Mitigating SUV uncertainties using total body PET imaging.

PURPOSE: Standardised uptake values (SUV) are commonly used to quantify 18F-FDG lesion uptake. However, SUVs may suffer from several uncertainties and errors. Long-axial field-of-view (LAFOV) PET/CT systems might enable image-based quality control (QC) by deriving 18F-FDG activity and weight from total body (TB) 18F-FDG PET images. In this study, we aimed to develop these image-based QC to reduce errors and mitigate SUV uncertainties. METHODS: Twenty-five out of 81 patient scans from a LAFOV PET/CT system were used to determine regression fits for deriving of image-derived activity and weight. Thereafter, the regression fits were applied to 56 independent 18F-FDG PET scans from the same scanner to determine if injected activity and weight could be obtained accurately from TB and half-body (HB) scans. Additionally, we studied the impact of image-based values on the precision of liver SUVmean and lesion SUVpeak. Finally, 20 scans were acquired from a short-axial field-of-view (SAFOV) PET/CT system to determine if the regression fits also applied to HB scans from a SAFOV system. RESULTS: Both TB and HB 18F-FDG activity and weight significantly predicted reported injected activity (r = 0.999; r = 0.984) and weight (r = 0.999; r = 0.987), respectively. After applying the regression fits, 18F-FDG activity and weight were accurately derived within 4.8% and 3.2% from TB scans and within 4.9% and 3.1% from HB, respectively. Image-derived values also mitigated liver and lesion SUV variability compared with reported values. Moreover, 18F-FDG activity and weight obtained from a SAFOV scanner were derived within 6.7% and 4.5%, respectively. CONCLUSION: 18F-FDG activity and weight can be derived accurately from TB and HB scans, and image-derived values improved SUV precision and corrected for lesion SUV errors. Therefore, image-derived values should be included as QC to generate a more reliable and reproducible quantitative uptake measurement.

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

INTRODUCTION: Although visual and quantitative assessments of [18F]FDG PET/CT studies typically rely on liver uptake value as a reference or normalisation factor, consensus or consistency in measuring [18F]FDG uptake is lacking. Therefore, we evaluate the variation of several liver standardised uptake value (SUV) measurements in lymphoma [18F]FDG PET/CT studies using different uptake metrics. METHODS: PET/CT scans from 34 lymphoma patients were used to calculate SUVmaxliver, SUVpeakliver and SUVmeanliver as a function of (1) volume-of-interest (VOI) size, (2) location, (3) imaging time point and (4) as a function of total metabolic tumour volume (MTV). The impact of reconstruction protocol on liver uptake is studied on 15 baseline lymphoma patient scans. The effect of noise on liver SUV was assessed using full and 25% count images of 15 lymphoma scans. RESULTS: Generally, SUVmaxliver and SUVpeakliver were 38% and 16% higher compared to SUVmeanliver. SUVmaxliver and SUVpeakliver increased up to 31% and 15% with VOI size while SUVmeanliver remained unchanged with the lowest variability for the largest VOI size. Liver uptake metrics were not affected by VOI location. Compared to baseline, liver uptake metrics were 15-18% and 9-18% higher at interim and EoT PET, respectively. SUVliver decreased with larger total MTVs. SUVmaxliver and SUVpeakliver were affected by reconstruction protocol up to 62%. SUVmax and SUVpeak moved 22% and 11% upward between full and 25% count images. CONCLUSION: SUVmeanliver was most robust against VOI size, location, reconstruction protocol and image noise level, and is thus the most reproducible metric for liver uptake. The commonly recommended 3 cm diameter spherical VOI-based SUVmeanliver values were only slightly more variable than those seen with larger VOI sizes and are sufficient for SUVmeanliver measurements in future studies. TRIAL REGISTRATION: EudraCT: 2006-005,174-42, 01-08-2008.

89Zr-immuno-PET using the anti-LAG-3 tracer [89Zr]Zr-BI 754111: demonstrating target specific binding in NSCLC and HNSCC.

