Dataset Information

The role of FDG-PET/CT in the evaluation of residual disease in paediatric non-Hodgkin lymphoma.

ABSTRACT: (18) F-labelled-fluorodeoxyglucose positron emission tomography (FDG-PET) findings are challenging to interpret for residual disease versus complete response in paediatric patients with non-Hodgkin lymphoma (NHL). A biopsy is often warranted to confirm the presence or absence of viable tumour if there is clinical or radiographic evidence of residual disease. In this study, we compared conventional imaging and FDG-PET/computerized tomography (CT) findings with biopsy results in 18 children with NHL. Our goal was to provide additional data to establish more reliable criteria for response evaluation. Residual disease was suspected after conventional imaging alone in eight patients, after FDG-PET/CT alone in three and after both modalities in seven patients. Biopsy confirmed the presence of viable tumour in two patients. Two additional patients experienced progressive disease or relapse. The sensitivity and negative predictive value of FDG-PET/CT using the London criteria to indicate residual tumour detectable by biopsy were 100%, but specificity was low (60%), as was the positive predictive value (25%). Thus, in this study, a negative FDG-PET/CT finding was a good indicator of complete remission. However, because false-positive FDG-PET/CT findings are common, biopsy and close monitoring are required for accurate determination of residual disease in individual patients.

SUBMITTER: Bhojwani D

PROVIDER: S-EPMC4351138 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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The role of FDG-PET/CT in the evaluation of residual disease in paediatric non-Hodgkin lymphoma.

Bhojwani Deepa D McCarville Mary B MB Choi John K JK Sawyer Jennifer J Metzger Monika L ML Inaba Hiroto H Davidoff Andrew M AM Gold Robert R Shulkin Barry L BL Sandlund John T JT

British journal of haematology 20141110 6

(18) F-labelled-fluorodeoxyglucose positron emission tomography (FDG-PET) findings are challenging to interpret for residual disease versus complete response in paediatric patients with non-Hodgkin lymphoma (NHL). A biopsy is often warranted to confirm the presence or absence of viable tumour if there is clinical or radiographic evidence of residual disease. In this study, we compared conventional imaging and FDG-PET/computerized tomography (CT) findings with biopsy results in 18 children with N ...[more]

PMID: 25382494

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Project description:ObjectivesTo assess the concordance of whole-body MRI (WB-MRI) and an FDG-PET/CT-based reference standard for the initial staging in children with Hodgkin lymphoma (HL) METHODS: Children with newly diagnosed HL were included in this prospective, multicentre, international study and underwent WB-MRI and FDG-PET/CT at staging. Two radiologists and a nuclear medicine physician independently evaluated all images. Discrepancies between WB-MRI and FDG-PET/CT were assessed by an expert panel. All FDG-PET/CT errors were corrected to derive the FDG-PET/CT-based reference standard. The expert panel corrected all reader errors in the WB-MRI DWI dataset to form the intrinsic MRI data. Inter-observer agreement for WB-MRI DWI was calculated using overall agreement, specific agreements and kappa statistics. Concordance for correct classification of all disease sites and disease stage between WB-MRI (without DWI, with DWI and intrinsic WB-MRI DWI) and the reference standard was calculated as primary outcome. Secondary outcomes included positive predictive value, negative predictive value and kappa statistics. Clustering within patients was accounted for using a mixed-effect logistic regression model with random intercepts and a multilevel kappa analysis.ResultsSixty-eight children were included. Inter-observer agreement between WB-MRI DWI readers was good for disease stage (κ = 0.74). WB-MRI DWI agreed with the FDG-PET/CT-based reference standard for determining disease stage in 96% of the patients versus 88% for WB-MRI without DWI. Agreement between WB-MRI DWI and the reference standard was excellent for both nodal (98%) and extra-nodal (100%) staging.ConclusionsWB-MRI DWI showed excellent agreement with the FDG-PET/CT-based reference standard. The addition of DWI to the WB-MRI protocol improved the staging agreement.Key points• This study showed excellent agreement between WB-MRI DWI and an FDG-PET/CT-based reference standard for staging paediatric HL. • Diffusion-weighted imaging is a useful addition to WB-MRI in staging paediatric HL. • Inter-observer agreement for WB-MRI DWI was good for both nodal and extra-nodal staging and determining disease stage.

