Baseline metabolic tumour volume is an independent prognostic factor 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.

A different perspective on PET/CT before treatment in patients with Hodgkin lymphoma: importance of volumetric and dissemination parameters

The aim of this study is to investigate the role of the combination of volumetric and dissemination parameters obtained from pretreatment 18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting the interim response and progression status in patients with Hodgkin lymphoma (HL). Pretreatment PET/CT images of HL patients were analyzed with LIFEx software, and volumes of interest (VOIs) were drawn with a fixed SUV 4.0 threshold. MTV, SUVmax, and TLG values were obtained from each VOI. Total MTV (tMTV) was calculated by summing the MTV values in all VOIs, and similarly, total TLG (tTLG) was obtained by summing the TLG values. The distance between the centers of the lesions was noted as Dmax, and the distance between the outermost voxels of the lesions as DmaxVox. tMTV/DmaxVox was calculated by dividing the tMTV value by the DmaxVox value, and tTLG/DmaxVox was calculated by dividing the tTLG value by the DmaxVox value. The correlation of pretreatment PET parameters with response groups (complete/poor) and relapse/progression status (stable/progressive) was statistically evaluated. A total of 52 patients were included in the study. Bulky disease, tMTV, tTLG, and tMTV/DmaxVox values were found to be significantly higher in the poor response group. tMTV > 190.60 ml was found to be the only prognostic factor predicting interim PET response. The tMTV/DmaxVox and tTLG/DmaxVox showed statistically significant differences between the groups with and without progression. tMTV/DmaxVox > 7.70 was found to be the only prognostic factor in predicting relapse/progression. The evaluation of tumor burden and dissemination together in 18F-FDG PET/CT before treatment in patients with HL can help us to predict the results of the patients.

Impact of baseline and interim quantitative PET parameters on outcomes of classical Hodgkin Lymphoma

Currently, analysis of interim PET (iPET) according to the Deauville score (DS) is the most important predictive factor in Hodgkin lymphoma (HL); however, there is room for improvement in its prognostic power. This study aimed to evaluate the prognostic value of quantitative PET analysis (maximum standard uptake value [SUVmax], total metabolic tumor volume [TMTV] and total lesion glicolysis [TLG]) at baseline (PET0) and iPET in a retrospective cohort of newly diagnosed classical HL. For positive iPET (+ iPET), the reduction of quantitative parameters in relation to PET0 (ΔSUVmax, ΔTMTV and ΔTLG) was calculated. Between 2011 and 2017, 234 patients treated with ABVD were analyzed. Median age was 30 years-old, 59% had advanced stage disease, 57% a bulky mass and 25% a + iPET (DS 4-5). At baseline, high TLG was associated with an increased cumulative incidence of failure (CIF) (p = 0.032) while neither SUVmax, TMTV or TLG were associated with overall survival (OS) or progression-free survival (PFS). In multivariate analysis, only iPET was associated with CIF (p < 0.001). Among ΔSUVmax, ΔTMTV and ΔTLG, only a ΔSUVmax ≥ 68.8 was significant for PFS (HR: 0.31, CI95%: 0.11-0.86, p = 0.024). A subset of patients with improved PFS amongst + iPET was identified by the quantitative (ΔSUVmax ≥ 68.8%) analysis. In this real-world Brazilian cohort, with prevalent high-risk patients, quantitative analysis of PET0 did not demonstrate to be prognostic, while a dynamic approach incorporating the ΔSUVmax to + iPET succeeded in refining a subset with better prognosis. These findings warrant validation in larger series and indicate that not all patients with + iPET might need treatment intensification.

Prognostic Value of Baseline Tumor Burden and Tumor Dissemination Extracted From 18 F-FDG PET/CT in a Cohort of Adult Patients With Early or Advanced Hodgkin Lymphoma

PURPOSE

We aimed to assess the prognostic value of baseline tumor burden and dissemination parameters extracted from 18 F-FDG PET/CT in patients with early or advanced Hodgkin lymphoma (HL) treated with ABVD (doxorubicin, bleomycin, vinblastine, and dacarbazine) or escalated BEACOPP (increased bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone).

PATIENTS AND METHODS

Patients aged ≥18 years with classical Hodgkin lymphoma were retrospectively included. Progression-free survival (PFS) analysis of dichotomized clinicobiological and PET/CT parameters (SUV max , TMTV, TLG, D max , and D bulk ) was performed. Optimal cutoff values for quantitative metrics were defined as the values maximizing the Youden index from receiver operating characteristic analysis. PFS rates were estimated with Kaplan-Meier curves, and the log-rank test was used to assess statistical significance. Hazard ratios were calculated using Cox proportional hazards models.

RESULTS

With a median age of 32 years, 166 patients were enrolled. A total of 111 patients had ABVD or ABVD-like treatment with or without radiotherapy and 55 patients with escalated BEACOPP treatment. The median follow-up was 55 months. Only International Prognostic Score (IPS >1), TMTV >107 cm 3 , and TLG >1628 were found to be significant prognostic factors for PFS on univariate analysis. Multivariate analysis revealed that IPS and TLG were independently prognostic and, combined, identified 4 risk groups ( P < 0.001): low (low TLG and low IPS; 4-year PFS, 95%), intermediate-low (high IPS and low TLG; 4-year PFS, 79%), intermediate-high (low IPS and high TLG; 4-year PFS, 78%), and high (high TLG and high IPS; 4-year PFS, 71%).

CONCLUSIONS

Combining baseline TLG with IPS could improve PFS prediction.

Prognostic value of baseline metabolic tumor volume (MTV) for forecasting chemotherapy outcome in early-stage unfavorable Hodgkin lymphoma: Data from the phase III HD17 trial

OBJECTIVES

The prognostic relevance of metabolic tumor volume (MTV) having recently been demonstrated in patients with early-stage favorable and advanced-stage Hodgkin lymphoma. The current study aimed to assess the potential prognostic value of 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in early-stage unfavorable Hodgkin lymphoma patients treated within the German Hodgkin Study Group HD17 trial.

METHODS

18 F-FDG PET/CT images were available for MTV analysis in 154 cases. We used three different threshold methods (SUV2.5 , SUV4.0 , and SUV41% ) to calculate MTV. Receiver-operating-characteristic analysis was performed to describe the value of these parameters in predicting an adequate therapy response. Therapy response was evaluated as PET negativity after 2 cycles of eBEACOPP followed by 2 cycles of ABVD.

RESULTS

All three threshold methods analyzed for MTV showed a positive correlation with the PET response after chemotherapy. Areas under the curve (AUC) were 0.70 (95% CI 0.53-0.87) and 0.65 (0.50-0.80) using the fixed thresholds of SUV4.0 and SUV2.5 , respectively, for MTV- calculation. The calculation of MTV using a relative threshold of SUV41% showed an AUC of 0.63 (0.47-0.79).

CONCLUSIONS

MTV does have predictive value after chemotherapy in early-stage unfavorable Hodgkin lymphoma, particularly when the fixed threshold of SUV4.0 is used for MTV calculation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01356680.

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.