PURPOSE: Although lymphocyte activation gene-3 (LAG-3) directed therapies demonstrate promising clinical anti-cancer activity, only a subset of patients seems to benefit and predictive biomarkers are lacking. Here, we explored the potential use of the anti-LAG-3 antibody tracer [89Zr]Zr-BI 754111 as a predictive imaging biomarker and investigated its target specific uptake as well as the correlation of its tumor uptake and the tumor immune infiltration. METHODS: Patients with head and neck (N = 2) or lung cancer (N = 4) were included in an imaging substudy of a phase 1 trial with BI 754091 (anti-PD-1) and BI 754111 (anti-LAG-3). After baseline tumor biopsy and [18F]FDG-PET, patients were given 240 mg of BI 754091, followed 8 days later by administration of [89Zr]Zr-BI 754111 (37 MBq, 4 mg). PET scans were performed 2 h, 96 h, and 144 h post-injection. To investigate target specificity, a second tracer administration was given two weeks later, this time with pre-administration of 40 (N = 3) or 600 mg (N = 3) unlabeled BI 754111, followed by PET scans at 96 h and 144 h post-injection. Tumor immune cell infiltration was assessed by immunohistochemistry and RNA sequencing. RESULTS: Tracer uptake in tumors was clearly visible at the 4-mg mass dose (tumor-to-plasma ratio 1.63 [IQR 0.37-2.89]) and could be saturated by increasing mass doses (44 mg: 0.67 [IQR 0.50-0.85]; 604 mg: 0.56 [IQR 0.42-0.75]), demonstrating target specificity. Tumor uptake correlated to immune cell-derived RNA signatures. CONCLUSIONS: [89Zr]Zr-BI-754111 PET imaging shows favorable technical and biological characteristics for developing a potential predictive imaging biomarker for LAG-3-directed therapies. TRIAL REGISTRATION: ClinicalTrials.gov , NCT03780725. Registered 19 December 2018.

[18F]Fluoride PET provides distinct information on disease activity in ankylosing spondylitis as compared to MRI and conventional radiography.

PURPOSE: To relate [18F]fluoride uptake on PET with abnormalities on magnetic resonance imaging (MRI) and conventional radiography (CR) in ankylosing spondylitis (AS) patients. METHODS: Ten clinically active AS patients (female 6/10, age 38 ± 11 years) were included, and both spine and SI-joints were examined. PET scans were dichotomously scored for enhanced [18F]fluoride uptake, MRI scans were scored for fatty lesions, erosions, ankylosis, and bone marrow edema (BME), and CR was scored for erosions, syndesmophytes, and ankylosis. The overlap of lesions across all modalities was evaluated through univariate and multivariate analyses using a generalized mixed model. RESULTS: In the spine, 69 lesions with enhanced [18F]fluoride uptake, 257 MRI lesions, and 88 CR lesions were observed. PET lesions were mostly located in costovertebral and facet joints, outside the field of view (FOV) of the MRI and CR. However, PET lesions inside the FOV of MRI and CR partially showed no abnormality on MRI and CR. In lesions with abnormalities on multiple modalities, both univariate and multivariate analysis showed that PET activity had the strongest association with BME on MRI and ankylosis on CR. In the SI joints, 15 lesions (75%) with PET uptake were found, with 87% showing abnormalities on MRI and CR. CONCLUSION: [18F]fluoride PET lesions are often found outside the scope of MRI and CR, and even in the same location show only partial overlap with abnormalities on MRI (especially BME) and CR (especially ankylosis). This suggests that [18F]fluoride PET partially visualizes aspects of AS separate from MRI and CR, providing novel information. CLINICAL TRIAL REGISTRATION: NL43223.029.13 registered at 02-05-2013.  https://www.toetsingonline.nl/to/ccmo_search.nsf/fABRpop?readform&unids=C1257BA2002CC066C1257B4E0049A65A.

18F-sodium fluoride PET-CT visualizes both axial and peripheral new bone formation in psoriatic arthritis patients.

