Effect of synthetic CT on dose-derived toxicity predictors for MR-only prostate radiotherapy.

Objectives: Toxicity-driven adaptive radiotherapy (RT) is enhanced by the superior soft tissue contrast of magnetic resonance (MR) imaging compared with conventional computed tomography (CT). However, in an MR-only RT pathway synthetic CTs (sCT) are required for dose calculation. This study evaluates 3 sCT approaches for accurate rectal toxicity prediction in prostate RT. Methods: Thirty-six patients had MR (T2-weighted acquisition optimized for anatomical delineation, and T1-Dixon) with same day standard-of-care planning CT for prostate RT. Multiple sCT were created per patient using bulk density (BD), tissue stratification (TS, from T1-Dixon) and deep-learning (DL) artificial intelligence (AI) (from T2-weighted) approaches for dose distribution calculation and creation of rectal dose volume histograms (DVH) and dose surface maps (DSM) to assess grade-2 (G2) rectal bleeding risk. Results: Maximum absolute errors using sCT for DVH-based G2 rectal bleeding risk (risk range 1.6% to 6.1%) were 0.6% (BD), 0.3% (TS) and 0.1% (DL). DSM-derived risk prediction errors followed a similar pattern. DL sCT has voxel-wise density generated from T2-weighted MR and improved accuracy for both risk-prediction methods. Conclusions: DL improves dosimetric and predicted risk calculation accuracy. Both TS and DL methods are clinically suitable for sCT generation in toxicity-guided RT, however, DL offers increased accuracy and offers efficiencies by removing the need for T1-Dixon MR. Advances in knowledge: This study demonstrates novel insights regarding the effect of sCT on predictive toxicity metrics, demonstrating clear accuracy improvement with increased sCT resolution. Accuracy of toxicity calculation in MR-only RT should be assessed for all treatment sites where dose to critical structures will guide adaptive-RT strategies. Clinical trial registration number: Patient data were taken from an ethically approved (UK Health Research Authority) clinical trial run at Guy's and St Thomas' NHS Foundation Trust. Study Name: MR-simulation in Radiotherapy for Prostate Cancer. ClinicalTrials.gov Identifier: NCT03238170.

Healthy tissue metabolism assessed by [18F]FDG PET/CT as a marker of prognosis and adverse events in advanced Hodgkin lymphoma patients.

The aim of the study was to assess healthy tissue metabolism (HTM) using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) during chemotherapy in Hodgkin lymphoma (HL) and the association of HTM with baseline metabolic tumour volume (MTV), haematological parameters, adverse events (AEs), early response and progression-free survival (PFS). We retrospectively identified 200 patients with advanced HL from the RATHL trial with [18F]FDG-PET/CT before (PET0) and following 2 cycles of chemotherapy (PET2). [18F]FDG-uptake was measured in bone marrow (BM), spleen, liver and mediastinal blood pool (MBP). Deauville score (DS) 1-3 was used to classify responders and DS 4-5, non-responders. [18F]FDG-uptake decreased significantly in BM and spleen and increased in liver and MBP at PET2 (all p < 0.0001), but was not associated with MTV. Higher BM uptake at PET0 was associated with lower baseline haemoglobin and higher absolute neutrophil counts, platelets, and white blood cells. High BM, spleen, and liver uptake at PET0 was associated with neutropenia after cycles 1-2. BM uptake at PET0 was associated with treatment failure at PET2 and non-responders with higher BM uptake at PET2 had significantly inferior PFS (p = 0.023; hazard ratio = 2.31). Based on these results, we concluded that the change in HTM during chemotherapy was most likely a direct impact of chemotherapy rather than a change in MTV. BM uptake has prognostic value in HL.

Investigator choice of standard therapy versus sequential novel therapy arms in the treatment of relapsed follicular lymphoma (REFRACT): study protocol for a multi-centre, open-label, randomised, phase II platform trial.