Evaluation of Semiautomatic and Deep Learning-Based Fully Automatic Segmentation Methods on [18F]FDG PET/CT Images from Patients with Lymphoma: Influence on Tumor Characterization

The objective is to assess the performance of seven semiautomatic and two fully automatic segmentation methods on [18F]FDG PET/CT lymphoma images and evaluate their influence on tumor quantification. All lymphoma lesions identified in 65 whole-body [18F]FDG PET/CT staging images were segmented by two experienced observers using manual and semiautomatic methods. Semiautomatic segmentation using absolute and relative thresholds, k-means and Bayesian clustering, and a self-adaptive configuration (SAC) of k-means and Bayesian was applied. Three state-of-the-art deep learning-based segmentations methods using a 3D U-Net architecture were also applied. One was semiautomatic and two were fully automatic, of which one is publicly available. Dice coefficient (DC) measured segmentation overlap, considering manual segmentation the ground truth. Lymphoma lesions were characterized by 31 features. Intraclass correlation coefficient (ICC) assessed features agreement between different segmentation methods. Nine hundred twenty [18F]FDG-avid lesions were identified. The SAC Bayesian method achieved the highest median intra-observer DC (0.87). Inter-observers' DC was higher for SAC Bayesian than manual segmentation (0.94 vs 0.84, p < 0.001). Semiautomatic deep learning-based median DC was promising (0.83 (Obs1), 0.79 (Obs2)). Threshold-based methods and publicly available 3D U-Net gave poorer results (0.56 ≤ DC ≤ 0.68). Maximum, mean, and peak standardized uptake values, metabolic tumor volume, and total lesion glycolysis showed excellent agreement (ICC ≥ 0.92) between manual and SAC Bayesian segmentation methods. The SAC Bayesian classifier is more reproducible and produces similar lesion features compared to manual segmentation, giving the best concordant results of all other methods. Deep learning-based segmentation can achieve overall good segmentation results but failed in few patients impacting patients' clinical evaluation.

Imaging recommendations in pediatric lymphoma: A COG Diagnostic Imaging Committee/SPR Oncology Committee White Paper

Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL) are both malignancies originating in the lymphatic system and both affect children, but many features differ considerably, impacting workup and management. This paper provides consensus-based imaging recommendations for evaluation of patients with HL and NHL at diagnosis and response assessment for both interim and end of therapy (follow-up).

Baseline metabolic tumour burden improves risk stratification in Hodgkin lymphoma: A Children's Oncology Group study

The Children's Oncology Group AHOD0831 study used a positron emission tomography (PET) response-adapted approach in high-risk Hodgkin lymphoma, whereby slow early responders (SERs) received more intensive therapy than rapid early responders (RERs). We explored if baseline PET-based characteristics would improve risk stratification. Of 166 patients enrolled in the COG AHOD0831 study, 94 (57%) had baseline PET scans evaluable for quantitative analysis. For these patients, total body metabolic tumour volume (MTV), total lesion glycolysis (TLG), maximum standardized uptake value (SUVmax ) and peak SUV (SUVpeak ) were obtained. MTV/TLG thresholds were an SUV of 2.5 (MTV2.5 /TLG2.5 ) and 40% of the tumour SUVmax (MTV40% /TLG40% ). TLG2.5 was associated with event-free survival (EFS) in the complete cohort (p = 0.04) and in RERs (p = 0.01), but not in SERs (p = 0.8). The Youden index cut-off for TLG2.5 was 1841. Four-year EFS was 92% for RER/TLG2.5  up to 1841, 60% for RER/TLG2.5  greater than 1841, 74% for SER/TLG2.5  up to 1841 and 79% for SER/TLG2.5  greater than 1841. Second EFS for RER/TLG2.5  up to 1841 was 100%. Thus, RERs with a low baseline TLG2.5 experienced excellent EFS with less intensive therapy, whereas RERs with a high baseline TLG2.5 experienced poor EFS. These findings suggest that patients with a high upfront tumour burden may benefit from intensified therapy, even if they achieve a RER.

PET/CT in Hodgkin Lymphoma: An Update

¹⁸F-FDG-PET/CT is now an integral part of the workup and management of patients with Hodgkin's lymphoma (HL). PET/CT is currently routinely performed for staging and for response assessment at the end of treatment. Interim PET/CT is typically performed after 1-4 of 6-8 chemo/chemoimmunotherapy cycles ± radiation for prognostication and potential treatment escalation or de-escalation early in the course of therapy, a concept known as response-or risk-adapted treatment. Quantitative PET is an area of growing interest. Metrics such as the standardized uptake value (SUV), metabolic tumor volume, total lesion glycolysis, and their changes with treatment are being investigated as more reproducible and, potentially, more accurate predictors of response and prognosis. Despite the progress made in standardizing the use of PET/CT in lymphoma, challenges remain, particularly with respect to its limited positive predictive value. This review highlights the most relevant applications of PET/CT in HL, its strengths and limitations, as well as recent efforts to implement PET/CT-based metrics as promising tools for precision medicine. Finally, the value of PET/CT for response assessment to immunotherapy is discussed.

Molecular Imaging of Lymphoma: Future Directions and Perspectives

More than 250,000 patients die from Hodgkin or non-Hodgkin lymphoma each year. Currently, molecular imaging with ¹⁸F-FDG-PET/CT is the standard of care for lymphoma staging and therapy response assessment. In this review, we will briefly summarize the role of molecular imaging for lymphoma diagnosis, staging, outcome prediction, and prognostication. We discuss future directions in response assessment and surveillance with quantitative PET parameters, the utility of interim assessment, and the differences with response assessment to immunomodulatory therapy. Lastly, we will cover innovations in the field regarding novel tracers and artificial intelligence.

Clinical application of AI-based PET images in oncological patients

Based on the advantages of revealing the functional status and molecular expression of tumor cells, positron emission tomography (PET) imaging has been performed in numerous types of malignant diseases for diagnosis and monitoring. However, insufficient image quality, the lack of a convincing evaluation tool and intra- and interobserver variation in human work are well-known limitations of nuclear medicine imaging and restrict its clinical application. Artificial intelligence (AI) has gained increasing interest in the field of medical imaging due to its powerful information collection and interpretation ability. The combination of AI and PET imaging potentially provides great assistance to physicians managing patients. Radiomics, an important branch of AI applied in medical imaging, can extract hundreds of abstract mathematical features of images for further analysis. In this review, an overview of the applications of AI in PET imaging is provided, focusing on image enhancement, tumor detection, response and prognosis prediction and correlation analyses with pathology or specific gene mutations in several types of tumors. Our aim is to describe recent clinical applications of AI-based PET imaging in malignant diseases and to focus on the description of possible future developments.

Prognostic value of 18F-FDG lesion dissemination features in patients with peripheral T-cell lymphoma (PTCL)

PURPOSE

To explore the prognostic value of the distance between the two lesions that were farthest apart (Dmax) on baseline 18F-FDG PET/CT in peripheral T lymphoma (PTCL) and establish a new prognostic model for predicting the survival outcomes of patients with PTCL.

METHODS

In this study, a retrospective analysis of 95 patients with PTCL who underwent baseline 18F-FDG PET/CT was performed to assess the predictive value of Dmax. The total metabolic tumour volume (TMTV), total lesion glycolysis (TLG), standardized uptake value (SUV), and Dmax were calculated with LIFEx software. Progression-free survival (PFS) and overall survival (OS) were used as endpoints. The prognostic model was developed based on the results of the multivariate analysis. The time-dependent area under the ROC curve (tdAUC), calibration curves, Harrell C-index, and decision curve analysis (DCA) were used to assess the model.