PURPOSE: As bone formation is associated with psoriatic arthritis (PsA), positron emission tomography (PET) using a 18F-Fluoride tracer may enable sensitive detection of disease activity. Our primary aim was to determine the feasibility of whole-body 18F-sodium fluoride PET-CT in clinically active PsA patients to depict new bone formation (as a reflection of disease activity) at peripheral joints and entheses. Our secondary aim was to describe 18F-sodium fluoride findings in the axial skeleton. METHODS: Sixteen patients (female 10/16, age 50.6 ± 8.9 years) with PsA fulfilling CASPAR criteria or with a clinical diagnosis of PsA according to the treating rheumatologist and with ≥ 1 clinically active enthesitis site were included. Of each patient, a whole-body 18F-sodium fluoride PET-CT scan was performed. All scans were scored for PET-positive lesions at peripheral joints, enthesis sites and the spine. Clinical disease activity was assessed by swollen/tender joint count 44, enthesitis according to MASES and SPARCC scores. RESULTS: Out of 1088 evaluated joints, 109 joints showed PET enhancement, mainly in the interphalangeal and metatarsal joints of the feet (14/109, 12.9%) and the distal interphalangeal joints of the hands (14/109, 12.9%). PET positivity was found at 44/464 enthesis sites, mainly at the patella tendon insertion (11/44, 25%) and quadriceps tendon insertion (10/44, 22.7%). Of the PET-positive joints and enthesis sites, respectively 18.2% and 29.5% were clinically positive; 81.8% and 70.5% of the PET-positive joints and entheses respectively were clinically asymptomatic. In 11 patients, ≥ 1 axial PET-positive lesion was observed, mainly in the cervical spine. CONCLUSIONS: New molecular bone formation was observed on 18F-sodium fluoride PET-CT scans, in all domains in which PsA disease activity can be observed, with a substantial part showing no clinical symptoms. CLINICAL TRIAL REGISTRATION: EudraCT: 2017-004,850-40, registered on 13 December 2017.

18F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma.

PURPOSE: Accurate prognostic markers are urgently needed to identify diffuse large B-Cell lymphoma (DLBCL) patients at high risk of progression or relapse. Our purpose was to investigate the potential added value of baseline radiomics features to the international prognostic index (IPI) in predicting outcome after first-line treatment. METHODS: Three hundred seventeen newly diagnosed DLBCL patients were included. Lesions were delineated using a semi-automated segmentation method (standardized uptake value ≥ 4.0), and 490 radiomics features were extracted. We used logistic regression with backward feature selection to predict 2-year time to progression (TTP). The area under the curve (AUC) of the receiver operator characteristic curve was calculated to assess model performance. High-risk groups were defined based on prevalence of events; diagnostic performance was assessed using positive and negative predictive values. RESULTS: The IPI model yielded an AUC of 0.68. The optimal radiomics model comprised the natural logarithms of metabolic tumor volume (MTV) and of SUVpeak and the maximal distance between the largest lesion and any other lesion (Dmaxbulk, AUC 0.76). Combining radiomics and clinical features showed that a combination of tumor- (MTV, SUVpeak and Dmaxbulk) and patient-related parameters (WHO performance status and age > 60 years) performed best (AUC 0.79). Adding radiomics features to clinical predictors increased PPV with 15%, with more accurate selection of high-risk patients compared to the IPI model (progression at 2-year TTP, 44% vs 28%, respectively). CONCLUSION: Prediction models using baseline radiomics combined with currently used clinical predictors identify patients at risk of relapse at baseline and significantly improved model performance. TRIAL REGISTRATION NUMBER AND DATE: EudraCT: 2006-005,174-42, 01-08-2008.

Comparing lesion and feature selections to predict progression in newly diagnosed DLBCL patients with FDG PET/CT radiomics features.

