituting a platform for numerous scientific purposes. The REALYSA study was registered at www.clinicaltrials.gov as #NCT03869619.

Metabolic tumor volume predicts outcome in patients with advanced stage follicular lymphoma from the RELEVANCE trial

BACKGROUND

We investigated the prognostic value of baseline positron emission tomography (PET) parameters for patients with treatment-naïve follicular lymphoma (FL) in the phase III RELEVANCE trial, comparing the immunomodulatory combination of lenalidomide and rituximab (R2) versus R-chemotherapy (R-chemo), with both regimens followed by R maintenance therapy.

PATIENTS AND METHODS

Baseline characteristics of the entire PET-evaluable population (n = 406/1032) were well balanced between treatment arms. The maximal standard uptake value (SUVmax) and the standardized maximal distance between tow lesions (SDmax) were extracted, the standardized distance between two lesions the furthest apart, were extracted. The total metabolic tumor volume (TMTV) was computed using the 41% SUVmax method.

RESULTS

With a median follow-up of 6.5 years, the 6-year progression-free survival (PFS) was 57.8%, the median TMTV was 284 cm3, SUVmax was 11.3 and SDmax was 0.32 m-1, with no significant difference between arms. High TMTV (>510 cm3) and FLIPI were associated with an inferior PFS (P = 0.013 and P = 0.006, respectively), whereas SUVmax and SDmax were not (P = 0.08 and P = 0.12, respectively). In multivariable analysis, follicular lymphoma international prognostic index (FLIPI) and TMTV remained significantly associated with PFS (P = 0.0119 and P = 0.0379, respectively). These two adverse factors combined stratified the overall population into three risk groups: patients with no risk factors (40%), with one factor (44%), or with both (16%), with a 6-year PFS of 67.7%, 54.5%, and 41.0%, respectively. No significant interaction between treatment arms and TMTV or FLIPI (P = 0.31 or P = 0.59, respectively) was observed. The high-risk group (high TMTV and FLIPI 3-5) had a similar PFS in both arms (P = 0.45) with a median PFS of 68.4% in the R-chemo arm versus 71.4% in the R2 arm.

CONCLUSIONS

Baseline TMTV is predictive of PFS, independently of FLIPI, in patients with advanced FL even in the context of antibody maintenance.

Advances in positron emission tomography and radiomics

Positron emission tomography is established for staging and response evaluation in lymphoma using visual evaluation and semi-quantitative analysis. Radiomic analysis involving quantitative imaging features at baseline, such as metabolic tumor volume and markers of disease dissemination and changes in the standardized uptake value during treatment are emerging as powerful biomarkers. The combination of radiomic features with clinical risk factors and genomic analysis offers the potential to improve clinical risk prediction. This review discusses the state of current knowledge, progress toward standardization of tumor delineation for radiomic analysis and argues that radiomic features, molecular markers and circulating tumor DNA should be included in clinical trial designs to enable the development of baseline and dynamic risk scores that could further advance the field to facilitate testing of novel treatments and personalized therapy in aggressive lymphomas.

Prognostic Value of 18F-FDG PET/CT in Diffuse Large B-Cell Lymphoma Treated with a Risk-Adapted Immunochemotherapy Regimen

Early identification of patients with diffuse large B-cell lymphoma (DLBCL) who are likely to experience disease recurrence or refractory disease after rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) would be useful for improving risk-adapted treatment strategies. We aimed to assess the prognostic value of 18F-FDG PET/CT parameters at baseline, interim, and end of treatment (EOT). Methods: We analyzed the prognostic impact of 18F-FDG PET/CT in 166 patients with DLBCL treated with a risk-adapted immunochemotherapy regimen. Scans were obtained at baseline, after 4 cycles of R-CHOP or 3 cycles of RR-CHOP (double dose of R) and 1 cycle of CHOP alone (interim) and 6 wk after completing therapy (EOT). Progression-free survival (PFS) and overall survival (OS) were estimated using Kaplan-Meier and the impact of clinical/PET factors assessed with Cox models. We also assessed the predictive ability of the recently proposed International Metabolic Prognostic Index (IMPI). Results: The median follow-up was 7.9 y. International Prognostic Index (IPI), baseline metabolic tumor volume (MTV), and change in maximum SUV (ΔSUVmax) at interim scans were statistically significant predictors for OS. Baseline MTV, interim ΔSUVmax, and EOT Deauville score were statistically significant predictors of PFS. Combining interim PET parameters demonstrated that patients with Deauville 4-5 and positive ΔSUVmax ≤ 70% at restaging (∼10% of the cohort) had extremely poor prognosis. The IMPI had limited discrimination and slightly overestimated the event rate in our cohort. Conclusion: Baseline MTV and interim ΔSUVmax predicted both PFS and OS with this sequential immunochemotherapy program. Combining interim Deauville score with interim ΔSUVmax may identify an extremely high-risk DLBCL population.

Characterization of Mediastinal Bulky Lymphomas with FDG-PET-Based Radiomics and Machine Learning Techniques

BACKGROUND

This study tested the diagnostic value of 18F-FDG PET/CT (FDG-PET) volumetric and texture parameters in the histological differentiation of mediastinal bulky disease due to classical Hodgkin lymphoma (cHL), primary mediastinal B-cell lymphoma (PMBCL) and grey zone lymphoma (GZL), using machine learning techniques.

METHODS

We reviewed 80 cHL, 29 PMBCL and 8 GZL adult patients with mediastinal bulky disease and histopathological diagnoses who underwent FDG-PET pre-treatment. Volumetric and radiomic parameters were measured using FDG-PET both for bulky lesions (BL) and for all lesions (AL) using LIFEx software (threshold SUV ≥ 2.5). Binary and multiclass classifications were performed with various machine learning techniques fed by a relevant subset of radiomic features.

RESULTS

The analysis showed significant differences between the lymphoma groups in terms of SUVmax, SUVmean, MTV, TLG and several textural features of both first- and second-order grey level. Among machine learning classifiers, the tree-based ensembles achieved the best performance both for binary and multiclass classifications in histological differentiation.

CONCLUSIONS

Our results support the value of metabolic heterogeneity as an imaging biomarker, and the use of radiomic features for early characterization of mediastinal bulky lymphoma.

Brentuximab Vedotin Plus AVD for First-Line Treatment of Early-Stage Unfavorable Hodgkin Lymphoma (BREACH): A Multicenter, Open-Label, Randomized, Phase II Trial

PURPOSE

The prognosis of patients with early-stage unfavorable Hodgkin lymphoma remains unsatisfactory. We assessed the efficacy and safety of brentuximab vedotin plus doxorubicin, vinblastine, and dacarbazine (BV-AVD) in previously untreated, early-stage unfavorable Hodgkin lymphoma (ClinicalTrials.gov identifier: NCT02292979).

METHODS

BREACH is a multicenter, randomized, open-label, phase II trial. Eligible patients were age 18-60 years with ≥ 1 unfavorable EORTC/LYSA criterion. Patients were randomly assigned (2:1) to four cycles of BV-AVD or standard doxorubicin, bleomycin, vincristine, and dacarbazine (ABVD), followed by 30 Gy involved node radiotherapy. The primary end point was the positron emission tomography (PET) response rate after two cycles by expert independent review using the Deauville score. The study was designed to test if the PET-negative rate after two cycles of BV-AVD was superior to 75%. We hypothesized a 10% increase in the PET-negative rate after two cycles of BV-AVD.

RESULTS

Between March 2015 and October 2016, 170 patients were enrolled. After two cycles, the primary end point of the study was met: 93 (82.3%; 90% CI, 75.3 to 88.0) of 113 patients in the BV-AVD arm were PET-negative (Deauville score 1-3) compared with 43 (75.4%; 90% CI, 64.3% to 84.5%) of 57 in the ABVD arm. The 2-year progression-free survival (PFS) was 97.3% (95% CI, 91.9 to 99.1) and 92.6% (95% CI, 81.4% to 97.2%) in the BV-AVD and ABVD arms, respectively. High total metabolic tumor volume was associated with a significantly shorter PFS (hazard ratio, 17.9; 95% CI, 2.2 to 145.5; P < .001). For patients with high total metabolic tumor volume, the 2-year PFS rate was 90.9% (95% CI, 74.4 to 97.0) and 70.7% (95% CI, 39.4% to 87.9%) in the BV-AVD and ABVD arms, respectively.

CONCLUSION

BV-AVD demonstrated an improvement in the PET-negative rate compared with ABVD after two cycles.