RESULTS

Patients were followed up for a median of 17.0 months. Multivariate analysis showed that bone marrow biopsy (BMB) and Dmax were independent predictors of PFS (HR: 1.889, P = 0.039; HR: 1.965, P = 0.047) and OS (HR: 1.923, P = 0.031; HR: 1.982, P = 0.034). The model consisting of Dmax, TMTV, and BMB had substantial prognostic value for survival outcomes of PTCL and could successfully identify four groups of patients with significantly different prognoses (χ² = 13.731, P = 0.003 for PFS; χ² = 11.841, P = 0.008 for OS). The tdAUC, C-index, calibration curves, and DCA supported that the model was superior to the prognostic index for T-cell lymphoma (PIT) and International Prognostic Index (IPI) scores.

CONCLUSION

BMB and Dmax were independent predictors of PTCL in our study. Moreover, a prognostic model based on the Dmax, TMTV, and BMB could be useful for predicting the survival outcomes of patients with PTCL.

Iterated cross validation method for prediction of survival in diffuse large B-cell lymphoma for small size dataset

Efforts have been made to improve the risk stratification model for patients with diffuse large B-cell lymphoma (DLBCL). This study aimed to evaluate the disease prognosis using machine learning models with iterated cross validation (CV) method. A total of 122 patients with pathologically confirmed DLBCL and receiving rituximab-containing chemotherapy were enrolled. Contributions of clinical, laboratory, and metabolic imaging parameters from fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) scans to the prognosis were evaluated using five regression models, namely logistic regression, random forest, support vector classifier (SVC), deep neural network (DNN), and fuzzy neural network models. Binary classification predictions for 3-year progression free survival (PFS) and 3-year overall survival (OS) were conducted. The 10-iterated fivefold CV with shuffling process was conducted to predict the capability of learning machines. The median PFS and OS were 41.0 and 43.6 months, respectively. Two indicators were found to be independent predictors for prognosis: international prognostic index and total metabolic tumor volume (MTVsum) from FDG PET/CT. For PFS, SVC and DNN (both with accuracy 71%) have the best predictive results, of which outperformed other algorithms. For OS, the DNN has the best predictive result (accuracy 76%). Using clinical and metabolic parameters as input variables, the machine learning methods with iterated CV method add the predictive values for PFS and OS evaluation in DLBCL patients.

Semi-automated 18F-FDG PET segmentation methods for tumor volume determination in Non-Hodgkin lymphoma patients: a literature review, implementation and multi-threshold evaluation

In the treatment of Non-Hodgkin lymphoma (NHL), multiple therapeutic options are available. Improving outcome predictions are essential to optimize treatment. The metabolic active tumor volume (MATV) has shown to be a prognostic factor in NHL. It is usually retrieved using semi-automated thresholding methods based on standardized uptake values (SUV), calculated from ¹⁸F-Fluorodeoxyglucose Positron Emission Tomography (¹⁸F-FDG PET) images. However, there is currently no consensus method for NHL. The aim of this study was to review literature on different segmentation methods used, and to evaluate selected methods by using an in house created software tool. A software tool, MUltiple SUV Threshold (MUST)-segmenter was developed where tumor locations are identified by placing seed-points on the PET images, followed by subsequent region growing. Based on a literature review, 9 SUV thresholding methods were selected and MATVs were extracted. The MUST-segmenter was utilized in a cohort of 68 patients with NHL. Differences in MATVs were assessed with paired t-tests, and correlations and distributions figures. High variability and significant differences between the MATVs based on different segmentation methods (p < 0.05) were observed in the NHL patients. Median MATVs ranged from 35 to 211 cc. No consensus for determining MATV is available based on the literature. Using the MUST-segmenter with 9 selected SUV thresholding methods, we demonstrated a large and significant variation in MATVs. Identifying the most optimal segmentation method for patients with NHL is essential to further improve predictions of toxicity, response, and treatment outcomes, which can be facilitated by the MUST-segmenter.

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.

Influence of Sociodemographic Determinants on the Hodgkin Lymphoma Baseline Characteristics in Long Survivors Patients Enrolled in the Prospective Phase 3 Trial AHL2011

INTRODUCTION

Whereas numerous studies on several cancers describe the link between social conditions and disease severity, little is known about the social and demographic characteristics of Hodgkin lymphoma (HL) patients. At diagnosis, 10-15% of the patients in the advanced stages have a well-known poor outcome owing to their chemoresistance, but the determinants of the more advanced stages remain elusive. The objective of the present study was to decipher the potential impact of social disparities on the disease features at diagnosis and analyze how the sociodemographic patient features could impact the HL outcome of patients with advanced-stage HL enrolled in the AHL2011 trial.

METHODS

This ancillary study was conducted on a cohort of patients from French centers that had recruited more than five patients in the phase III AHL2011 study (NCT0135874). Patients had to be alive at the time of the ancillary study and had to have given their consent to answer the questionnaire. Pre-treatment data (age, gender, stage, B symptoms, IPS), the treatment received, the responses to PET-CT, and the presence of serious adverse events (serious adverse events-SAEs) were all extracted from the AHL2011 trial database. Sociodemographic data-marital status, living area, level of education, socio-professional category, and professional situation-were extracted from the questionnaires. The population density at the point of diagnosis was determined based on ZIP Code, and the distance from the reference medical center was then calculated by the road network. Baseline PET acquisition was performed before any treatment. PET images at baseline were centrally reviewed. The total metabolic tumor volume (TMTV) at the baseline was calculated using a 41% SUVmax cutoff for each lesion. Progression-free survival was defined as the time from randomization to the first progression, relapse, or death from any cause or the last follow-up. The data cutoff for the analyses presented here was 31 October 2017. The progression-free survival was analyzed on an intention-to-treat basis.

RESULTS

Among the 823 patients enrolled in the AHL2011 study, the questionnaire was sent to 394 patients, of whom 232 (58.9%) responded. At the time of HL diagnosis, 61.9% (N = 143) of patients declared that they were not socially isolated, 38.1% (N = 88) that they were single, 163 (71.2%) had a professional activity, and 66 (28.8%) were inactive owing to unemployment, retirement, or sick leave. Of the patients, 31.1% (N = 71) lived in a rural region, compared to 68.9% (N = 157) that lived in an urban region. The residence ZIP Code at the time of HL diagnosis was available for 163 (70%). Sociodemographic characteristics did not influence the presence of usual prognostic factors (ECOG, B symptoms, bulky mass, IPS) except for professional activity, which was associated with more frequent low IPS (0-2) (79 (48.5%) active versus 20 (30.3%) inactive patients; p = 0.012). Likewise, no correlation was observed between TMTV and sociodemographic characteristics. However, the TMTV quartile distribution was different according to the living area, with the two upper quartiles being enriched with patients living in a rural area (p = 0.008). Moreover, a negative correlation between the average number of the living area's inhabitants and TMTV (R Pearson = -0.29, p = 0.0004) was observed.

CONCLUSION

This study focused on sociodemographic parameters in advanced-stage HL patients and shows that professional activity is associated with more favorable disease features (low IPS), while patients living in rural or low-populated areas are more likely to have an unfavorable HL presentation with a high tumor burden (high TMTV). These data suggest that some patient sociodemographic characteristics might impact either access to medical care or environmental exposure, leading to a higher frequency of unfavorable presentations. Further prospective sociodemographic studies are necessary to confirm these preliminary results.

The application of machine learning to imaging in hematological oncology: A scoping review

Background

Here, we conducted a scoping review to (i) establish which machine learning (ML) methods have been applied to hematological malignancy imaging; (ii) establish how ML is being applied to hematological cancer radiology; and (iii) identify addressable research gaps.