PURPOSE: Biomarkers that can accurately predict outcome in DLBCL patients are urgently needed. Radiomics features extracted from baseline [18F]-FDG PET/CT scans have shown promising results. This study aims to investigate which lesion- and feature-selection approaches/methods resulted in the best prediction of progression after 2 years. METHODS: A total of 296 patients were included. 485 radiomics features (n = 5 conventional PET, n = 22 morphology, n = 50 intensity, n = 408 texture) were extracted for all individual lesions and at patient level, where all lesions were aggregated into one VOI. 18 features quantifying dissemination were extracted at patient level. Several lesion selection approaches were tested (largest or hottest lesion, patient level [all with/without dissemination], maximum or median of all lesions) and compared to the predictive value of our previously published model. Several data reduction methods were applied (principal component analysis, recursive feature elimination (RFE), factor analysis, and univariate selection). The predictive value of all models was tested using a fivefold cross-validation approach with 50 repeats with and without oversampling, yielding the mean cross-validated AUC (CV-AUC). Additionally, the relative importance of individual radiomics features was determined. RESULTS: Models with conventional PET and dissemination features showed the highest predictive value (CV-AUC: 0.72-0.75). Dissemination features had the highest relative importance in these models. No lesion selection approach showed significantly higher predictive value compared to our previous model. Oversampling combined with RFE resulted in highest CV-AUCs. CONCLUSION: Regardless of the applied lesion selection or feature selection approach and feature reduction methods, patient level conventional PET features and dissemination features have the highest predictive value. Trial registration number and date: EudraCT: 2006-005174-42, 01-08-2008.

Systematic Review: Targeted Molecular Imaging of Angiogenesis and Its Mediators in Rheumatoid Arthritis.

Extensive angiogenesis is a characteristic feature in the synovial tissue of rheumatoid arthritis (RA) from a very early stage of the disease onward and constitutes a crucial event for the development of the proliferative synovium. This process is markedly intensified in patients with prolonged disease duration, high disease activity, disease severity, and significant inflammatory cell infiltration. Angiogenesis is therefore an interesting target for the development of new therapeutic approaches as well as disease monitoring strategies in RA. To this end, nuclear imaging modalities represent valuable non-invasive tools that can selectively target molecular markers of angiogenesis and accurately and quantitatively track molecular changes in multiple joints simultaneously. This systematic review summarizes the imaging markers used for single photon emission computed tomography (SPECT) and/or positron emission tomography (PET) approaches, targeting pathways and mediators involved in synovial neo-angiogenesis in RA.

Multiparametric functional MRI and 18F-FDG-PET for survival prediction in patients with head and neck squamous cell carcinoma treated with (chemo)radiation.

OBJECTIVES: To assess (I) correlations between diffusion-weighted (DWI), intravoxel incoherent motion (IVIM), dynamic contrast-enhanced (DCE) MRI, and 18F-FDG-PET/CT imaging parameters capturing tumor characteristics and (II) their predictive value of locoregional recurrence-free survival (LRFS) and overall survival (OS) in patients with head and neck squamous cell carcinoma (HNSCC) treated with (chemo)radiotherapy. METHODS: Between 2014 and 2018, patients with histopathologically proven HNSCC, planned for curative (chemo) radiotherapy, were prospectively included. Pretreatment clinical, anatomical, and functional imaging parameters (obtained by DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT) were extracted for primary tumors (PT) and lymph node metastases. Correlations and differences between parameters were assessed. The predictive value of LRFS and OS was assessed, performing univariable, multivariable Cox and CoxBoost regression analyses. RESULTS: In total, 70 patients were included. Significant correlations between 18F-FDG-PET parameters and DWI-/DCE volume parameters were found (r > 0.442, p < 0.002). The combination of HPV (HR = 0.903), intoxications (HR = 1.065), PT ADCGTV (HR = 1.252), Ktrans (HR = 1.223), and Ve (HR = 1.215) was predictive for LRFS (C-index = 0.546; p = 0.023). N-stage (HR = 1.058), HPV positivity (HR = 0.886), hypopharyngeal tumor location (HR = 1.111), ADCGTV (HR = 1.102), ADCmean (HR = 1.137), D* (HR = 0.862), Ktrans (HR = 1.106), Ve (HR = 1.195), SUVmax (HR = 1.094), and TLG (HR = 1.433) were predictive for OS (C-index = 0.664; p = 0.046). CONCLUSIONS: Functional imaging parameters, performing DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT, yielded complementary value in capturing tumor characteristics. More specific, intoxications, HPV-negative status, large tumor volume-related parameters, high permeability (Ktrans), and high extravascular extracellular space (Ve) parameters were predictive for adverse locoregional recurrence-free survival and adverse overall survival. Low cellularity (high ADC) and high metabolism (high SUV) were additionally predictive for decreased overall survival. These different predictive factors added to estimated locoregional and overall survival. KEY POINTS: • Parameters of DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT were able to capture complementary tumor characteristics. • Multivariable analysis revealed that intoxications, HPV negativity, large tumor volume and high vascular permeability (Ktrans), and extravascular extracellular space (Ve) were complementary predictive for locoregional recurrence. • In addition to predictive parameters for locoregional recurrence, also high cellularity (low ADC) and high metabolism (high SUV) were complementary predictive for overall survival.