BACKGROUND: Relapsed or refractory follicular lymphoma (rrFL) is an incurable disease associated with shorter remissions and survival after each line of standard therapy. Many promising novel, chemotherapy-free therapies are in development, but few are licensed as their role in current treatment pathways is poorly defined. METHODS: The REFRACT trial is an investigator-initiated, UK National Cancer Research Institute, open-label, multi-centre, randomised phase II platform trial aimed at accelerating clinical development of novel therapies by addressing evidence gaps. The first of the three sequential novel therapy arms is epcoritamab plus lenalidomide, to be compared with investigator choice standard therapy (ICT). Patients aged 18 years or older with biopsy proven relapsed or refractory CD20 positive, grade 1-3a follicular lymphoma and assessable disease by PET-CT are eligible. The primary outcome is complete metabolic response by PET-CT at 24 weeks using the Deauville 5-point scale and Lugano 2014 criteria. Secondary outcomes include overall metabolic response, progression-free survival, overall survival, duration of response, and quality of life assessed by EQ-5D-5 L and FACT-Lym. The trial employs an innovative Bayesian design with a target sample size of 284 patients: 95 in the ICT arm and 189 in the novel therapy arms. DISCUSSION: Whilst there are many promising novel drugs in early clinical development for rrFL, understanding the relative efficacy and safety of these agents, and their place in modern treatment pathways, is limited by a lack of randomised trials and dearth of published outcomes for standard regimens to act as historic controls. Therefore, the aim of REFRACT is to provide an efficient platform to evaluate novel agents against standard therapies for rrFL. The adaptive Bayesian power prior methodology design will minimise patient numbers and accelerate trial delivery. TRIAL REGISTRATION: ClinicalTrials.gov: NCT05848765; 08-May-2023. EUDRACT: 2022-000677-75; 10-Feb-2022.

Guideline for the diagnosis and management of marginal zone lymphomas: a British Society of Haematology guideline

The objective of this guideline is to provide healthcare professionals with clear guidance on the diagnosis and management of patients with marginal zone lymphoma (MZL).

Long-Term Follow-Up of the Response-Adjusted Therapy for Advanced Hodgkin Lymphoma Trial.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.We analyzed long-term results of the response-adapted trial for adult patients with advanced-stage Hodgkin lymphoma. The aim was to confirm noninferiority of treatment de-escalation by omission of bleomycin from doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) for interim fluorodeoxyglucose positron emission tomography (iPET)-negative patients and assess efficacy and long-term safety for iPET-positive patients who underwent treatment intensification with escalated bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisolone (BEACOPP/BEACOPP14). The median follow-up is 7.3 years. For all patients, the 7-year progression-free survival (PFS) and overall survival (OS) are 78.2% (95% CI, 75.6 to 80.5) and 91.6% (95% CI, 89.7 to 93.2), respectively. The 1.3% difference in 3-year PFS (95% CI, -3.0 to 4.7) between ABVD and doxorubicin, vinblastine, and dacarbazine (AVD) now falls within the predefined noninferiority margin. Among 172 patients with positive iPET, the 7-year PFS was 65.9% (95% CI, 58.1 to 72.6) and the 7-year OS was 83.2% (95% CI, 76.2 to 88.3). The cumulative incidence of second malignancies at 7 years was 5.5% (95% CI, 4.0 to 7.5) for those receiving ABVD/AVD and 2.5% (95% CI, 0.8 to 7.7) for those escalated to BEACOPP. With extended follow-up, these results confirm noninferiority of treatment de-escalation after a negative iPET. Escalation with BEACOPP for iPET-positive patients is effective and safe, with no increase in second malignancies.

Metabolic tumour volume in Hodgkin lymphoma-A comparison between manual and AI-based analysis.

AIM: To compare total metabolic tumour volume (tMTV), calculated using two artificial intelligence (AI)-based tools, with manual segmentation by specialists as the reference. METHODS: Forty-eight consecutive Hodgkin lymphoma (HL) patients staged with [18F] fluorodeoxyglucose positron emission tomography/computed tomography were included. The median age was 35 years (range: 7-75), 46% female. The tMTV was automatically measured using the AI-based tools positron emission tomography assisted reporting system (PARS) (from Siemens) and RECOMIA (recomia.org) without any manual adjustments. A group of eight nuclear medicine specialists manually segmented lesions for tMTV calculations; each patient was independently segmented by two specialists. RESULTS: The median of the manual tMTV was 146 cm3 (interquartile range [IQR]: 79-568 cm3) and the median difference between two tMTV values segmented by different specialists for the same patient was 26 cm3 (IQR: 10-86 cm3). In 22 of the 48 patients, the manual tMTV value was closer to the RECOMIA tMTV value than to the manual tMTV value segmented by the second specialist. In 11 of the remaining 26 patients, the difference between the RECOMIA tMTV and the manual tMTV was small (<26 cm3, which was the median difference between two manual tMTV values from the same patient). The corresponding numbers for PARS were 18 and 10 patients, respectively. CONCLUSION: The results of this study indicate that RECOMIA and Siemens PARS AI tools could be used without any major manual adjustments in 69% (33/48) and 58% (28/48) of HL patients, respectively. This demonstrates the feasibility of using AI tools to support physicians measuring tMTV for assessment of prognosis in clinical practice.