Methods

The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews guidelines. The inclusion criteria were (i) pediatric and adult patients with suspected or confirmed hematological malignancy undergoing imaging (population); (ii) any study using ML techniques to derive models using radiological images to apply to the clinical management of these patients (concept); and (iii) original research articles conducted in any setting globally (context). Quality Assessment of Diagnostic Accuracy Studies 2 criteria were used to assess diagnostic and segmentation studies, while the Newcastle-Ottawa scale was used to assess the quality of observational studies.

Results

Of 53 eligible studies, 33 applied diverse ML techniques to diagnose hematological malignancies or to differentiate them from other diseases, especially discriminating gliomas from primary central nervous system lymphomas (n=18); 11 applied ML to segmentation tasks, while 9 applied ML to prognostication or predicting therapeutic responses, especially for diffuse large B-cell lymphoma. All studies reported discrimination statistics, but no study calculated calibration statistics. Every diagnostic/segmentation study had a high risk of bias due to their case-control design; many studies failed to provide adequate details of the reference standard; and only a few studies used independent validation.

Conclusion

To deliver validated ML-based models to radiologists managing hematological malignancies, future studies should (i) adhere to standardized, high-quality reporting guidelines such as the Checklist for Artificial Intelligence in Medical Imaging; (ii) validate models in independent cohorts; (ii) standardize volume segmentation methods for segmentation tasks; (iv) establish comprehensive prospective studies that include different tumor grades, comparisons with radiologists, optimal imaging modalities, sequences, and planes; (v) include side-by-side comparisons of different methods; and (vi) include low- and middle-income countries in multicentric studies to enhance generalizability and reduce inequity.

Radiomics in clinical trials: perspectives on standardization

The term biomarker is used to describe a biological measure of the disease behavior. The existing imaging biomarkers are associated with the known tissue biological characteristics and follow a well-established roadmap to be implemented in routine clinical practice. Recently, a new quantitative imaging analysis approach named radiomics has emerged. It refers to the extraction of a large number of advanced imaging features with high-throughput computing. Extensive research has demonstrated its value in predicting disease behavior, progression, and response to therapeutic options. However, there are numerous challenges to establishing it as a clinically viable solution, including lack of reproducibility and transparency. The data-driven nature also does not offer insights into the underpinning biology of the observed relationships. As such, additional effort is needed to establish it as a qualified biomarker to inform clinical decisions. Here we review the technical difficulties encountered in the clinical applications of radiomics and current effort in addressing some of these challenges in clinical trial designs. By addressing these challenges, the true potential of radiomics can be unleashed.

Prognostic value of combined MTV and ADC derived from baseline FDG PET/MRI in aggressive non-Hodgkins lymphoma

PURPOSE

The aim of this prospective study was to investigate the prognostic value of metabolic tumor volume (MTV) and apparent diffusion coefficient (ADC) from baseline FDG PET/MRI compared to established clinical risk factors in terms of progression free survival (PFS) at 2 years in a cohort of diffuse large B-cell Lymphoma (DLBCL) and high-grade-B-cell lymphoma (HGBCL).

METHODS

Thirty-three patients and their baseline PET/MRI examinations were included. Images were read by two pairs of nuclear medicine physicians and radiologists for defining lymphoma lesions. MTV was computed on PET, and up to six lymphoma target lesions with restricted diffusion was defined for each PET/MRI examination. Minimum ADC (ADC_min) and the corresponding mean ADC (ADC_mean) from the target lesion with the lowest ADC_min were included in the analyses. For the combined PET/MRI parameters, the ratio between MTV and the target lesion with the lowest ADC_min (MTV/ADC_min) and the corresponding ADC_mean (MTV/ADC_mean) was calculated for each patient. Clinical, histological, and PET/MRI parameters were compared between the treatment failure and treatment response group, while survival analyses for each variable was performed by using univariate Cox regression. In case of significant variables in the Cox regression analyses, Kaplan-Meier survival analyses with log-rank test was used to study the effect of the variables on PFS.

RESULTS

ECOC PS scale ≥2 (p = 0.05) and ADC_mean (p = 0.05) were significantly different between the treatment failure group (n = 6) and those with treatment response (n = 27). Survival analyses showed that ADC_mean was associated with PFS (p = 0.02, [HR 2.3 for 1 SD increase]), while combining MTV and ADC did not predict outcome. In addition, ECOG PS ≥2 (p = 0.01, [HR 13.3]) and histology of HGBCL (p = 0.02 [HR 7.6]) was significantly associated with PFS.

CONCLUSIONS

ADC_mean derived from baseline MRI could be a prognostic imaging biomarker for DLBCL and HGBCL. Baseline staging with PET/MRI could therefore give supplementary prognostic information compared to today's standard PET/CT.

Classical Hodgkin Lymphoma: A Joint Clinical and PET Model to Predict Poor Responders at Interim Assessment

(1) This study aimed to investigate whether baseline clinical and Positron Emission Tomography/Computed Tomography (bPET)-derived parameters could help predicting early response to the first two cycles of chemotherapy (Deauville Score at interim PET, DS at iPET) in patients with classical Hodgkin lymphoma (cHL) to identify poor responders (DS ≥ 4) who could benefit from first-line treatment intensification at an earlier time point. (2) cHL patients with a bPET and an iPET imaging study in our Centre’s records (2013−2019), no synchronous/metachronous tumors, no major surgical resection of disease prior to bPET, and treated with two cycles of ABVD chemotherapy before iPET were retrospectively included. Baseline International Prognostic Score for HL (IPS) parameters were collected. Each patient’s bPET total metabolic tumor volume (TMTV) and highest tumoral SUVmax were collected. ROC curves and Youden’s index were used to derive the optimal thresholds of TMTV and SUVmax with regard to the DS (≥4). Chi-square or Fisher’s exact test were used for the univariate analysis. A multivariate analysis was then performed using logistic regression. The type I error rate in the hypothesis testing was set to 5%. (3) A total of 146 patients were included. The optimal threshold to predict a DS ≥ 4 was >177 mL for TMTV and >14.7 for SUVmax (AUC of 0.65 and 0.58, respectively). The univariate analysis showed that only TMTV, SUVmax, advanced disease stage, and age were significantly associated with a DS ≥ 4. A multivariate model was finally derived from TMTV, SUVmax, and age, with an AUC of 0.77. (4) A multivariate model with bPET parameters and age at diagnosis was satisfactorily predictive of poor response at iPET after ABVD induction chemotherapy in cHL patients. More studies are needed to validate these results and further implement DS-predictive factors at baseline in order to prevent poor response and intensify therapeutic strategies a-priori when needed.

Circulating tumor DNA in Hodgkin lymphoma

Somatic mutations of genes involved in NF-κB, PI3K/AKT, NOTCH, and JAK/STAT signaling pathways play an important role in the pathogenesis of Hodgkin lymphoma (HL). HL tumor cells form only about 5% of the tumor mass; however, it was shown that HL tumor-derived DNA could be detected in the bloodstream. This circulating tumor DNA (ctDNA) reflects the genetic profile of HL tumor cells and can be used for qualitative and quantitative analysis of tumor-specific somatic DNA mutations within the concept of liquid biopsy. Overall, the most frequently mutated gene in HL is STAT6; however, the exact spectrum of mutations differs between individual HL histological subtypes. Importantly, reduction of ctDNA plasma levels after initial treatment is highly correlated with prognosis. Therefore, ctDNA shows great promise as a novel tool for non-invasive tumor genome analysis for biomarker driven therapy as well as for superior minimal residual disease monitoring and treatment resistance detection. Here, we summarize the recent advancements of ctDNA analysis in HL with focus on ctDNA detection methodologies, genetic profiling of HL and its clonal evolution, and the emerging prognostic value of ctDNA.