Ultra-low foetal radiation exposure in 18F-FDG PET/CT imaging with a long axial field-of-view PET/CT system.

PURPOSE: Long axial field-of-view (LAFOV) PET/CT systems enable PET/CT scans with reduced injected activities because of improved sensitivity. With this study, we aimed to examine the foetal radiation dose from an 18F-FDG PET/CT scan on a LAFOV PET/CT system with reduced injected activity. METHODS: Two pregnant women were retrospectively included and received an 18F-FDG PET/CT scan on a LAFOV PET/CT system with an intravenous bolus injection of 0.30 MBq/kg. Foetal radiation exposure from the PET was estimated using dose conversion factors from three published papers. Radiation exposure from the CT scans was estimated using CT-Expo. RESULTS: Foetal radiation dose from the PET scan ranged between 0.11 and 0.44 mGy. Foetal radiation exposure from the CT scan ranged between < 0.10 - 0.90 mGy depending if the foetus was included in the field-of-view. CONCLUSION: Foetal radiation dose could be reduced to < 1.5 mGy when scanning pregnant patients on a LAFOV PET/CT system. The radiation dose to the foetus was reduced significantly in our study due to the increased sensitivity of the LAFOV PET/CT system.

Validation of image-derived input function using a long axial field of view PET/CT scanner for two different tracers.

BACKGROUND: Accurate image-derived input function (IDIF) from highly sensitive large axial field of view (LAFOV) PET/CT scanners could avoid the need of invasive blood sampling for kinetic modelling. The aim is to validate the use of IDIF for two kinds of tracers, 3 different IDIF locations and 9 different reconstruction settings. METHODS: Eight [18F]FDG and 10 [18F]DPA-714 scans were acquired respectively during 70 and 60 min on the Vision Quadra PET/CT system. PET images were reconstructed using various reconstruction settings. IDIFs were taken from ascending aorta (AA), descending aorta (DA), and left ventricular cavity (LV). The calibration factor (CF) extracted from the comparison between the IDIFs and the manual blood samples as reference was used for IDIFs accuracy and precision assessment. To illustrate the effect of various calibrated-IDIFs on Patlak linearization for [18F]FDG and Logan linearization for [18F]DPA-714, the same target time-activity curves were applied for each calibrated-IDIF. RESULTS: For [18F]FDG, the accuracy and precision of the IDIFs were high (mean CF ≥ 0.82, SD ≤ 0.06). Compared to the striatum influx (Ki) extracted using calibrated AA IDIF with the updated European Association of Nuclear Medicine Research Ltd. standard reconstruction (EARL2), Ki mean differences were < 2% using the other calibrated IDIFs. For [18F]DPA714, high accuracy of the IDIFs was observed (mean CF ≥ 0.86) except using absolute scatter correction, DA and LV (respectively mean CF = 0.68, 0.47 and 0.44). However, the precision of the AA IDIFs was low (SD ≥ 0.10). Compared to the distribution volume (VT) in a frontal region obtained using calibrated continuous arterial sampler input function as reference, VT mean differences were small using calibrated AA IDIFs (for example VT mean difference = -5.3% using EARL2), but higher using calibrated DA and LV IDIFs (respectively + 12.5% and + 19.1%). CONCLUSIONS: For [18F]FDG, IDIF do not need calibration against manual blood samples. For [18F]DPA-714, AA IDIF can replace continuous arterial sampling for simplified kinetic quantification but only with calibration against arterial blood samples. The accuracy and precision of IDIF from LAFOV PET/CT system depend on tracer, reconstruction settings and IDIF VOI locations, warranting careful optimization.