Imaging of Invasive Fungal Infections- The Role of PET/CT

Over the last decades, the population at risk for invasive fungal disease (IFD) has increased because of medical therapy advances and diseases compromising patients' immune systems. The high morbidity and mortality associated with invasive fungal disease in the immunocompromised present the challenge of early diagnosis of the IFD and the need to closely monitor the infection during treatment. The definitive diagnosis of invasive fungal disease based on culture or histopathological methods often has reduced diagnostic accuracy in the immunocompromised and may be very invasive. Less invasive and indirect evidence of the fungal infection by serology and imaging has been used for the early diagnosis of fungal infection before definitive results are available or when the definitive methods of diagnosis are suboptimal. Imaging in invasive fungal disease is a non-invasive biomarker that helps in the early diagnosis of invasive fungal disease but helps follow-up the infection during treatment. Different imaging modalities are used in the workup to evaluate fungal disease. The different imaging modalities have advantages and disadvantages at different sites in the body and may complement each other in the management of IFD. Positron emission tomography integrated with computed tomography with [18F]Fluorodeoxyglucose (FDG PET/CT) has helped manage IFD. The combined functional data from PET and anatomical data from the CT from almost the whole body allows noninvasive evaluation of IFD and provides a semiquantitative means of assessing therapy. FDG PET/CT adds value to anatomic-based only imaging modalities. The nonspecificity of FDG uptake has led to the evaluation of other tracers in the assessment of IFD. However, these are mainly still at the preclinical level and are yet to be translated to humans. FDG PET/CT remains the most widely evaluated radionuclide-based imaging modality in IFD management. The limitations of FDG PET/CT must be well understood, and more extensive prospective studies in uniform populations are needed to validate its role in the management of IFD that can be international guidelines.

Influence of the methodological aspects of the dichotomization of total metabolic tumor volume measured through baseline fluorine-18 fluorodeoxyglucose PET on survival prediction in lymphoma

OBJECTIVE

The total metabolic tumor volume (TMTV) measured from fluorine-18 fluorodeoxyglucose (18F-FDG) PET can be useful for determining the prognosis of patients with lymphoma. Stratifying patients into high- and low-TMTV risk groups requires a cutoff point, which is determined through the dichotomization method. This study investigated whether different TMTV dichotomization methods influenced survival prediction in patients with lymphoma.

METHODS

We retrospectively enrolled 129 patients with lymphoma who had undergone baseline 18F-FDG PET. TMTV was calculated using a fixed standardized uptake value threshold of 4.0. A total of six methods were employed to determine the optimal TMTV cutoff point using receiver-operating characteristic curve analyses, X-Tile bioinformatics software, and the Cutoff Finder web application. The prognostic performance of each method in survival prediction was examined.

RESULTS

The median (interquartile range) TMTV was 123 cm3 (21-335 cm3). The optimal TMTV cutoff values for predicting progression-free survival (PFS) and overall survival (OS) were in the range of 144-748 cm3. The cutoff points were used to dichotomize patients into two groups with distinct prognoses. All TMTV dichotomizations were significantly predictive of PFS and OS. The survival curves showed significant differences between the high- and low-TMTV groups. The C-indices of the survival models did not significantly differ in any of the dichotomizations.

CONCLUSION

The prognostic significance of TMTV was maintained regardless of the methodological aspects of dichotomization. However, the optimal TMTV cutoff point varied according to the chosen dichotomization method. Care should be taken when establishing an optimal TMTV cutoff point for clinical use.

Reproducibility of [18F]FDG PET/CT liver SUV as reference or normalisation factor

INTRODUCTION

Although visual and quantitative assessments of [18F]FDG PET/CT studies typically rely on liver uptake value as a reference or normalisation factor, consensus or consistency in measuring [18F]FDG uptake is lacking. Therefore, we evaluate the variation of several liver standardised uptake value (SUV) measurements in lymphoma [18F]FDG PET/CT studies using different uptake metrics.

METHODS

PET/CT scans from 34 lymphoma patients were used to calculate SUVmaxliver, SUVpeakliver and SUVmeanliver as a function of (1) volume-of-interest (VOI) size, (2) location, (3) imaging time point and (4) as a function of total metabolic tumour volume (MTV). The impact of reconstruction protocol on liver uptake is studied on 15 baseline lymphoma patient scans. The effect of noise on liver SUV was assessed using full and 25% count images of 15 lymphoma scans.

RESULTS

Generally, SUVmaxliver and SUVpeakliver were 38% and 16% higher compared to SUVmeanliver. SUVmaxliver and SUVpeakliver increased up to 31% and 15% with VOI size while SUVmeanliver remained unchanged with the lowest variability for the largest VOI size. Liver uptake metrics were not affected by VOI location. Compared to baseline, liver uptake metrics were 15-18% and 9-18% higher at interim and EoT PET, respectively. SUVliver decreased with larger total MTVs. SUVmaxliver and SUVpeakliver were affected by reconstruction protocol up to 62%. SUVmax and SUVpeak moved 22% and 11% upward between full and 25% count images.

CONCLUSION

SUVmeanliver was most robust against VOI size, location, reconstruction protocol and image noise level, and is thus the most reproducible metric for liver uptake. The commonly recommended 3 cm diameter spherical VOI-based SUVmeanliver values were only slightly more variable than those seen with larger VOI sizes and are sufficient for SUVmeanliver measurements in future studies.

TRIAL REGISTRATION

EudraCT: 2006-005,174-42, 01-08-2008.

Final results of brentuximab vedotin combined with ifosfamide-carboplatin-etoposide in first refractory/relapsed Hodgkin lymphoma: a lymphoma study association phase I/II study

This phase I/II study assessed the combination of brentuximab vedotin (BV) with ifosfamide-carboplatin-etoposide (ICE) as a second-line therapy in refractory/relapsed (R/R) classical Hodgkin lymphoma (cHL) patients. Phase I study was designed to determine the maximum tolerated dose (MTD) of BV (10 patients) and phase II evaluated the rate of complete metabolic response (CMR) after 2 cycles of BV-ICE (42 patients). There were no dose-limiting toxicities (DLT) during phase I recommending BV 1.8 mg/kg for phase II. Twenty-six patients (61.9%) achieved CMR after 2 cycles of BV-ICE and 37 patients (88%) were transplanted. With a median follow-up of 38 months, the 3-year progression free survival (PFS) and overall survival (OS) rate were 64.3% and 100%, respectively. Hematological toxicities (81%) and infections (21%) were the most frequent adverse event encountered BV-ICE regimen is feasible with manageable toxicities and could be an alternative to other salvage treatments. Trial Registration: ClinicalTrials.gov identifier: NCT02686346.

18F-FDG PET/CT for assessing heterogeneous metabolic response between primary tumor and metastases and prognosis in non-small cell lung cancer

INTRODUCTION

This study aimed to use ¹⁸F-fluorodeoxyglucose positron emission tomography and/or computed tomography (¹⁸FDG-PET/CT) imaging to evaluate the heterogeneous metabolic response between primary tumor and metastases in NSCLC after therapy and explored its correlation with prognosis.

METHODS

The data of patients with NSCLC who underwent ¹⁸FDG-PET/CT before and after treatment were retrospectively analyzed. Heterogeneous metabolic response (HR), defined as the difference in metabolic response between any metastases and primary lesion, was evaluated using ¹⁸FDG-PET/CT. And the correlation between HR and clinical prognosis was also analyzed.

RESULTS

A total of 56 patients with NSCLC including 56 primary lesions and 491 metastases were enrolled in the study. 46.4% (26/56) of patients had HR, especially in patients with stage IV disease and whose metastases with high metabolic burden. HR was significantly correlated with poorer overall survival (OS) and progression-free survival (PFS) (P < .001 and P = .045, respectively). The multivariate analysis suggested that HR was an unfavorable independent prognostic factor for OS (HR = 4.36; 95% CI, 2.00-9.49; P < .001) but not for PFS (P = .469). HR between lymph node metastases was correlated with shorter OS (P < .001) but not with PFS (P = .370).

CONCLUSION

HR was observed between primary and metastatic lesions in NSCLC after treatment using PET/CT. HR is significantly associated with poor prognosis and is an independent prognostic factor for OS.

Overall survival with circulating tumor DNA-guided therapy in advanced non-small-cell lung cancer

Circulating tumor DNA (ctDNA) sequencing guides therapy decisions but has been studied mostly in small cohorts without sufficient follow-up to determine its influence on overall survival. We prospectively followed an international cohort of 1,127 patients with non-small-cell lung cancer and ctDNA-guided therapy. ctDNA detection was associated with shorter survival (hazard ratio (HR), 2.05; 95% confidence interval (CI), 1.74-2.42; P < 0.001) independently of clinicopathologic features and metabolic tumor volume. Among the 722 (64%) patients with detectable ctDNA, 255 (23%) matched to targeted therapy by ctDNA sequencing had longer survival than those not treated with targeted therapy (HR, 0.63; 95% CI, 0.52-0.76; P < 0.001). Genomic alterations in ctDNA not detected by time-matched tissue sequencing were found in 25% of the patients. These ctDNA-only alterations disproportionately featured subclonal drivers of resistance, including RICTOR and PIK3CA alterations, and were associated with short survival. Minimally invasive ctDNA profiling can identify heterogeneous drivers not captured in tissue sequencing and expand community access to life-prolonging therapy.