Evaluation of manual and automated approaches for segmentation and extraction of quantitative indices from [18F]FDG PET-CT images.

Utilisation of whole organ volumes to extract anatomical and functional information from computed tomography (CT) and positron emission tomography (PET) images may provide key information for the treatment and follow-up of cancer patients. However, manual organ segmentation, is laborious and time-consuming. In this study, a CT-based deep learning method and a multi-atlas method were evaluated for segmenting the liver and spleen on CT images to extract quantitative tracer information from Fluorine-18 fluorodeoxyglucose ([18F]FDG) PET images of 50 patients with advanced Hodgkin lymphoma (HL). Manual segmentation was used as the reference method. The two automatic methods were also compared with a manually defined volume of interest (VOI) within the organ, a technique commonly performed in clinical settings. Both automatic methods provided accurate CT segmentations, with the deep learning method outperforming the multi-atlas with a DICE coefficient of 0.93 ± 0.03 (mean ± standard deviation) in liver and 0.87 ± 0.17 in spleen compared to 0.87 ± 0.05 (liver) and 0.78 ± 0.11 (spleen) for the multi-atlas. Similarly, a mean relative error of -3.2% for the liver and -3.4% for the spleen across patients was found for the mean standardized uptake value (SUVmean) using the deep learning regions while the corresponding errors for the multi-atlas method were -4.7% and -9.2%, respectively. For the maximum SUV (SUVmax), both methods resulted in higher than 20% overestimation due to the extension of organ boundaries to include neighbouring, high-uptake regions. The conservative VOI method which did not extend into neighbouring tissues, provided a more accurate SUVmaxestimate. In conclusion, the automatic, and particularly the deep learning method could be used to rapidly extract information of the SUVmeanwithin the liver and spleen. However, activity from neighbouring organs and lesions can lead to high biases in SUVmaxand current practices of manually defining a volume of interest in the organ should be considered instead.

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.

Interobserver variability in interim PET assessment in Hodgkin lymphoma-reasons and solutions.

INTRODUCTION: Interim PET (iPET) assessment is important for response adaptation in Hodgkin lymphoma (HL). The current standard for iPET assessment is the Deauville score (DS). The aim of our study was to evaluate the causes of interobserver variability in assigning the DS for iPET in HL patients and to make suggestions for improvement. METHODS: All evaluable iPET scans from the RAPID study were re-read by two nuclear physicians, blinded to the results and patient outcomes in the RAPID trial. The iPET scans were assessed visually according to the DS and, thereafter, quantified using the qPET method. All discrepancies of more than one DS level were re-evaluated by both readers to find the reason for the discordant result. RESULTS: In 249/441 iPET scans (56%) a concordant visual DS result was achieved. A "minor discrepancy" of one DS level occurred in 144 scans (33%) and a "major discrepancy" of more than one DS level in 48 scans (11%). The main causes for major discrepancies were 1) different interpretation of PET-positive lymph nodes-malignant vs. inflammatory; 2) lesions missed by one reader and 3) different assessment of lesions in activated brown fat tissue. In 51% of the minor discrepancy scans with residual lymphoma uptake, additional quantification resulted in a concordant quantitative DS result. CONCLUSION: Discordant visual DS assessment occurred in 44% of all iPET scans. The main reason for major discrepancies was the different interpretation of PET positive lymph nodes as malignant or inflammatory. Disagreements in evaluation of the hottest residual lymphoma lesion can be solved by the use of semi-quantitative assessment.

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

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

Application of the Lugano Classification for Initial Evaluation, Staging, and Response Assessment of Hodgkin and Non-Hodgkin Lymphoma: The PRoLoG Consensus Initiative (Part 2-Technical).

The aim of this initiative was to provide consensus recommendations from a consortium of academic and industry experts in the field of lymphoma and imaging for the consistent application of imaging assessment with the Lugano classification. Methods: Consensus was obtained through a series of meetings from July 2019 to October 2021 sponsored by the PINTaD (Pharma Imaging Network for Therapeutics and Diagnostics) as part of the ProLoG (PINTaD RespOnse criteria in Lymphoma wOrking Group) consensus initiative. Results: Consensus recommendations encompass all technical imaging aspects of the Lugano classification. Some technical considerations for PET/CT and diagnostic CT are clarified with regards to required imaging series and scan visits, as well as acquisition and reconstruction of PET images and influence of lesion size and background activity. Recommendations are given on the role of imaging and clinical reviewers as well as on training and monitoring. Finally, an example template of an imaging case report form is provided to support efficient collection of data with Lugano Classification. Conclusion: Consensus recommendations are made to comprehensively address technical and imaging areas of inconsistency and ambiguity in the classification encountered by end users. Such guidance should be used to support standardized acquisition and evaluation with the Lugano 2014.