Project description:PurposeFor pediatric lymphoma, quantitative FDG PET/CT imaging features such as metabolic tumor volume (MTV) are important for prognosis and risk stratification strategies. However, feature extraction is difficult and time-consuming in cases of high disease burden. The purpose of this study was to fully automate the measurement of PET imaging features in PET/CT images of pediatric lymphoma.Methods18F-FDG PET/CT baseline images of 100 pediatric Hodgkin lymphoma patients were retrospectively analyzed. Two nuclear medicine physicians identified and segmented FDG avid disease using PET thresholding methods. Both PET and CT images were used as inputs to a three-dimensional patch-based, multi-resolution pathway convolutional neural network architecture, DeepMedic. The model was trained to replicate physician segmentations using an ensemble of three networks trained with 5-fold cross-validation. The maximum SUV (SUVmax), MTV, total lesion glycolysis (TLG), surface-area-to-volume ratio (SA/MTV), and a measure of disease spread (Dmaxpatient) were extracted from the model output. Pearson's correlation coefficient and relative percent differences were calculated between automated and physician-extracted features.ResultsMedian Dice similarity coefficient of patient contours between automated and physician contours was 0.86 (IQR 0.78-0.91). Automated SUVmax values matched exactly the physician determined values in 81/100 cases, with Pearson's correlation coefficient (R) of 0.95. Automated MTV was strongly correlated with physician MTV (R = 0.88), though it was slightly underestimated with a median (IQR) relative difference of - 4.3% (- 10.0-5.7%). Agreement of TLG was excellent (R = 0.94), with median (IQR) relative difference of - 0.4% (- 5.2-7.0%). Median relative percent differences were 6.8% (R = 0.91; IQR 1.6-4.3%) for SA/MTV, and 4.5% (R = 0.51; IQR - 7.5-40.9%) for Dmaxpatient, which was the most difficult feature to quantify automatically.ConclusionsAn automated method using an ensemble of multi-resolution pathway 3D CNNs was able to quantify PET imaging features of lymphoma on baseline FDG PET/CT images with excellent agreement to reference physician PET segmentation. Automated methods with faster throughput for PET quantitation, such as MTV and TLG, show promise in more accessible clinical and research applications.

Project description:ObjectivesRelapse occurs in ~20% of patients with classical Hodgkin lymphoma (cHL) despite treatment adaption based on 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography response. The objective was to evaluate pre-treatment FDG PET/CT-derived machine learning (ML) models for predicting outcome in patients with cHL.MethodsAll cHL patients undergoing pre-treatment PET/CT at our institution between 2008 and 2018 were retrospectively identified. A 1.5 × mean liver standardised uptake value (SUV) and a fixed 4.0 SUV threshold were used to segment PET/CT data. Feature extraction was performed using PyRadiomics with ComBat harmonisation. Training (80%) and test (20%) cohorts stratified around 2-year event-free survival (EFS), age, sex, ethnicity and disease stage were defined. Seven ML models were trained and hyperparameters tuned using stratified 5-fold cross-validation. Area under the curve (AUC) from receiver operator characteristic analysis was used to assess performance.ResultsA total of 289 patients (153 males), median age 36 (range 16-88 years), were included. There was no significant difference between training (n = 231) and test cohorts (n = 58) (p value > 0.05). A ridge regression model using a 1.5 × mean liver SUV segmentation had the highest performance, with mean training, validation and test AUCs of 0.82 ± 0.002, 0.79 ± 0.01 and 0.81 ± 0.12. However, there was no significant difference between a logistic model derived from metabolic tumour volume and clinical features or the highest performing radiomic model.ConclusionsOutcome prediction using pre-treatment FDG PET/CT-derived ML models is feasible in cHL patients. Further work is needed to determine optimum predictive thresholds for clinical use.Key points• A fixed threshold segmentation method led to more robust radiomic features. • A radiomic-based model for predicting 2-year event-free survival in classical Hodgkin lymphoma patients is feasible. • A predictive model based on ridge regression was the best performing model on our dataset.

Project description:IntroductionAssessment 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 analysisThe 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 disseminationThe 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.

Dataset Information

The role of FDG-PET/CT in the evaluation of residual disease in paediatric non-Hodgkin lymphoma.

Publications

The role of FDG-PET/CT in the evaluation of residual disease in paediatric non-Hodgkin lymphoma.

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