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.

The Impact of Semiautomatic Segmentation Methods on Metabolic Tumor Volume, Intensity, and Dissemination Radiomics in 18F-FDG PET Scans of Patients with Classical Hodgkin Lymphoma

Consensus about a standard segmentation method to derive metabolic tumor volume (MTV) in classical Hodgkin lymphoma (cHL) is lacking, and it is unknown how different segmentation methods influence quantitative PET features. Therefore, we aimed to evaluate the delineation and completeness of lesion selection and the need for manual adaptation with different segmentation methods, and to assess the influence of segmentation methods on the prognostic value of MTV, intensity, and dissemination radiomics features in cHL patients. Methods: We analyzed a total of 105 ¹⁸F-FDG PET/CT scans from patients with newly diagnosed (n = 35) and relapsed/refractory (n = 70) cHL with 6 segmentation methods: 2 fixed thresholds on SUV4.0 and SUV2.5, 2 relative methods of 41% of SUV_max (41max) and a contrast-corrected 50% of SUV_peak (A50P), and 2 combination majority vote (MV) methods (MV2, MV3). Segmentation quality was assessed by 2 reviewers on the basis of predefined quality criteria: completeness of selection, the need for manual adaptation, and delineation of lesion borders. Correlations and prognostic performance of resulting radiomics features were compared among the methods. Results: SUV4.0 required the least manual adaptation but tended to underestimate MTV and often missed small lesions with low ¹⁸F-FDG uptake. SUV2.5 most frequently included all lesions but required minor manual adaptations and generally overestimated MTV. In contrast, few lesions were missed when using 41max, A50P, MV2, and MV3, but these segmentation methods required extensive manual adaptation and overestimated MTV in most cases. MTV and dissemination features significantly differed among the methods. However, correlations among methods were high for MTV and most intensity and dissemination features. There were no significant differences in prognostic performance for all features among the methods. Conclusion: A high correlation existed between MTV, intensity, and most dissemination features derived with the different segmentation methods, and the prognostic performance is similar. Despite frequently missing small lesions with low ¹⁸F-FDG avidity, segmentation with a fixed threshold of SUV4.0 required the least manual adaptation, which is critical for future research and implementation in clinical practice. However, the importance of small, low ¹⁸F-FDG-avidity lesions should be addressed in a larger cohort of cHL patients.

Risk factors for POD24 in patients with previously untreated follicular lymphoma: a systematic review and meta-analysis

Progression of disease within 24 months (POD24) is strongly associated with a poor outcome in patients with follicular lymphoma (FL). Our study aimed to identify the potential risk factors for POD24 in patients with FL. Medline, EMBASE and the Cochrane Library were systematically searched from the earliest record to September 2020. Studies investigating the prognostic factors for POD24 in patients with newly diagnosed grade 1-3a FL were included. Among 10,014 pieces of literature, a total of 90 studies investigating 82 risk factors were included for qualitative analysis. Meta-analyses were performed in 31 studies with 11 factors. Results showed that elevated sIL-2R, β2m and LDH, total metabolic tumour volume > 510 cm³, vitamin D < 20 ng/mL, grade 3a and lymphoma-associated macrophages/high-power field ≥ 15 were significantly associated with an increased risk of POD24. No significant association was found between POD24 and the ALC/AMC ratio, sex, T effector signature or EZH2 genetic alteration. Additionally, minimal residual disease, Ki-67, PD-1 and TP53 were analysed narratively. Overall, this is the first study that comprehensively analysed the prognostic factors associated with POD24 in FL patients. We have confirmed the significance value of several common prognostic factors as well as others not commonly included in clinical study, helping to construct an integrated and more efficient model.

Healthy Organs Uptake on Baseline 18F-FDG PET/CT as an Alternative to Total Metabolic Tumor Volume to Predict Event-Free Survival in Classical Hodgkin's Lymphoma

Purpose

Healthy organs uptake, including cerebellar and liver SUVs have been reported to be inversely correlated to total metabolic tumor volume (TMTV), a controversial predictor of event-free survival (EFS) in classical Hodgkin's Lymphoma (cHL). The objective of this study was to estimate TMTV by using healthy organs SUV measurements and assess the performance of this new index (UF, Uptake Formula) to predict EFS in cHL.

Methods

Patients with cHL were retrospectively included. SUV values and TMTV derived from baseline 18F-FDG PET/CT were harmonized using ComBat algorithm across PET/CT systems. UF was estimated using ANOVA analysis. Optimal thresholds of TMTV and UF were calculated and tested using Cox models.

Results

163 patients were included. Optimal UF model of TMTV included age, lymphoma maximum SUVmax, hepatic SUVmean and cerebellar SUVmax (R2 14.0% - p &lt; 0.001). UF &gt; 236.8 was a significant predictor of EFS (HR: 2.458 [1.201–5.030], p = 0.01) and was not significantly different from TMTV &gt; 271.0 (HR: 2.761 [1.183–5.140], p = 0.001). UF &gt; 236.8 remained significant in a bivariate model including IPS score (p = 0.02) and determined two populations with different EFS (63.7 vs. 84.9%, p = 0.01).

Conclusion

The Uptake Formula, a new index including healthy organ SUV values, shows similar performance to TMTV in predicting EFS in Hodgkin's Lymphoma. Validation cohorts will be needed to confirm this new prognostic parameter.

Application of SPECT and PET / CT with computer-aided diagnosis in bone metastasis of prostate cancer: a review

Bone metastasis has a significant influence on the prognosis of prostate cancer(PCa) patients. In this review, we discussed the current application of PCa bone metastasis diagnosis with single-photon emission computed tomography (SPECT) and positron emission tomography/computed tomography (PET/CT) computer-aided diagnosis(CAD) systems. A literature search identified articles concentrated on PCa bone metastasis and PET/CT or SPECT CAD systems using the PubMed database. We summarized the previous studies focused on CAD systems and manual quantitative markers calculation, and the coincidence rate was acceptable. We also analyzed the quantification methods, advantages, and disadvantages of CAD systems. CAD systems can detect abnormal lesions of PCa patients’ 99mTc-MDP-SPECT, 18F-FDG-PET/CT, 18F-NaF-PET/CT, and 68 Ga-PSMA PET/CT images automated or semi-automated. CAD systems can also calculate the quantitative markers, which can quantify PCa patients’ whole-body bone metastasis tumor burden accurately and quickly and give a standardized and objective result. SPECT and PET/CT CAD systems are potential tools to monitor and quantify bone metastasis lesions of PCa patients simply and accurately, the future clinical application of CAD systems in diagnosing PCa bone metastasis lesions is necessary and feasible.

Response-adapted anti-PD1 based salvage therapy for Hodgkin lymphoma with nivolumab +/- ICE (NICE)

This phase 2 trial evaluated PET-adapted nivolumab (Nivo) alone or in combination with ifosfamide, carboplatin, and etoposide (NICE) as first salvage therapy and bridge to autologous hematopoietic cell transplantation (AHCT) in relapsed/refractory (RR) classical Hodgkin lymphoma (cHL). Patients with RR cHL received 240mg Nivo every 2 weeks for up to 6 cycles (C). Patients in complete response (CR) after C6 proceeded to AHCT, while patients with progressive disease (PD) at any point or not in CR after C6 received NICE for 2 cycles. The primary endpoint was CR rate per the 2014 Lugano classification at completion of protocol therapy. 43 patients were evaluable for toxicity; 42 were evaluable for response. 34 patients received Nivo alone and 9 patients received Nivo+NICE. No unexpected toxicities were observed after Nivo or NICE. After Nivo, the overall response rate (ORR) was 81% and the CR rate was 71%. Among the 9 patients who received NICE, all responded with 8 (89%) achieving CR. At the end of all protocol therapy, the ORR and CR rates were 93% and 91%. Thirty-three patients were bridged directly to AHCT, including 26 after Nivo alone. The 2-year progression-free survival (PFS) and overall survival in all treated patients (n=43) were 72% (95%CI:56-83) and 95% (95%CI:82-99), respectively. Among the 33 patients who bridged directly to AHCT after protocol therapy, the 2-year PFS was 94% (95%CI:78-98). PET-adapted sequential salvage therapy with Nivo or Nivo+NICE was well-tolerated and effective, resulting in a high CR rate and bridging most patients to AHCT without chemotherapy. This Clinical Trial is registered under NCT03016871.