Baseline 18 F-FDG PET/CT May Portend the Prognosis of Patients With Waldenström Macroglobulinemia/Lymphoplasmacytic Lymphoma After First-Line Treatment

PURPOSE

The outcome of patients with Waldenström macroglobulinemia/lymphoplasmacytic lymphoma (WM/LPL) is variable. We aim to study if baseline 18 F-FDG PET/CT has some prognostic significance in WM/LPL.

METHODS

Thirty-three patients with newly diagnosed WM/LPL who underwent baseline 18 F-FDG PET/CT and received active treatment thereafter were recruited in this retrospective study. Semiquantitative indices of baseline 18 F-FDG PET/CT were measured as total lesion glycolysis (TLG), metabolic tumor volume (MTV), and SUV max . The patients were followed up for at least 3 years or until reaching the endpoint, which were defined as progression-free survival (PFS) and the time to next treatment (TTNT).

RESULTS

The overall response rate of the first-line treatment in the recruited patients was 84.8% (28/33). The 3-year PFS and overall survival rates were 56.3% and 89.3%, respectively. Patients with PFS <36 months and TTNT <36 months showed TLG and MTV significantly higher than those with PFS ≥36 months and TTNT ≥36 months ( P < 0.05). SUV max in patients with PFS <36 months was significantly higher than those with PFS ≥36 months ( P = 0.033). Receiver operating characteristic analysis demonstrated that cutoff values of TLG >291.28 SUVbw * mL, MTV >108.78 mL, and SUV max >3.16 were optimal for predicting PFS <36 months. Kaplan-Meier analysis showed that TLG >291.28 SUVbw * mL and MTV >108.78 mL were predictive for shorter PFS ( P = 0.003) and TTNT ( P = 0.002). In multivariate analysis, TLG >291.28 SUVbw * mL and MTV >108.78 mL were independent predictors for shorter PFS (hazard ratio, 3.06; 95% confidence interval, 1.09-8.57; P = 0.033) and TTNT (hazard ratio, 10.01; 95% confidence interval, 2.56-39.22; P = 0.001).

CONCLUSIONS

The metabolic indices of TLG and MTV in baseline 18 F-FDG PET/CT were independent prognostic factors to predict PFS and TTNT in patients with WM/LPL.

High baseline total lesion glycolysis predicts early progression of disease within 24 months in patients with high-tumor-burden follicular lymphoma

Despite the introduction of rituximab-containing regimens, approximately 20% of patients with follicular lymphoma (FL) still experience progression of disease within 24 months (POD24) and have poor overall survival. Therefore, a more accurate risk assessment tool is required. We investigated the predictive value of two new volume-based parameters determined from baseline 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT), baseline total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG), in 45 patients with high-tumor-burden FL who underwent baseline PET/CT. We observed that high TMTV, high TLG, and poor initial treatment response (less than complete [metabolic] response [non-CR/CMR] at the end of induction therapy) independently predicted poor PFS. Notably, POD24-positive patients were more common in the high-TLG group than in the high-TMTV group, which suggests that TLG is a stronger predictor of outcomes than TMTV. Combining baseline TLG and initial treatment response showed that patients with both high TLG and non-CR/CMR experienced significantly poorer outcomes, with a 2 year PFS of 0% (hazard ratio 60.39, P = 0.000002). This combination had 56% sensitivity and 100% specificity for detecting patients who would experience POD24. Baseline TLG and initial treatment response can precisely identify patients at high risk of POD24.

Predictive value of baseline metabolic tumor volume in early-stage favorable Hodgkin Lymphoma - Data from the prospective, multicenter phase III HD16 trial

Background

¹⁸F -fluorodeoxyglucose (FDG) positron emission tomography (PET) plays an important role in the staging and response assessment of lymphoma patients. Our aim was to explore the predictive relevance of metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in patients with early stage Hodgkin lymphoma treated within the German Hodgkin Study Group HD16 trial.

Methods

¹⁸F-FDG PET/CT images were available for MTV and TLG analysis in 107 cases from the HD16 trial. We calculated MTV and TLG using three different threshold methods (SUV_4.0, SUV_41% and SUV_140%L), and then performed receiver-operating-characteristic analysis to assess the predictive impact of these parameters in predicting an adequate therapy response with PET negativity after 2 cycles of chemotherapy.

Results

All three threshold methods analyzed for MTV and TLG calculation showed a positive correlation with the PET response after 2 cycles chemotherapy. The largest area under the curve (AUC) was observed using the fixed threshold of SUV_4.0 for MTV- calculation (AUC 0.69 [95% CI 0.55–0.83]) and for TLG-calculation (AUC 0.69 [0.55–0.82]). The calculations for MTV and TLG with a relative threshold showed a lower AUC: using SUV_140%L AUCs of 0.66 [0.53–0.80] for MTV and 0.67 for TLG [0.54–0.81]) were observed, while with SUV_41% an AUC of 0.61 [0.45–0.76] for MTV, and an AUC 0.64 [0.49–0.80]) for TLG were seen.

Conclusions

MTV and TLG do have a predictive value after two cycles ABVD in early stage Hodgkin lymphoma, particularly when using the fixed threshold of SUV_4.0 for MTV and TLG calculation.

Trial registration

ClinicalTrials.gov NCT00736320.

Prognostic value of pre-transplantation total metabolic tumor volume on 18fluoro-2-deoxy-D-glucose positron emission tomography-computed tomography in relapsed and refractory aggressive lymphoma

Relapsed and refractory aggressive lymphoma have a poor prognosis. High-dose chemotherapy followed by autologous hematopoietic stem cell transplantation (auto-HSCT) is effective in chemosensitive patients. Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is among the few options for non-chemosensitive patients. ¹⁸Fluoro-2-deoxy-D-glucose positron emission tomography-computed tomography (¹⁸FDG-PET/CT) is the standard tool for evaluating response to chemotherapy and residual tumor volume. However, accurate assessment of residual tumor volume is not currently being achieved in clinical practice, and its value in prognostic and therapeutic stratification remains unclear. To answer this question, we investigated the efficacy of quantitative indicators, including total metabolic tumor volume (TMTV), in predicting prognosis after auto-HSCT and allo-HSCT. We retrospectively analyzed 39 patients who received auto-HSCT and 28 who received allo-HSCT. In the auto-HSCT group, patients with a higher TMTV had a poor prognosis due to greater risk of relapse. In the allo-HSCT group, patients with a higher TMTV had a lower progression-free survival rate and a significantly higher relapse rate. Neither Deauville score nor other clinical parameters were associated with prognosis in either group. Therefore, pre-transplant TMTV on PET is effective for prognostic prediction and therapeutic decision-making for relapsed or refractory aggressive lymphoma.