Impact of positron emission tomography - computed tomography status on progression-free survival for relapsed follicular lymphoma patients undergoing autologous stem cell transplantation.

The optimum management approach for patients with relapsed or refractory follicular lymphoma remains uncertain. Autologous stem cell transplantation (autoSCT) is considered a standard option in suitable, younger patients with relapsed follicular lymphoma. AutoSCT is associated with very durable remissions in a minority of subjects, but also with significant, well-established toxicities. Although positron emission tomography (PET) status prior to autoSCT is an established prognostic factor in diffuse large B-cell lymphoma and Hodgkin lymphoma, no data exist in follicular lymphoma. We describe survival outcomes according to pre-transplant PET status, classified by the Lugano criteria into complete metabolic remission (CMR) versus non-CMR, in 172 patients with relapsed or refractory follicular lymphoma within a national, multicenter, retrospective British Society of Blood and Marrow Transplantation and Cellular Therapy registry study. The median number of lines of therapy prior to SCT was three (range, 1-6). The median follow-up after SCT was 27 months (range, 3-70). The median progression-free survival for all patients after autoSCT was 28 months (interquartile range, 23- 36). There was no interaction between age at transplantation, sex, number of months since last relapse, Karnofsky performance status or comorbidity index and achieving CMR prior to autoSCT. Superior progression-free survival was observed in 115 (67%) patients obtaining CMR versus 57 (33%) non-CMR patients (3-year progression-free survival 50% vs. 22%, P=0.011) and by pre-SCT Deauville score (continuous variable 1-5, hazard ratio [HR]=1.32, P=0.049). PET status was independently associated with progression-free status (non-CMR HR=2.02, P=0.003), overall survival (non-CMR HR=3.08, P=0.010) and risk of relapse (non-CMR HR=1.64, P=0.046) after autoSCT by multivariable analysis. Our data suggest that pre- SCT PET status is of clear prognostic value and may help to improve the selection of patients for autoSCT.

Relapse patterns in early-PET negative, limited-stage Hodgkin lymphoma (HL) after ABVD with or without radiotherapy-a joint analysis of EORTC/LYSA/FIL H10 and NCRI RAPID trials.

In the H10 and RAPID randomised trials, chemotherapy+radiotherapy (combined modalities treatment, CMT) was compared with chemotherapy (C) in limited-stage Hodgkin lymphoma (HL), with negative early positron emission tomography (ePETneg). We analysed patterns of relapses in the H10 trial, validated findings in the RAPID trial and performed a combined analysis stratified by trial. The impact of radiotherapy (RT) on risk of relapse was studied using adjusted Cox models, with time-varying effects. In H10, 1,059 ePETneg patients were included (465 European Organisation for Research and Treatment of Cancer (EORTC) favourable [F], 594 unfavourable [U]). Among the F patients, 2/227 (1%) relapsed after CMT, 30/238 (13%) after C: of these relapses, 21/30 (70%) occurred in less than 2 years and 25/30 (83%) affected originally involved areas. Among the U group, 16/292 (5%) relapsed after CMT: 8/16 (50%) in less than 2 years, 11/16 (69%) in originally involved areas. After C 30/302 (10%) relapsed: 27/30 (90%) in less than 2 years, and 26/30 (87%) in originally involved areas. Similar results were observed in 419 ePETneg RAPID patients (241 F, 128 U, 50 unclassified): among F patients, 6/118 (5%) relapsed after CMT; 13/123 (11%) after C: 11/13 (85%) in less than 2 years and 11/13 (85%) affecting originally involved areas. In U patients, 3/65 (5%) relapsed after CMT and 5/63 (8%) after C. In both trials, omitting RT in ePETneg HL resulted in more early relapses, mainly affecting originally involved areas. RT significantly reduced risk of early relapses in the combined stratified analysis.

A tumor volume and performance status model to predict outcome before treatment in diffuse large B-cell lymphoma.