Deep Learning Approach to Automatize TMTV Calculations Regardless of Segmentation Methodology for Major FDG-Avid Lymphomas

The total metabolic tumor volume (TMTV) is a new prognostic factor in lymphomas that could benefit from automation with deep learning convolutional neural networks (CNN). Manual TMTV segmentations of 1218 baseline 18FDG-PET/CT have been used for training. A 3D V-NET model has been trained to generate segmentations with soft dice loss. Ground truth segmentation has been generated using a combination of different thresholds (TMTVprob), applied to the manual region of interest (Otsu, relative 41% and SUV 2.5 and 4 cutoffs). In total, 407 and 405 PET/CT were used for test and validation datasets, respectively. The training was completed in 93 h. In comparison with the TMTVprob, mean dice reached 0.84 in the training set, 0.84 in the validation set and 0.76 in the test set. The median dice scores for each TMTV methodology were 0.77, 0.70 and 0.90 for 41%, 2.5 and 4 cutoff, respectively. Differences in the median TMTV between manual and predicted TMTV were 32, 147 and 5 mL. Spearman’s correlations between manual and predicted TMTV were 0.92, 0.95 and 0.98. This generic deep learning model to compute TMTV in lymphomas can drastically reduce computation time of TMTV.

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.

Role of PET/CT in initial evaluation of lymphoma patients

Background

Accurate radiologic assessment of treatment response in lymphoma patients is important to evaluate the effectiveness of treatment and consequently predict the relapse; the value of PET/CT for post-treatment prognosis prediction has been recently investigated. The aim of this study is to highlight the prognostic value of PET-CT metabolic volumetric parameters in the evaluation of lymphoma patients.

Results

Among the included 40 patients, post-treatment SUV, MTV, and TLG were significantly lower in a responsive group than the non-responsive group. % changes of all quantitative PET/CT parameters were significantly higher in the responsive group than the non-responsive group.

Conclusions

This study suggests that pre-treatment PET/CT quantitative measures (except baseline SUVmax) are not conclusive in the prediction of patient response to treatment; however, the ΔSUVmax, ΔMTV, and ΔTLG% from the baseline to the end of therapy could be used in predicting patient response to treatment, determining patient prognosis, and suggesting the relapse.

Role of PET/CT in initial evaluation of lymphoma patients

Background

Accurate radiologic assessment of treatment response in lymphoma patients is important to evaluate the effectiveness of treatment and consequently predict the relapse; the value of PET/CT for post-treatment prognosis prediction has been recently investigated. The aim of this study is to highlight the prognostic value of PET-CT metabolic volumetric parameters in the evaluation of lymphoma patients.

Results

Among the included 40 patients, post-treatment SUV, MTV, and TLG were significantly lower in a responsive group than the non-responsive group. % changes of all quantitative PET/CT parameters were significantly higher in the responsive group than the non-responsive group.

Conclusions

This study suggests that pre-treatment PET/CT quantitative measures (except baseline SUVmax) are not conclusive in the prediction of patient response to treatment; however, the ΔSUVmax, ΔMTV, and ΔTLG% from the baseline to the end of therapy could be used in predicting patient response to treatment, determining patient prognosis, and suggesting the relapse.

Prognostic value of baseline metabolic tumour volume in advanced-stage Hodgkin's lymphoma

Our aim was to evaluate the prognostic value of initial total metabolic tumour volume (TMTV) in a population of patients with advanced-stage Hodgkin's lymphoma (HL). We retrospectively included 179 patients with stage IIb-III-IV Hodgkin's disease who received BEACOPP or ABVD as the first-line treatment. The initial TMTV was determined using a semi-automatic method for each patient. We analysed its prognostic value in terms of 5-year progression-free survival (PFS), overall survival, and positron emission tomography (PET) response after two courses of chemotherapy. Considering all the treatments and using a threshold of 217 cm³, TMTV was predictive of 5-year PFS and PET response after two courses of chemotherapy. In multivariable analysis involving TMTV, IPI score, and the first treatment received, TMTV remained a baseline prognostic factor for 5-year PFS. In the subgroup of patients treated with BEACOPP with a threshold of 331 cm³, TMTV was predictive of PET response, but not 5-year PFS (p = 0.087). The combined analysis of TMTV and PET response enabled the individualisation of a subgroup of patients (low TMTV and complete response on PET) with a very low risk of recurrence. Baseline TMTV appears to be a useful independent prognostic factor for predicting relapse in advanced-stage HL in ABVD subgroup, with a tendency of survival curves separation in BEACOPP subgroup.

FDG-PET/CT in Lymphoma: Where Do We Go Now?

18F-fluorodeoxyglucose positron emission tomography combined with computed tomography (FDG-PET/CT) is an essential part of the management of patients with lymphoma at staging and response evaluation. Efforts to standardize PET acquisition and reporting, including the 5-point Deauville scale, have enabled PET to become a surrogate for treatment success or failure in common lymphoma subtypes. This review summarizes the key clinical-trial evidence that supports PET-directed personalized approaches in lymphoma but also points out the potential place of innovative PET/CT metrics or new radiopharmaceuticals in the future.

Comparison between tumour metabolism derived from 18F-FDG PET/CT and accurate cytogenetic stratification in newly diagnosed multiple myeloma patients

Background

¹⁸F-fluorodeoxyglucose positron emission tomography integrated with computed tomography (¹⁸F-FDG PET/CT) is a useful tool for baseline staging in newly diagnosed multiple myeloma (MM) but also for prognostic stratification. This monocentric retrospective study aimed at examining the relation between baseline tumour metabolism assessed by ¹⁸F-FDG PET/CT and linear predictor (LP) score, a new cytogenetic stratification score.

Methods

From March 2012 to March 2019, 57 patients with newly diagnosed MM addressed to our institution for baseline ¹⁸F-FDG PET/CT were included. LP score was determined on systematic iliac crest bone marrow samples. Obtained on CD138-sorted bone marrow plasma cells, this recent composite cytogenetic stratification is a 6-marker based weighted score using fluorescence in situ hybridization (FISH) ± single nucleotide polymorphism (SNP) arrays. We compared quantitative metabolic parameters and LP score using a Kruskal-Wallis test and visual suspicion of diffuse bone marrow involvement (DBI; based on hepatic background as threshold of positivity) and cytogenetic data using a Chi-squared test.

Results

The distribution of total metabolic tumour volume (TMTV) and total lesion glycolysis (TLG) values among the three LP score categories was almost stochastic, with no significant association (P=0.70). Additionally, no significant association between TMTV/TLG and any of the six cytogenetic abnormalities included in LP score calculation. A significant association was found between visual high suspicion of DBI and LP score (P=0.036), and between this visual parameter and the presence of 1q gain (P=0.049).

Conclusions

There is no significant association between quantitative metabolic parameters assessed with ¹⁸F-FDG PET/CT and LP score in patients with newly diagnosed MM, suggesting a potential complementarity of these biomarkers for prognostic stratification. A significant association was found between high visual suspicion of DBI and LP score.

Total Lesion Glycolysis Improves Tumor Burden Evaluation and Risk Assessment at Diagnosis in Hodgkin Lymphoma

Hodgkin lymphoma (HL) is a hematological malignancy with an excellent prognosis. However, we still need to identify those patients that could experience failed standard frontline chemotherapy. Tumor burden evaluation and standard decisions are based on Ann Arbor (AA) staging, but this approach may be insufficient in predicting outcomes. We aim to study new ways to assess tumor burden through volume-based PET parameters to improve the risk assessment of HL patients. We retrospectively analyzed 101 patients with HL from two hospitals in the Balearic Islands between 2011 and 2018. Higher metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were significantly associated with a higher incidence of III-IV AA stages, B-symptoms, hypoalbuminemia, lymphopenia, and higher IPS. Standardized uptake value (SUVmax) was significantly related to AA stage and hypoalbuminemia. We found that TLG or the combination of SUVmax, TLG, and MTV significantly improved the risk assessment when compared to AA staging. We conclude that TLG is the best single PET/CT-related tumor-load parameter that significantly improves HL risk assessment when compared to AA staging. If confirmed in a larger and validated sample, this information could be used to modify standard frontline therapy and justifies the inclusion of TLG inside an HL prognostic score.

Prognostic value of baseline total metabolic tumour volume of 18F-FDG PET/CT imaging in patients with angioimmunoblastic T-cell lymphoma

Purpose

The aim of this study was to explore the prognostic value of baseline metabolic parameters of ¹⁸F-FDG PET/CT imaging in patients with angioimmunoblastic T-cell lymphoma (AITL).

Materials and methods

Fifty-six AITL patients (average age 64.0 ± 1.3 years) diagnosed pathologically from August 2009 to August 2019 were enrolled in this retrospective study. The total metabolic tumour volume (TMTV), total lesion glycolysis (TLG), maximum standardized uptake value (SUVmax), and correlated clinical characteristics were collected and analysed. TMTV was computed with the 41% SUVmax threshold method. The chi-square test or Fisher’s exact probability method was used to compare clinical characteristics. Kaplan–Meier curves were used to describe progression-free survival (PFS) and overall survival (OS). The log-rank test was used to analyse the difference within groups. The statistically significant factors in the univariate regression analysis were incorporated into the Cox risk proportional regression model for multivariate survival analysis.