High-risk stage IIB Hodgkin lymphoma treated in the H10 and AHL2011 trials: total metabolic tumor volume is a useful risk factor to stratify patients at baseline

Stage IIB Hodgkin lymphoma (HL) patients, with a mediastinum-to-thorax (M/T) ratio of ≥0.33 or extranodal localization have a poor prognosis and are treated either as limited or advanced stage. We compared these two approaches in patients included in two randomized phase III trials enrolling previously untreated early (H10) or advanced stage HL (AHL2011). We included HL patients with Ann-Arbor stage IIB with M/T ≥0.33 or extranodal involvement enrolled in the H10 or AHL2011 trials with available positron emission tomography at baseline (PET0) and after two cycles of chemotherapy (PET2). Baseline total metabolic tumor volume (TMTV) was calculated using the 41% SUVmax method. PET2 response assessment used the Deauville score. One hundred and fourty-eight patients were eligible, including 83 enrolled in the AHL2011 trial and 65 in the H10 trial. The median TMTV value was 155.5 mL (range, 8.3-782.9 mL), 165.6 mL in AHL2011 and 147 mL in H10. PET2 positivity rates were 16.9% (n=14) and 9.2% (n=6) in AHL2011 and H10 patients, respectively. With a median follow-up of 4.1 years (95% confidence interval [CI]: 3.9-4.4), overall 4-year PFS was 88.0%, 87.0% in AHL2011 and 89.2% in H10. In univariate and mutivariate analyses, baseline TMTV and PET2 response influenced significantly progression-free survival (hazard ratio [HR]=4.94, HR=3.49 respectively). Notably, among the 16 patients who relapsed, 13 (81%) had a baseline TMTV baseline ≥155 mL. Upfront ABVD plus radiation therapy or upfront escBEACOPP without radiotherapy provide similar patient's outcome in high-risk stage IIB HL. TMTV is useful to stratify these patients at baseline.

Risk stratification for relapsed/refractory classical Hodgkin lymphoma integrating pretransplant Deauville score and residual metabolic tumor volume

Pretransplant Deauville score (DS) is an imaging biomarker used for risk stratification in relapsed/refractory classical Hodgkin lymphoma (cHL). However, the prognostic value of residual metabolic tumor volume (rMTV) in patients with DS 4-5 has been less well characterized. We retrospectively assessed 106 patients with relapsed/refractory cHL who underwent autologous stem cell transplantation. Pretransplant DS was determined as 1-3 (59%) and 4-5 (41%), with a markedly inferior event-free survival (EFS) in patients with DS 4-5 (hazard ratio [HR], 3.14; p = .002). High rMTV_41% (rMTV_high , ≥4.4 cm³ ) predicted significantly poorer EFS in patients with DS 4-5 (HR, 3.70; p = .014). In a multivariable analysis, we identified two independent factors predicting treatment failure: pretransplant DS combined with rMTV_41% and disease status (primary refractory vs. relapsed). These two factors allow to stratify patients into three groups with divergent 2-year EFS: 89% for low-risk (51%; relapsed disease and either pretransplant DS 1-3 or DS 4-5/rMTV_low ; HR 1), 65% for intermediate-risk (28%; refractory disease and either DS 1-3 or DS 4-5/rMTV_low ; HR 3.26), and 45% for high-risk (21%; DS 4-5/rMTV_high irrespective of disease status; HR 7.61) groups. Pretransplant DS/rMTV_41% combination and disease status predict the risk of post-transplant treatment failure and will guide risk-stratified approaches in relapsed/refractory cHL.

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.

A comparison of FDG PET/MR and PET/CT for staging, response assessment, and prognostic imaging biomarkers in lymphoma

The aim of the current study was to investigate the diagnostic performance of FDG PET/MR compared to PET/CT in a patient cohort including Hodgkins lymphoma, diffuse large B-cell lymphoma, and high-grade B-cell lymphoma at baseline and response assessment. Sixty-one patients were examined with FDG PET/CT directly followed by PET/MR. Images were read by two pairs of nuclear medicine physicians and radiologists. Concordance for lymphoma involvement between PET/MR and the reference standard PET/CT was assessed at baseline and response assessment. Correlation of prognostic biomarkers Deauville score, criteria of response, SUVmax, SUVpeak, and MTV was performed between PET/MR and PET/CT. Baseline FDG PET/MR showed a sensitivity of 92.5% and a specificity 97.9% compared to the reference standard PET/CT (κ 0.91) for nodal sites. For extranodal sites, a sensitivity of 80.4% and a specificity of 99.5% were found (κ 0.84). Concordance in Ann Arbor was found in 57 of 61 patients (κ 0.92). Discrepancies were due to misclassification of region and not lesion detection. In response assessment, a sensitivity of 100% and a specificity 99.9% for all sites combined were found (κ 0.92). There was a perfect agreement on Deauville scores 4 and 5 and criteria of response between the two modalities. Intraclass correlation coefficient (ICC) for SUVmax, SUVpeak, and MTV values showed excellent reliability (ICC > 0.9). FDG PET/MR is a reliable alternative to PET/CT in this patient population, both in terms of lesion detection at baseline staging and response assessment, and for quantitative prognostic imaging biomarkers.

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.

Baseline FDG PET/CT in free breathing versus deep inspiration breath-hold for pediatric patients with mediastinal lymphoma

INTRODUCTION

The prospective TEDDI protocol investigates the feasibility of radiotherapy delivery in deep inspiration breath-hold (DIBH) for pediatric patients. To secure optimal radiotherapy planning, a diagnostic baseline FDG PET/CT in free breathing (FB) and DIBH was acquired. The anatomical changes in the mediastinum and the effect on PET metrics between the two breathing conditions were assessed for pediatric patients with mediastinal lymphoma.

MATERIAL AND METHODS

Ten patients aged 5-17 were included and had a PET/CT in FB and DIBH. Metabolic active lymphoma volumes were manually delineated with a visually based segmentation method and the PET metrics were extracted. The anatomical lymphoma, lung and heart volumes were delineated on CT.

RESULTS

The lung volume increased while the heart was displaced caudally and separated from the lymphoma in DIBH compared to FB. Both the anatomical and the metabolically active lymphoma volumes appeared different regarding shape and configuration in the two breathing conditions. The image quality of the DIBH PET was equal to the FB PET regarding interpretation and delineation of lymphoma lesions. All PET metrics increased on the DIBH PET compared to the FB PET with the highest increase observed for the maximum standardized uptake value (33%, range 7-56%).

CONCLUSION

Diminished respiratory motion together with anatomical changes within the lymphoma increased all PET metrics in DIBH compared to FB. The anatomical changes observed in DIBH compared to FB are expected to reduce radiation doses to the heart and lungs in pediatric patients with mediastinal lymphoma referred for radiotherapy delivery in DIBH and, thereby, reduce their risk of late effects.

TRIAL REGISTRATION

The Danish Ethical Committee (H-16035870, approved November 24^th 2016), the Danish Data Protection Agency (2012-58-0004, approved 1 January 2017). Registered retrospectively at clinicaltrials.gov (NCT03315546, 20 October 2017).

Automatic Segmentation of Metastatic Breast Cancer Lesions on 18F-FDG PET/CT Longitudinal Acquisitions for Treatment Response Assessment

Metastatic breast cancer patients receive lifelong medication and are regularly monitored for disease progression. The aim of this work was to (1) propose networks to segment breast cancer metastatic lesions on longitudinal whole-body PET/CT and (2) extract imaging biomarkers from the segmentations and evaluate their potential to determine treatment response. Baseline and follow-up PET/CT images of 60 patients from the EPICUREseinmeta study were used to train two deep-learning models to segment breast cancer metastatic lesions: One for baseline images and one for follow-up images. From the automatic segmentations, four imaging biomarkers were computed and evaluated: SULpeak, Total Lesion Glycolysis (TLG), PET Bone Index (PBI) and PET Liver Index (PLI). The first network obtained a mean Dice score of 0.66 on baseline acquisitions. The second network obtained a mean Dice score of 0.58 on follow-up acquisitions. SULpeak, with a 32% decrease between baseline and follow-up, was the biomarker best able to assess patients' response (sensitivity 87%, specificity 87%), followed by TLG (43% decrease, sensitivity 73%, specificity 81%) and PBI (8% decrease, sensitivity 69%, specificity 69%). Our networks constitute promising tools for the automatic segmentation of lesions in patients with metastatic breast cancer allowing treatment response assessment with several biomarkers.