Aggressive large B-cell lymphoma (LBCL) has variable outcomes. Current prognostic tools use factors for risk stratification that inadequately identify patients at high risk of refractory disease or relapse before initial treatment. A model associating 2 risk factors, total metabolic tumor volume (TMTV) >220 cm3 (determined by fluorine-18 fluorodeoxyglucose positron emission tomography coupled with computed tomography) and performance status (PS) ≥2, identified as prognostic in 301 older patients in the REMARC trial (#NCT01122472), was validated in 2174 patients of all ages treated in 2 clinical trials, PETAL (Positron Emission Tomography-Guided Therapy of Aggressive Non-Hodgkin Lymphomas; N = 510) and GOYA (N = 1315), and in real-world clinics (N = 349) across Europe and the United States. Three risk categories, low (no factors), intermediate (1 risk factor), and high (2 risk factors), significantly discriminated outcome in most of the series. Patients with 2 risk factors had worse outcomes than patients with no risk factors in the PETAL, GOYA, and real-world series. Patients with intermediate risk also had significantly worse outcomes than patients with no risk factors. The TMTV/Eastern Cooperative Oncology Group-PS combination outperformed the International Prognostic Index with a positive C-index for progression-free survival and overall survival in most series. The combination of high TMTV > 220 cm3 and ECOG-PS ≥ 2 is a simple clinical model to identify aggressive LBCL risk categories before treatment. This combination addresses the unmet need to better predict before treatment initiation for aggressive LBCL the patients likely to benefit the most or not at all from therapy.

Proposed New Dynamic Prognostic Index for Diffuse Large B-Cell Lymphoma: International Metabolic Prognostic Index.

PURPOSE: Baseline metabolic tumor volume (MTV) is a promising biomarker in diffuse large B-cell lymphoma (DLBCL). Our aims were to determine the best statistical relationship between MTV and survival and to compare MTV with the International Prognostic Index (IPI) and its individual components to derive the best prognostic model. METHODS: PET scans and clinical data were included from five published studies in newly diagnosed diffuse large B-cell lymphoma. Transformations of MTV were compared with the primary end points of 3-year progression-free survival (PFS) and overall survival (OS) to derive the best relationship for further analyses. MTV was compared with IPI categories and individual components to derive the best model. Patients were grouped into three groups for survival analysis using Kaplan-Meier analysis; 10% at highest risk, 30% intermediate risk, and 60% lowest risk, corresponding with expected clinical outcome. Validation of the best model was performed using four studies as a test set and the fifth study for validation and repeated five times. RESULTS: The best relationship for MTV and survival was a linear spline model with one knot located at the median MTV value of 307.9 cm3. MTV was a better predictor than IPI for PFS and OS. The best model combined MTV with age as continuous variables and individual stage as I-IV. The MTV-age-stage model performed better than IPI and was also better at defining a high-risk group (3-year PFS 46.3% v 58.0% and 3-year OS 51.5% v 66.4% for the new model and IPI, respectively). A regression formula was derived to estimate individual patient survival probabilities. CONCLUSION: A new prognostic index is proposed using MTV, age, and stage, which outperforms IPI and enables individualized estimates of patient outcome.

Neural network dose prediction for rectal spacer stratification in dose-escalated prostate radiotherapy.

PURPOSE: To develop a knowledge-based decision-support system capable of stratifying patients for rectal spacer (RS) insertion based on neural network predicted rectal dose, reducing the need for time- and resource-intensive radiotherapy (RT) planning. METHODS: Forty-four patients treated for prostate cancer were enrolled into a clinical trial (NCT03238170). Dose-escalated prostate RT plans were manually created for 30 patients with simulated boost volumes using a conventional treatment planning system (TPS) and used to train a hierarchically dense 3D convolutional neural network to rapidly predict RT dose distributions. The network was used to predict rectal doses for 14 unseen test patients, with associated toxicity risks calculated according to published data. All metrics obtained using the network were compared to conventionally planned values. RESULTS: The neural network stratified patients with an accuracy of 100% based on optimal rectal dose-volume histogram constraints and 78.6% based on mandatory constraints. The network predicted dose-derived grade 2 rectal bleeding risk within 95% confidence limits of -1.9% to +1.7% of conventional risk estimates (risk range 3.5%-9.9%) and late grade 2 fecal incontinence risk within -0.8% to +1.5% (risk range 2.3%-5.7%). Prediction of high-resolution 3D dose distributions took 0.7 s. CONCLUSIONS: The feasibility of using a neural network to provide rapid decision support for RS insertion prior to RT has been demonstrated, and the potential for time and resource savings highlighted. Directly after target and healthy tissue delineation, the network is able to (i) risk stratify most patients with a high degree of accuracy to prioritize which patients would likely derive greatest benefit from RS insertion and (ii) identify patients close to the stratification threshold who would require conventional planning.