Results

The TMTV cut-off value was 514.6 cm³ from the ROC curve analysis. Forty (71.4%) patients progressed and 31 (55.4%) patients died within a median follow-up time of 19.1 (interquartile range 7.8–34.6) months. The 1-year and 3-year PFS rates were 42.9% and 30.1%, and the 3-year and 5-year OS rates were 45.9% and 34.4%, respectively. Univariate survival analysis showed that high TMTV and TLG may be the factors contributing to poor PFS and OS. Multivariate analysis showed that TMTV and prognostic index for T-cell lymphoma (PIT) were independent parameters for PFS and OS in AITL patients. TMTV, combined with PIT, may have better risk stratification performance than TMTV alone.

Conclusions

Baseline TMTV and PIT were independent prognostic predictors in AITL patients. The combination of TMTV and PIT can facilitate prognostic stratification and contribute to personalized therapy.

Optimizing Workflows for Fast and Reliable Metabolic Tumor Volume Measurements in Diffuse Large B Cell Lymphoma

PURPOSE

This pilot study aimed to determine interobserver reliability and ease of use of three workflows for measuring metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in diffuse large B cell lymphoma (DLBCL).

PROCEDURES

Twelve baseline [¹⁸F]FDG PET/CT scans from DLBCL patients with wide variation in number and size of involved organs and lymph nodes were selected from the international PETRA consortium database. Three observers analyzed scans using three workflows. Workflow A: user-defined selection of individual lesions followed by four automated segmentations (41%SUVmax, A50%SUVpeak, SUV≥2.5, SUV≥4.0). For each lesion, observers indicated their "preferred segmentation." Individually selected lesions were summed to yield total MTV and TLG. Workflow B: fully automated preselection of [¹⁸F]FDG-avid structures (SUV≥4.0 and volume≥3ml), followed by removing non-tumor regions with single mouse clicks. Workflow C: preselected volumes based on Workflow B modified by manually adding lesions or removing physiological uptake, subsequently checked by experienced nuclear medicine physicians. Workflow C was performed 3 months later to avoid recall bias from the initial Workflow B analysis. Interobserver reliability was expressed as intraclass correlation coefficients (ICC).

RESULTS

Highest interobserver reliability in Workflow A was found for SUV≥2.5 and SUV≥4.0 methods (ICCs for MTV 0.96 and 0.94, respectively). SUV≥4.0 and A50%Peak were most and SUV≥2.5 was the least preferred segmentation method. Workflow B had an excellent interobserver reliability (ICC = 1.00) for MTV and TLG. Workflow C reduced the ICC for MTV and TLG to 0.92 and 0.97, respectively. Mean workflow analysis time per scan was 29, 7, and 22 min for A, B, and C, respectively.

CONCLUSIONS

Improved interobserver reliability and ease of use occurred using fully automated preselection (using SUV≥4.0 and volume≥3ml, Workflow B) compared with individual lesion selection by observers (Workflow A). Subsequent manual modification was necessary for some patients but reduced interobserver reliability which may need to be balanced against potential improvement on prognostic accuracy.

Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML)

The identification of reliable and non-invasive oncology biomarkers remains a main priority in healthcare. There are only a few biomarkers that have been approved as diagnostic for cancer. The most frequently used cancer biomarkers are derived from either biological materials or imaging data. Most cancer biomarkers suffer from a lack of high specificity. However, the latest advancements in machine learning (ML) and artificial intelligence (AI) have enabled the identification of highly predictive, disease-specific biomarkers. Such biomarkers can be used to diagnose cancer patients, to predict cancer prognosis, or even to predict treatment efficacy. Herein, we provide a summary of the current status of developing and applying Magnetic resonance imaging (MRI) biomarkers in cancer care. We focus on all aspects of MRI biomarkers, starting from MRI data collection, preprocessing and machine learning methods, and ending with summarizing the types of existing biomarkers and their clinical applications in different cancer types.

Interobserver agreement in automated metabolic tumor volume measurements of Deauville score 4 and 5 lesions at interim 18F-FDG PET in DLBCL

Introduction: Metabolic tumor volume (MTV) on interim-PET (I-PET) is a potential prognostic biomarker for diffuse large B-cell lymphoma (DLBCL). Implementation of MTV on I-PET requires consensus which semi-automated segmentation method delineates lesions most successfully with least user interaction. Methods used for baseline PET are not necessarily optimal for I-PET due to lower lesional standardized uptake values (SUV) at I-PET. Therefore, we aimed to evaluate which method provides the best delineation quality of Deauville-score (DS) 4-5 DLBCL lesions on I-PET at best interobserver agreement on delineation quality and, secondly, to assess the effect of lesional SUV_max on delineation quality and performance agreements. Methods: DS4-5 lesions from 45 I-PET scans were delineated using six semi-automated methods i) SUV 2.5, ii) SUV 4.0, iii) adaptive threshold [A50%peak], iv) 41% of maximum SUV [41%max], v) majority vote including voxels detected by ≥2 methods [MV2] and vi) detected by ≥3 methods [MV3]. Delineation quality per MTV was rated by three independent observers as acceptable or non-acceptable. For each method, observer scores on delineation quality, specific agreements and MTV were assessed for all lesions, and per category of lesional SUV_max (<5, 5-10, >10). Results: In 60 DS4-5 lesions on I-PET, MV3 performed best, with acceptable delineation in 90% of lesions, with a positive agreement (PA) of 93%. Delineation quality scores and agreements per method strongly depended on lesional SUV: the best delineation quality scores were obtained using MV3 in lesions with SUV_max<10 and SUV4.0 in more FDG-avid lesions. Consequently, overall delineation quality and PA improved by applying the most preferred method per SUV category instead of using MV3 as single best method. MV3- and SUV4.0-derived MTVs of lesions with SUV_max>10, were comparable after excluding visually failed MV3 contouring. For lesions with SUV_max<10, MTVs using different methods correlated poorly. Conclusion: On I-PET, MV3 performed best and provided the highest interobserver agreement regarding acceptable delineations of DS4-5 DLBCL lesions. However, delineation method preference strongly depended on lesional SUV. Therefore, we suggest to explore an approach that identifies the optimal delineation method per lesion as function of tumor FDG uptake characteristics, i.e. SUV_max.

Baseline PET/CT imaging parameters for prediction of treatment outcome in Hodgkin and diffuse large B cell lymphoma: a systematic review

Purpose

To systematically review the literature evaluating clinical utility of imaging metrics derived from baseline fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) for prediction of progression-free (PFS) and overall survival (OS) in patients with classical Hodgkin lymphoma (HL) and diffuse large B cell lymphoma (DLBCL).

Methods

A search of MEDLINE/PubMed, Web of Science, Cochrane, Scopus and clinicaltrials.gov databases was undertaken for articles evaluating PET/CT imaging metrics as outcome predictors in HL and DLBCL. PRISMA guidelines were followed. Risk of bias was assessed using the Quality in Prognosis Studies (QUIPS) tool.

Results

Forty-one articles were included (31 DLBCL, 10 HL). Significant predictive ability was reported in 5/20 DLBCL studies assessing SUVmax (PFS: HR 0.13–7.35, OS: HR 0.83–11.23), 17/19 assessing metabolic tumour volume (MTV) (PFS: HR 2.09–11.20, OS: HR 2.40–10.32) and 10/13 assessing total lesion glycolysis (TLG) (PFS: HR 1.078–11.21, OS: HR 2.40–4.82). Significant predictive ability was reported in 1/4 HL studies assessing SUVmax (HR not reported), 6/8 assessing MTV (PFS: HR 1.2–10.71, OS: HR 1.00–13.20) and 2/3 assessing TLG (HR not reported). There are 7/41 studies assessing the use of radiomics (4 DLBCL, 2 HL); 5/41 studies had internal validation and 2/41 included external validation. All studies had overall moderate or high risk of bias.

Conclusion

Most studies are retrospective, underpowered, heterogenous in their methodology and lack external validation of described models. Further work in protocol harmonisation, automated segmentation techniques and optimum performance cut-off is required to develop robust methodologies amenable for clinical utility.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05233-2.

Computed tomography-based skeletal segmentation for quantitative PET metrics of bone involvement in multiple myeloma

Purpose

Quantifications in nuclear medicine are occasionally limited by the lack of standardization for defining volumes of interest (VOIs) on functional images. In the present article, we propose the use of computed tomography (CT)–based skeletal segmentation to determine anatomically the VOI in order to calculate quantitative parameters of fluorine 18 fluorodeoxyglucose (¹⁸F-FDG) PET/CT images from patients with multiple myeloma.

Methods

We evaluated 101 whole-body ¹⁸F-FDG PET/CTs of 58 patients with multiple myeloma. An initial subjective visual analysis of the PET images was used to classify the bone involvement as negative/mild, moderate, or marked. Then, a fully automated CT–based segmentation of the skeleton was performed on PET images. The maximum, mean, and SD of the standardized uptake values (SUV_max, SUV_mean, and SD_SUV) were calculated for bone tissue and compared with the visual analysis.