The Utility of Metabolic Parameters on Baseline F-18 FDG PET/CT in Predicting Treatment Response and Survival in Paediatric and Adolescent Hodgkin Lymphoma

Lymphoma is the third most common paediatric cancer. Early detection of high-risk patients is necessary to anticipate those who require intensive therapy and follow-up. Current literature shows that residual tumor avidity on PET (Positron Emission Tomography) following chemotherapy corresponds with decreased survival. However, the value of metabolic parameters has not been adequately investigated. In this retrospective study, we aimed to evaluate the prognostic value of metabolic and other parameters in paediatric and adolescent Hodgkin lymphoma. We recorded tMTV (total Metabolic Tumor Volume), TLG (Total Lesion Glycolysis), and SUVmax (maximum Standard Uptake Value) on baseline PET, as well the presence of bone marrow or visceral involvement. HIV (human immunodeficiency virus) status and baseline biochemistry from clinical records were noted. All patients received stage-specific standard of care therapy. Response assessment on end-of-treatment PET was evaluated according to the Deauville criteria. We found that bone marrow involvement (p = 0.028), effusion (p < 0.001), and treatment response (p < 0.001) on baseline PET, as well as HIV status (p = 0.036) and baseline haemoglobin (p = 0.039), were significantly related to progression-free survival (PFS), whereas only effusion (p = 0.017) and treatment response (p = 0.050) were predictive of overall survival (OS). Only baseline tMTV predicted treatment response (p = 0.017). This confirms the value of F-18 FDG PET/CT (Fluoro-deoxy-glucose Positron Emission Tomography/Computed Tomography) in prognostication in paediatric and adolescent Hodgkin lymphoma; however, further studies are required to define the significance of metabolic parameters.

Radiomic Features of 18F-FDG PET in Hodgkin Lymphoma Are Predictive of Outcomes

Purpose

In the present study, we aimed to investigate whether the radiomic features of baseline ¹⁸F-FDG PET can predict the prognosis of Hodgkin lymphoma (HL).

Methods

A total 65 HL patients (training cohort: n = 49; validation cohort: n = 16) were retrospectively enrolled in the present study. A total of 47 radiomic features were extracted from pretreatment PET images. The least absolute shrinkage and selection operator (LASSO) regression was used to select the most useful prognostic features in the training cohort. The distance between the two lesions that were the furthest apart (D_max) was recorded. The receiver operating characteristic (ROC) curve, Kaplan–Meier method, and Cox proportional hazards model were used to assess the prognostic factors.

Results

Long-zone high gray-level emphasis extracted from a gray-level zone-length matrix (LZHGE_GLZLM) (HR = 9.007; p=0.044) and Dmax (HR = 3.641; p=0.048) were independently correlated with 2-year progression-free survival (PFS). A prognostic stratification model was established based on both risk predictors, which could distinguish three risk categories for PFS (p=0.0002). The 2-year PFS was 100.0%, 64.7%, and 33.3%, respectively.

Conclusions

LZHGE_GLZLM and Dmax were independent prognostic factors for survival outcomes. Besides, we proposed a prognostic stratification model that could further improve the risk stratification of HL patients.

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.

Whole-body MRI radiomics model to predict relapsed/refractory Hodgkin Lymphoma: A preliminary study

PURPOSE

A strong prognostic score that enables a stratification of newly diagnosed Hodgkin Lymphoma (HL) to identify patients at high risk of refractory/relapsed disease is still needed. Our aim was to investigate the potential value of a radiomics analysis pipeline from whole-body MRI (WB-MRI) exams for clinical outcome prediction in patients with HL.

MATERIALS AND METHODS

Index lesions from baseline WB-MRIs of 40 patients (22 females; mean age 31.7 ± 11.4 years) with newly diagnosed HL treated by ABVD chemotherapy regimen were manually segmented on T1-weighted, STIR, and DWI images for texture analysis feature extraction. A machine learning approach based on the Extra Trees classifier and incorporating clinical variables, ¹⁸F-FDG-PET/CT-derived metabolic tumor volume, and WB-MRI radiomics features was tested using cross-validation to predict refractory/relapsed disease.

RESULTS

Relapsed disease was observed in 10/40 patients (25%), two of whom died due to progression of disease and graft versus host disease, while eight reached the complete remission. In total, 1403 clinical and radiomics features were extracted, of which 11 clinical variables and 171 radiomics parameters from both original and filtered images were selected. The 3 best performing Extra Trees classifier models obtained an equivalent highest mean accuracy of 0.78 and standard deviation of 0.09, with a mean AUC of 0.82 and standard deviation of 0.08.

CONCLUSIONS

Our preliminary results demonstrate that a combined machine learning and texture analysis model to predict refractory/relapsed HL on WB-MRI exams is feasible and may help in the clinical outcome prediction in HL patients.

Generation and validation of a PET radiomics model that predicts survival in diffuse large B cell lymphoma treated with R-CHOP14: A SAKK 38/07 trial post-hoc analysis

Functional parameters from positron emission tomography (PET) seem promising biomarkers in various lymphoma subtypes. This study investigated the prognostic value of PET radiomics in diffuse large B-cell lymphoma (DLBCL) patients treated with R-CHOP given either every 14 (testing set) or 21 days (validation set). Using the PyRadiomics Python package, 107 radiomics features were extracted from baseline PET scans of 133 patients enrolled in the Swiss Group for Clinical Cancer Research 38/07 prospective clinical trial (SAKK 38/07) [ClinicalTrial.gov identifier: NCT00544219]. The international prognostic indices, the main clinical parameters and standard PET metrics, together with 52 radiomics uncorrelated features (selected using the Spearman correlation test) were included in a least absolute shrinkage and selection operator (LASSO) Cox regression to assess their impact on progression-free (PFS), cause-specific (CSS), and overall survival (OS). A linear combination of the resulting parameters generated a prognostic radiomics score (RS) whose area under the curve (AUC) was calculated by receiver operating characteristic analysis. The RS efficacy was validated in an independent cohort of 107 DLBCL patients. LASSO Cox regression identified four radiomics features predicting PFS in SAKK 38/07. The derived RS showed a significant capability to foresee PFS in both testing (AUC, 0.709; p < 0.001) and validation (AUC, 0.706; p < 0.001) sets. RS was significantly associated also with CSS and OS in testing (CSS: AUC, 0.721; p < 0.001; OS: AUC, 0.740; p < 0.001) and validation (CSS: AUC, 0.763; p < 0.0001; OS: AUC, 0.703; p = 0.004) sets. The RS allowed risk classification of patients with significantly different PFS, CSS, and OS in both cohorts showing better predictive accuracy respect to clinical international indices. PET-derived radiomics may improve the prediction of outcome in DLBCL patients.

Pretherapy metabolic tumor volume associates with response to CD30 CAR T cells in Hodgkin lymphoma

High MTV immediately before lymphodepletion and CD30.CAR-T cell infusion is associated with shorter PFS.

High pretherapy MTV is associated with high circulating CD3⁺PD-1⁺ T cells after CD30.CAR-T infusion.