Results

Forty-five (44.5%), 32 (31.7%), and 24 (23.8%) PET images were, respectively, classified as negative/mild, moderate, or marked bone involvement. All quantitative parameters were significantly related to the visual assessment of bone involvement. This association was stronger for the SUV_mean [odds ratio (OR): 10.52 (95% confidence interval (CI), 5.68–19.48); P < 0.0001] and for the SD_SUV [OR: 5.58 (95% CI, 3.31–9.42); P < 0.001) than for the SUV_max [OR: 1.01 (95% CI, 1.003–1.022); P = 0.003].

Conclusion

CT–based skeletal segmentation allows for automated and therefore reproducible calculation of PET quantitative parameters of bone involvement in patients with multiple myeloma. Using this method, the SUV_mean and its respective SD correlated better with the visual analysis of ¹⁸F-FDG PET images than SUVmax. Its value in staging and evaluating therapy response needs to be evaluated.

Will Baseline Total Lesion Glycolysis Play a Role in Improving the Prognostic Value of the NCCN-IPI in Primary Gastric Diffuse Large B-Cell Lymphoma Patients Treated With the R-CHOP Regimen?

PURPOSE

The aim was to explore whether baseline total lesion glycolysis (TLG) can improve the prognostic value of the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) in primary gastric diffuse large B-cell lymphoma (PG-DLBCL) patients treated with an R-CHOP-like regimen.

MATERIALS AND METHODS

Ninety-four PG-DLBCL patients who underwent baseline PET/CT between July 2010 and May 2019 were included in this retrospective study. FDG-avid lesions in each patient were segmented to calculate the SUVmax, total metabolic tumor volume (TMTV), and TLG. Progression-free survival (PFS) and overall survival (OS) were used as end points to evaluate prognosis.

RESULTS

During the follow-up period of 5 to 108 months (35.3 ± 23.5 months), high TLG and a high NCCN-IPI were significantly associated with poor PFS and OS. Total lesion glycolysis and the NCCN-IPI were independent predictors of PFS and OS. Patients were stratified into 3 groups according to the combination of TLG and the NCCN-IPI for PFS (P < 0.001) and OS (P < 0.001): high-risk group (TLG > 1159.1 and NCCN-IPI 4-8) (PFS and OS, 57.7% and 61.5%, respectively, n = 42), intermediate-risk group (TLG > 1159.1 or NCCN-IPI 4-8) (PFS and OS, both 76.9%, n = 26), and low-risk group (TLG ≤ 1159.1 and NCCN-IPI 0-3) (PFS and OS, 97.6% and 100.0%, respectively, n = 26).

CONCLUSIONS

Both TLG and the NCCN-IPI are independent predictors of PG-DLBCL patient survival. Moreover, the combination of TLG and the NCCN-IPI improved patient risk stratification and might help personalize therapeutic regimens.

Baseline SUVmax is related to tumor cell proliferation and patient outcome in follicular lymphoma

Follicular lymphoma (FL) is the most common indolent lymphoma. Despite the clear benefit of CD20-based therapy, a subset of FL patients still progress to aggressive lymphoma. Thus, identifying early biomarkers that incorporate PET metrics could be helpful to identify patients with a high risk of treatment failure with Rituximab. We retrospectively included a total of 132 untreated FL patients separated into training and validation cohorts. Optimal threshold of baseline SUVmax was first determined in the training cohort (n=48) to predict progression-free survival (PFS). The PET results were investigated along with the tumor and immune microenvironment, which were determined by immunochemistry and transcriptome studies involving gene set enrichment analyses and immune cell deconvolution, together with the tumor mutation profile. We report that baseline SUVmax >14.5 was associated with poorer PFS than baseline SUVmax ≤14.5 (HR=0.28; p=0.00046). Neither immune T-cell infiltration nor immune checkpoint expression were associated with baseline PET metrics. By contrast, FL samples with Ki-67 staining ≥10% showed enrichment of cell cycle/DNA genes (p=0.013) and significantly higher SUVmax values (p=0.007). Despite similar oncogenic pathway alterations in both SUVmax groups of FL samples, 4 out of 5 cases harboring the infrequent FOXO1 transcription factor mutation were seen in FL patients with SUVmax >14.5. Thus, high baseline SUVmax reflects FL tumor proliferation and, together with Ki-67 proliferative index, can be used to identify patients at risk of early relapse with R-chemotherapy.

Baseline metabolic tumor volume calculation using different SUV thresholding methods in Hodgkin lymphoma patients: interobserver agreement and reproducibility across software platforms

AIM

Although it is not yet used in clinical practice, metabolic tumor volume (MTV) assessed on the baseline FDG-PET has shown consistent prognostic value in various lymphoma types. The aim of our study was to compare interobserver agreement and reproducibility across platforms of MTV calculation using different SUV thresholding methods in a large series of patients with newly diagnosed Hodgkin lymphoma.

MATERIALS AND METHODS

We retrospectively studied 121 patients. MTV at baseline FDG-PET was independently computed by three readers with three programs of semi-automatic segmentation, Fiji, LifeX, and Accurate. MTV measurement was performed with different thresholds: SUV >2.5, SUV >4, and SUV >41% of SUV max.

RESULTS

At inter-observer agreement analysis all Intraclass Correlation Coefficients (ICCs) were excellent (ICC >0.9), except for Accurate SUV >41% of SUV max (ICC = 0.8). The highest correlations were obtained at the SUV >4 threshold. The second best was SUV >2.5 threshold. Regarding reproducibility across software, we found statistically significant differences between Fiji versus LifeX and Accurate at fixed thresholds and between LifeX and Accurate at SUV >41% of SUV max, while no significant differences emerged between LifeX and Accurate using fixed thresholds.

CONCLUSION

The three SUV thresholds studied are all suitable for MTV calculation in terms of reproducibility. The best reproducibility is achieved using fixed thresholds, both SUV >4 and SUV >2.5. If more than one software has to be used in a study, we suggest the use of fixed thresholds and the platforms LifeX and Accurate.

Prognostic value of imaging markers from 18FDG-PET/CT in paediatric patients with Hodgkin lymphoma

OBJECTIVE

Identification of imaging prognostic parameters for early therapy personalisation to reduce treatment-related morbidity in paediatric Hodgkin lymphoma (HL). Our aim was to evaluate quantitative markers from baseline 2-[18F]fluoro-2-deoxy-d-glucose PET/CT as prognostic factors for treatment outcomes. Another goal was assessing the prognostic value of Deauville score at interim PET/CT.

METHODS

Twenty-one patients were prospectively enrolled. Median age was 12 years (range 6-17); 13 were female. Patients underwent PET/CT for disease staging (bPET), at the end of two cycles of chemotherapy (iPET) and after chemotherapy. A total of 173 lesions were segmented from bPET. We calculated 51 texture features for each lesion. Total metabolic tumour volume and total lesion glycolysis from bPET were calculated for response prediction at iPET. Univariate and multivariate analyses were used for optimal cut-off values to separate responders at iPET according to the Deauville score.

RESULTS

We identified four texture features as possible independent predictors of treatment outcomes at iPET. The areas under the ROC for univariate analysis were 0.89 (95% CI, 0.75-1), 0.82 (95% CI, 0.64-1), 0.79 (95% CI, 0.59-0.99) and 0.89 (95% CI, 0.75-1). The survival curves for patients assigned Deauville scores 1, 2, 3 and X were different from those assigned a score 4, with 4-year progression free-survival (PFS) rates of 85 versus 29%, respectively (P = 0.05).

CONCLUSIONS

We found four textural features as candidates for predicting early response to chemotherapy in paediatric patients with HL. The Deauville score at iPET was useful for differentiating PFS rates.

An Open Source Solution for "Hands-on" teaching of PET/CT to Medical Students under the COVID-19 Pandemic

AIMS

 Since 2017, medical students at the University of Bergen were taught PET/CT "hands-on" by viewing PET/CT cases in native format on diagnostic workstations in the hospital. Due to the COVID-19 pandemic, students were barred access. This prompted us to launch and evaluate a new freeware PET/CT viewing system hosted in the university network.

METHODS

 We asked our students to install the multiplatform Fiji viewer with Beth Israel PET/CT plugin (http://petctviewer.org) on their personal computers and connect to a central image database in the university network based on the public domain orthanc server (https://orthanc-server.com). At the end of course, we conducted an anonymous student survey.

RESULTS

 The new system was online within eight days, including regulatory approval. All 76 students (100 %) in the fifth year completed their course work, reading five anonymized PET/CT cases as planned. 41 (53 %) students answered the survey. Fiji was challenging to install with a mean score of 1.8 on a 5-point Likert scale (5 = easy, 1 = difficult). Fiji was more difficult to use (score 3.0) than the previously used diagnostic workstations in the hospital (score 4.1; p < 0.001, paired t-test). Despite the technical challenge, 47 % of students reported having learnt much (scores 4 and 5); only 11 % were negative (scores 1 and 2). 51 % found the PET/CT tasks engaging (scores 4 and 5) while 20 % and 5 % returned scores 2 and 1, respectively.

CONCLUSION

 Despite the initial technical challenge, "hands-on" learning of PET/CT based on the freeware Fiji/orthanc PET/CT-viewer was associated with a high degree of student satisfaction. We plan to continue running the system to give students permanent access to PET/CT cases in native format regardless of time or location.

COV is a readily available quantitative indicator of metabolic heterogeneity for predicting survival of patients with early and locally advanced NSCLC manifesting as central lung cancer

OBJECTIVES

The aim of our study was to investigate the value of a simple metabolic heterogeneity parameter, COV (coefficient of variation), by 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in the prognosis prediction of central lung cancer in early and locally advanced non-small-cell lung cancer (NSCLC).

METHODS

Seventy-three patients with NSCLC manifesting as central lung cancer were included retrospectively, and we used the COV to evaluate metabolic heterogeneity. Univariate and multivariate analyses were used to evaluate the predictive value in terms of overall survival (OS) and progression-free survival (PFS).

RESULT

For all 73 patients with pathologically confirmed NSCLC, 69.9 % had SCC, and 30.1 % had ADC or other types of NSCLC. The COV was a statistically significant factor in the univariate analysis for the OS rate. The optimal cut-off value was 23.1366, with sensitivity = 0.737 and specificity = 0.771. The COV values were dichotomized by this value and included with atelectasis in the Cox multivariate analysis. Both COV and atelectasis were independent risk factors for OS as follows: for COV (HR, 3.162, P = 0.0002), the 2-year OS rate was 62.5 % and 26.9 % in the low and high COV groups, respectively. For atelectasis (HR 2.047, P = 0.041), the 2-year OS rate was 30.6 % and 65.2 % in the groups with and without atelectasis, respectively (P = 0.017). For PFS, only COV (HR, 2.636, P = 0.001) was a significant predictor. The 2-year PFS rate was 29.7 % in the low COV group and 8% in the high COV group.

CONCLUSION

The pre-treatment metabolic heterogeneity parameter COV is a simple and easy way to predict the OS and PFS of patients with NSCLC manifesting as central lung cancer. Therefore, COV plays an important role in prognostic risk classification in NSCLC. The presence of atelectasis could also be a risk factor for poor prognosis of OS.

Prognostic value of the baseline 18F-FDG PET/CT metabolic tumour volume (MTV) and further stratification in low-intermediate (L-I) and high-intermediate (H-I) risk NCCNIPI subgroup by MTV in DLBCL MTV predict prognosis in DLBCL

Introduction

In the era of rituximab, the NCCNIPI is widely used in clinical practice as a tool for the prognosis and risk stratification of diffuse large B-cell lymphoma (DLBCL). In recent years, FDG PET/CT has also shown unique prognostic value. We try to further confirm the prognostic role of metabolic parameters in the overall and subgroups patients.

Methods

We retrospectively analysed 87 DLBCL patients who underwent baseline FDG PET/CT and followed the R-CHOP or R-CHOP-like strategy. The clinical parameters and PET-related metabolic parameters were evaluated.

Results

For all patients, the 2-year PFS rate was 65.5% and the 2-year OS rate was 66.7%. According to Cox multivariate analysis, a high NCCNIPI score (4–8 points) and an MTV greater than 64.1 cm³ (defined by ROC) were independent prognostic factors for PFS and OS. The patients were divided into low, low-intermediate, high-intermediate and high-risk groups by NCCNIPI score. The 2-year PFS rates in each group were 90.9%, 71.3%, 33.2% and 16.7%, and the 2-year OS rates were 100%, 81.6%, 48.4% and 16.7%. In the subsequent subgroup analysis by MTV, it could further stratified low-intermediate and high-intermediate NCCNIPI groups, the P value was 0.068 and 0.069 for PFS, 0.078 and 0.036 for OS.

Conclusions

MTV, as a tumor metabolic volume parameter, and the NCCNIPI score were independent predictors of prognosis in general DLBCL patients. In the low-intermediate and high-intermediate NCCNIPI subgroup, we further confirm the risk stratification abilities of MTV, which could add the prognostic value of NCCNIPI.

Electronic supplementary material

The online version of this article (10.1007/s12149-020-01531-1) contains supplementary material, which is available to authorized users.

Intratumor Heterogeneity Assessed by 18F-FDG PET/CT Predicts Treatment Response and Survival Outcomes in Patients with Hodgkin Lymphoma

RATIONALE AND OBJECTIVES

Radiomic analysis of ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) images enables the extraction of quantitative information of intratumour heterogeneity. This study investigated whether the baseline ¹⁸F-FDG PET/CT radiomics can predict treatment response and survival outcomes in patients with Hodgkin lymphoma (HL).

MATERIALS AND METHODS

Thirty-five patients diagnosed with HL who underwent ¹⁸F-FDG PET/CT scans before and during chemotherapy were retrospectively enrolled in this investigation. For each patient, we extracted 709 radiomic features from pretreatment PET/CT images. Clinical variables (age, gender, B symptoms, bulky tumor, and disease stage) and radiomic signatures (intensity, texture, and wavelet) were analyzed according to response to therapy, progression-free survival (PFS), and overall survival (OS). Receiver operating characteristic curve, logistic regression, and Cox proportional hazards model were used to examine potential predictive and prognostic factors.

RESULTS

High-intensity run emphasis (HIR) of PET and run-length nonuniformity (RLNU) of CT extracted from gray-level run-length matrix (GLRM) in high-frequency wavelets were independent predictive factors for the treatment response (odds ratio [OR] = 36.4, p = 0.014; OR = 30.4, p = 0.020). Intensity nonuniformity (INU) of PET and wavelet short run emphasis (SRE) of CT from GLRM and Ann Arbor stage were independently related to PFS (hazard ratio [HR] = 9.29, p = 0.023; HR = 18.40, p = 0.012; HR = 7.46, p = 0.049). Zone-size nonuniformity (ZSNU) of PET from gray-level size zone matrix (GLSZM) was independently associated with OS (HR = 41.02, p = 0.001). Based on these factors, a prognostic stratification model was devised for the risk stratification of patients. The proposed model allowed the identification of four risk groups for PFS and OS (p < 0.001 and p < 0.001).

CONCLUSION

HIR_{_}GLRM_PET and RLNU_{_}GLRM_CT in high-frequency wavelets serve as independent predictive factors for treatment response. ZSNU_{_}GLSZM_PET, INU_{_}GLRM_PET, and wavelet SRE_{_}GLRM_CT serve as independent prognostic factors for survival outcomes. The present study proposes a prognostic stratification model that may be clinically beneficial in guiding risk-adapted treatment strategies for patients with HL.

Comparison of different automatic methods for the delineation of the total metabolic tumor volume in I-II stage Hodgkin Lymphoma

Total metabolic tumor volume (TMTV) is a promising quantitative biomarker for therapy assessment and prognosis in Hodgkin Lymphoma affected patients that allows prediction of patient outcome. The aim of this study was to evaluate the TMTV reproducibility between different sources of variability in tumor delimitation such as SUV-based thresholds (2.5, 41% and 50%) and software tools (Beth Israel plugin (BI) and LIFEx). Effect of contouring procedure both including single and multiple regions of interest was also studied in patients with multiple lesions, and optimal cut-offs for each studied method were displayed to compare the effect on prognosis. Strong alikeness in TMTV was found for 2.5 under software choice. Best accuracy in contouring compared to visual assessment of the disease was found for BI multiple ROI and LIFEx single ROI drawing. Similar cut-offs were found between both software for all considered thresholds, but best resemblance and highest cut-off due to an overestimation of the TMTV was found for 2.5 SUV. Our findings suggest that optimal reproducibility in TMTV is found for SUV > 2.5 threshold under choice of contouring methodology or software tool, meaning that overestimation of the TMTV threshold using 2.5 looks to be preferable than underestimation with 41% and 50%.

Baseline metabolic tumor volume as a strong predictive and prognostic biomarker in patients with non-small cell lung cancer treated with PD1 inhibitors: a prospective study

BACKGROUND

Reliable predictive and prognostic markers are still lacking for patients treated with programmed death receptor 1 (PD1) inhibitors for non-small cell lung cancer (NSCLC). The purpose of this study was to investigate the prognostic and predictive values of different baseline metabolic parameters, including metabolic tumor volume (MTV), from 18F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET/CT) scans in patients with NSCLC treated with PD1 inhibitors.

METHODS

Maximum and peak standardized uptake values, MTV and total lesion glycolysis (TLG), as well as clinical and biological parameters, were recorded in 75 prospectively included patients with NSCLC treated with PD1 inhibitors. Associations between these parameters and overall survival (OS) were evaluated as well as their accuracy to predict early treatment discontinuation (ETD).