Our group has recently demonstrated that chimeric antigen receptor T-cell therapy targeting the CD30 antigen (CD30.CAR-T) is highly effective in patients with relapsed and refractory (r/r) classical Hodgkin lymphoma (cHL). Despite high rates of clinical response, relapses and progression were observed in a subset of patients. The objective of this study was to characterize clinical and correlative factors associated with progression-free survival (PFS) after CD30.CAR-T cell therapy. We evaluated correlatives in 27 patients with r/r cHL treated with lymphodepletion and CD30.CAR-T cells. With a median follow-up of 9.5 months, 17 patients (63%) progressed, with a median PFS of 352 days (95% confidence interval: 116-not reached), and 2 patients died (7%) with a median overall survival of not reached. High metabolic tumor volume (MTV, >60 mL) immediately before lymphodepletion and CD30.CAR-T cell infusion was associated with inferior PFS (log rank, P = .02), which persisted after adjusting for lymphodepletion and CAR-T dose (log rank, P = .01 and P = .006, respectively). In contrast, receiving bridging therapy, response to bridging therapy, CD30.CAR-T expansion/persistence, and percentage of CD3⁺PD-1⁺ lymphocytes over the first 6 weeks of therapy were not associated with differences in PFS. In summary, this study reports an association between high baseline MTV immediately before lymphodepletion and CD30.CAR-T cell infusion and worse PFS in patients with r/r cHL. This trial was registered at www.clinicaltrials.gov as #NCT02690545.

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.

Latest advances in the management of classical Hodgkin lymphoma: the era of novel therapies

Hodgkin lymphoma is a highly curable disease. Although most patients achieve complete response following frontline therapy, key unmet clinical needs remain including relapsed/refractory disease, treatment-related morbidity, impaired quality of life and poor outcome in patients older than 60 years. The incorporation of novel therapies, including check point inhibitors and antibody-drug conjugates, into the frontline setting, sequential approaches, and further individualized treatment intensity may address these needs. We summarize the current treatment options for patients with classical Hodgkin lymphoma from frontline therapy to allogeneic hematopoietic stem cell transplantation and describe novel trials in the field.

Overview and recent advances in PET/CT imaging in lymphoma and multiple myeloma

Imaging in hematological diseases has evolved extensively over the past several decades. Positron emission tomography/computed tomography (PET/CT) with of 2-[18 F]-fluoro-2-deoxy-d-glucose ([18 F] FDG) is currently essential for accurate staging and for early and late therapy response assessment for all FDG-avid lymphoproliferative histologies. The widely adopted visual Deauville 5-point scale and Lugano Classification recommendations have recently standardized PET scans interpretation and improved lymphoma patient management. In addition [18 F] FDG-PET is routinely recommended for initial evaluation and treatment response assessment of Multiple Myeloma (MM) with significant contribution in risk-stratification and prognostication, although magnetic resonance imaging remains the Gold Standard for the assessment of bone marrow involvement. In this review, an overview of the role of [18 F] FDG-PET, in hematological malignancies is provided, particularly focusing on Hodgkin lymphoma (HL) and Diffuse Large B Cell Lymphoma (DLBCL), both in adult and pediatric populations, and MM, at each point of patient management. Potential alternative molecular imaging applications in this field, such as non-[18 F] FDG-tracers, whole body magnetic resonance imaging (WB-MRI), hybrid PET/MRI and emerging radiomics research are briefly presented.

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.

Additional value of volumetric and texture analysis on FDG PET assessment in paediatric Hodgkin lymphoma: an Italian multicentric study protocol

INTRODUCTION

Assessment of response to therapy in paediatric patients with Hodgkin lymphoma (HL) by 18F-fluorodeoxyglucose positron emission tomography/CT has become a powerful tool for the discrimination of responders from non-responders. The addition of volumetric and texture analyses can be regarded as a valuable help for disease prognostication and biological characterisation. Based on these premises, the Hodgkin Lymphoma Study Group of the Associazione Italiana Ematologia Oncologia Pediatrica (AIEOP) has designed a prospective evaluation of volumetric and texture analysis in the Italian cohort of patients enrolled in the EuroNet-PHL-C2.

METHODS AND ANALYSIS

The primary objective is to compare volumetric assessment in patiens with HL at baseline and during the course of therapy with standard visual and semiquantitative analyses. The secondary objective is to identify the impact of volumetric and texture analysis on bulky masses. The tertiary objective is to determine the additional value of multiparametric assessment in patients having a partial response on morphological imaging.The overall cohort of the study is expected to be round 400-500 patients, with approximately half presenting with bulky masses. All PET scans of the Italian cohort will be analysed for volumetric assessment, comprising metabolic tumour volume and total lesion glycolysis at baseline and during the course of therapy. A dedicated software will delineate semiautomatically contours using different threshold methods, and the impact of each segmentation techniques will be evaluated. Bulky will be defined on contiguous lymph node masses ≥200 mL on CT/MRI. All bulky masses will be outlined and analysed by the same software to provide textural features. Morphological assessment will be based on RECIL 2017 for response definition.

ETHICS AND DISSEMINATION

The current study has been ethically approved (AIFA/SC/P/27087 approved 09/03/2018; EudraCT 2012-004053-88, EM-04). The results of the different analyses performed during and after study completion the will be actively disseminated through peer-reviewed journals, conference presentations, social media, print media and internet.

Clinical Impact of Extranodal Metabolic Tumor Volume in 240 Diffuse Large B cell Lymphoma Patients with Extranodal Involvement

The present study is to investigate whether extranodal (EN) metabolic tumor volume (MTV) would have a specific clinical meaning for survival in EN diffuse large B cell lymphoma (DLBCL) patients. Two hundred forty DLBCL patients with EN involvement received 18F-fluorodeoxygenase (FDG) positron emission tomography/computed tomography (PET/CT) were enrolled. Survival analysis revealed that low EN MTV (PFS [progression-free survival], HR = 0.278, 95% CI = 0.127-0.807, p = 0.001; OS [overall survival], HR = 0.320, 95% CI = 0.145-0.703, p = 0.003), low total MTV (PFS, HR = 0.194, 95% CI = 0.085-0.445, p < 0.001; OS, HR = 0.213, 95% CI = 0.092-0.491, p < 0.007), and high National Cancer Center Network-International Prognostic Index score (PFS, HR = 3.152, 95% CI = 1.732-5.734, p < 0.001; OS, HR = 2.457, 95% CI = 1.363-4.430, p = 0.003) were independently associated with survivals in the patients. Our data showed that EN MTV is a useful and novel prognostic parameter for predicting survival in DLBCL patients with EN involvement.

Circulating tumour DNA in B-cell lymphomas: current state and future prospects

Circulating tumour DNA (ctDNA) is a highly versatile analyte and an emerging biomarker for detection of tumour-specific sequences in lymphoid malignancies. Since ctDNA is derived from tumour cells throughout the body, it overcomes fundamental limitations of tissue biopsies by capturing the complete molecular profile of tumours, including those from inaccessible anatomic locations. Assays for ctDNA are minimally invasive and serial sampling monitors the effectiveness of therapy and identifies minimal residual disease below the detection limit of standard imaging scans. Dynamic changes in ctDNA levels measure real-time tumour kinetics, and early reductions in ctDNA during treatment correlate with clinical outcomes in multiple B-cell lymphomas. After therapy, ctDNA can effectively discriminate between patients who achieved a complete molecular remission from those with residual treatment-resistant disease. Serial monitoring of ctDNA after therapy can detect early molecular relapse and identify drug-resistant clones that harbour targetable mutations. In order for ctDNA to reach its full potential, the standardization and harmonization of the optimal pre-analytical and analytical techniques for B-cell lymphomas is a critically necessary requirement. Prospective validation of ctDNA within clinical studies is also required to determine its clinical utility as an adjunctive decision-making tool.