RESULTS

A high MTV and a high TLG were significantly associated with a lower OS (p<0.001). The median OS in patients with MTV above the median (36.5 cm³) was 10.5 months (95% CI: 6.2 to upper limit: unreached), while the median OS in patients with MTV below the median was not reached. Patients with no prior chemotherapy had a poorer OS than patients who had received prior systemic treatment (p=0.04). MTV and TLG could reliably predict ETD (area under the receiver operating characteristic curve=0.76, 95% CI: 0.65 to 0.87 and 0.72, 95% CI: 0.62 to 0.84, respectively).

CONCLUSION

MTV is a strong prognostic and predictive factor in patients with NSCLC treated with PD1 inhibitors and can be easily determined from routine ¹⁸F-FDG PET/CT scans. MTV, could help to personalize immunotherapy and be used to stratify patients in future clinical studies.

Automated Segmentation of Baseline Metabolic Total Tumor Burden in Diffuse Large B-Cell Lymphoma: Which Method Is Most Successful? A Study on Behalf of the PETRA Consortium

Metabolic tumor volume (MTV) is a promising biomarker of pretreatment risk in diffuse large B-cell lymphoma (DLBCL). Different segmentation methods can be used that predict prognosis equally well but give different optimal cutoffs for risk stratification. Segmentation can be cumbersome; a fast, easy, and robust method is needed. Our aims were to evaluate the best automated MTV workflow in DLBCL; determine whether uptake time, compliance or noncompliance with standardized recommendations for ¹⁸F-FDG scanning, and subsequent disease progression influence the success of segmentation; and assess differences in MTVs and discriminatory power of segmentation methods. Methods: One hundred forty baseline ¹⁸F-FDG PET/CT scans were selected from U.K. and Dutch studies on DLBCL to provide a balance between scans at 60 and 90 min of uptake, parameters compliant and noncompliant with standardized recommendations for scanning, and patients with and without progression. An automated tool was applied for segmentation using an SUV of 2.5 (SUV2.5), an SUV of 4.0 (SUV4.0), adaptive thresholding (A50P), 41% of SUV_max (41%), a majority vote including voxels detected by at least 2 methods (MV2), and a majority vote including voxels detected by at least 3 methods (MV3). Two independent observers rated the success of the tool to delineate MTV. Scans that required minimal interaction were rated as a success; scans that missed more than 50% of the tumor or required more than 2 editing steps were rated as a failure. Results: One hundred thirty-eight scans were evaluable, with significant differences in success and failure ratings among methods. The best performing was SUV4.0, with higher success and lower failure rates than any other method except MV2, which also performed well. SUV4.0 gave a good approximation of MTV in 105 (76%) scans, with simple editing for a satisfactory result in additionally 20% of cases. MTV was significantly different for all methods between patients with and without progression. The 41% segmentation method performed slightly worse, with longer uptake times; otherwise, scanning conditions and patient outcome did not influence the tool's performance. The discriminative power was similar among methods, but MTVs were significantly greater using SUV4.0 and MV2 than using other thresholds, except for SUV2.5. Conclusion: SUV4.0 and MV2 are recommended for further evaluation. Automated estimation of MTV is feasible.

Evaluation of the prognostic value of different methods of calculating the tumour metabolic volume with 18F-FDG PET/CT, in patients with diffuse large cell B-cell lymphoma

INTRODUCTION AND OBJECTIVES

Metabolic tumor volume (MTV) is a promising indicator of prognosis in diffuse large B-cell lymphoma (DLBCL). The aim of the present study is to evaluate the different methods for the calculation of the basal metabolic tumor volume with ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) in the patients with DLBCL, relating each one of the volumes measured with progression-free survival (PFS) and overall survival (OS).

METHODOLOGY

This is a retrospective analytical cohort study, in which 34 patients underwent to ¹⁸F-FDG PET/CT baseline prior to treatment. We compared three SUV thresholds 2.5, SUV 40% of the maximum SUV and SUV mean hepatic uptake (PERCIST) for the calculation of MTV and total lesion glycolysis (TLG) biomarkers, relating them to the PFS and OS. The best predictive model was selected based on the Akaike's information criterion (AIC) after performing a Cox proportional hazards regression.

RESULTS

In relation to the PFS, they show statistically significant differences: MTV 2.5, TLG 2.5, MTV 40, TLG 40, MTV and TLG calculated with the PERCIST threshold. Among these, the one that has a lower AIC is MTV 2.5, so it is considered the best parameter to predict the PFS. With respect to OS, it shows statistically significant differences: MTV 2.5, VMT and TLG calculated with the PERCIST threshold. Among these three, the one with the lowest AIC is MTV 2.5, which is why it is considered the best parameter to predict OS. In addition, a higher value of MTV and total tumor glycolysis (TLG), is associated with worse PFS and OS CONCLUSION: The MTV calculated with the threshold SUV 2.5 seems to be the best parameter to predict PFS and OS in patients diagnosed with DLBCL with ¹⁸F-FDG PET/CT.

Deep-Learning 18F-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma

Total metabolic tumor volume (TMTV), calculated from ¹⁸F-FDG PET/CT baseline studies, is a prognostic factor in diffuse large B-cell lymphoma (DLBCL) whose measurement requires the segmentation of all malignant foci throughout the body. No consensus currently exists regarding the most accurate approach for such segmentation. Further, all methods still require extensive manual input from an experienced reader. We examined whether an artificial intelligence–based method could estimate TMTV with a comparable prognostic value to TMTV measured by experts. Methods: Baseline ¹⁸F-FDG PET/CT scans of 301 DLBCL patients from the REMARC trial (NCT01122472) were retrospectively analyzed using a prototype software (PET Assisted Reporting System [PARS]). An automated whole-body high-uptake segmentation algorithm identified all 3-dimensional regions of interest (ROIs) with increased tracer uptake. The resulting ROIs were processed using a convolutional neural network trained on an independent cohort and classified as nonsuspicious or suspicious uptake. The PARS-based TMTV (TMTV_PARS) was estimated as the sum of the volumes of ROIs classified as suspicious uptake. The reference TMTV (TMTV_REF) was measured by 2 experienced readers using independent semiautomatic software. The TMTV_PARS was compared with the TMTV_REF in terms of prognostic value for progression-free survival (PFS) and overall survival (OS). Results: TMTV_PARS was significantly correlated with the TMTV_REF (ρ = 0.76; P < 0.001). Using PARS, an average of 24 regions per subject with increased tracer uptake was identified, and an average of 20 regions per subject was correctly identified as nonsuspicious or suspicious, yielding 85% classification accuracy, 80% sensitivity, and 88% specificity, compared with the TMTV_REF region. Both TMTV results were predictive of PFS (hazard ratio, 2.3 and 2.6 for TMTV_PARS and TMTV_REF, respectively; P < 0.001) and OS (hazard ratio, 2.8 and 3.7 for TMTV_PARS and TMTV_REF, respectively; P < 0.001). Conclusion: TMTV_PARS was consistent with that obtained by experts and displayed a significant prognostic value for PFS and OS in DLBCL patients. Classification of high-uptake regions using deep learning for rapidly discarding physiologic uptake may considerably simplify TMTV estimation, reduce observer variability, and facilitate the use of TMTV as a predictive factor in DLBCL patients.

Metabolic Tumour Volume from PSMA PET/CT Scans of Prostate Cancer Patients during Chemotherapy-Do Different Software Solutions Deliver Comparable Results?

(1) Background: Prostate-specific membrane antigen (PSMA)-derived tumour volume (PSMA-TV) and total lesion PSMA (TL-PSMA) from PSMA PET/CT scans are promising biomarkers for assessing treatment response in prostate cancer (PCa). Currently, it is unclear whether different software tools for assessing PSMA-TV and TL-PSMA produce comparable results. (2) Methods: ⁶⁸Ga-PSMA PET/CT scans from n = 21 patients with castration-resistant PCa (CRPC) receiving chemotherapy were identified from our single-centre database. PSMA-TV and TL-PSMA were calculated with Syngo.via (Siemens) as well as the freely available Beth Israel plugin for FIJI (Fiji Is Just ImageJ) before and after chemotherapy. While statistical comparability was illustrated and quantified via Bland-Altman diagrams, the clinical agreement was estimated by matching PSMA-TV, TL-PSMA and relative changes of both variables during chemotherapy with changes in serum PSA (ΔPSA) and PERCIST (Positron Emission Response Criteria in Solid Tumors). (3) Results: Comparing absolute PSMA-TV and TL-PSMA as well as Bland-Altman plotting revealed a good statistical comparability of both software algorithms. For clinical agreement, classifying therapy response did not differ between PSMA-TV and TL-PSMA for both software solutions and showed highly positive correlations with BR. (4) Conclusions: due to the high levels of statistical and clinical agreement in our CRPC patient cohort undergoing taxane chemotherapy, comparing PSMA-TV and TL-PSMA determined by Syngo.via and FIJI appears feasible.