Exploring the predictive potential of programmed death ligand 1 expression in healthy organs and lymph nodes as measured by 18F-BMS986-192 PET: pooled analysis of data from four solid tumor types.

INTRODUCTION: Immune checkpoint inhibitors (ICIs) can elicit anticancer immune responses, but predictive biomarkers are needed. We measured programmed death ligand 1 (PD-L1) expression in organs and lymph nodes using 18F-BMS-986192 positron emission tomography (PET)-imaging and looked for correlations with response and immune-related adverse events. METHODS: Four 18F-BMS-986192 PET studies in patients with melanoma, lung, pancreatic and oral cancer, receiving ICI treatment, were combined. Imaging data (organ standardized uptake value (SUV)mean, lymph node SUVmax) and clinical data (response to treatment and incidence of immune-related adverse events) were extracted. RESULTS: Baseline PD-L1 uptake in the spleen was on average higher in non-responding patients than in responders (spleen SUVmean 16.1±4.4 vs 12.5±3.4, p=0.02). This effect was strongest in lung cancer, and not observed in oral cancer. In the oral cancer cohort, benign tumor-draining lymph nodes (TDLNs) had higher PD-L1 uptake (SUVmax 3.3 IQR 2.5-3.9) compared with non-TDLNs (SUVmax 1.8, IQR 1.4-2.8 p=0.04). Furthermore, in the same cohort non-responders showed an increase in PD-L1 uptake in benign TDLNs on-treatment with ICIs (+15%), while for responders the PD-L1 uptake decreased (-11%). PD-L1 uptake did not predict immune-related adverse events, though elevated thyroid uptake on-treatment correlated with pre-existing thyroid disease or toxicity. CONCLUSION: PD-L1 PET uptake in the spleen is a potential negative predictor of response to ICIs. On-treatment with ICIs, PD-L1 uptake in benign TDLNs increases in non-responders, while it decreases in responders, potentially indicating a mechanism for resistance to ICIs in patients with oral cancer.

How to obtain the image-derived blood concentration from 89Zr-immuno-PET scans.

BACKGROUND: PET scans using zirconium-89 labelled monoclonal antibodies (89Zr-mAbs), known as 89Zr-immuno-PET, are made to measure uptake in tumour and organ tissue. Uptake is related to the supply of 89Zr-mAbs in the blood. Measuring activity concentrations in blood, however, requires invasive blood sampling. This study aims to identify the best delineation strategy to obtain the image-derived blood concentration (IDBC) from 89Zr-immuno-PET scans. METHODS: PET imaging and blood sampling of two 89Zr-mAbs were included, 89Zr-cetuximab and 89Zr-durvalumab. For seven patients receiving 89Zr-cetuximab, PET scans on 1-2 h, 2 and 6 days post-injection (p.i.) were analysed. Five patients received three injections of 89Zr-durvalumab. The scanning protocol for the first two injections consisted of PET scanning on 2, 5 and 7 days p.i. and for the third injection only on 7 days p.i. Blood samples were drawn with every PET scan and the sample-derived blood concentration (SDBC) was used as gold standard for the IDBC. According to an in-house developed standard operating procedure, the aortic arch, ascending aorta, descending aorta and left ventricle were delineated. Bland-Altman analyses were performed to assess the bias (mean difference) and variability (1.96 times the standard deviation of the differences) between IDBC and SDBC. RESULTS: Overall, the activity concentration obtained from the IDBC was lower than from the SDBC. When comparing IDBC with SDBC, variability was smallest for the ascending aorta (20.3% and 17.0% for 89Zr-cetuximab and 89Zr-durvalumab, respectively). Variability for the other regions ranged between 17.9 and 30.8%. Bias for the ascending aorta was - 10.9% and - 11.4% for 89Zr-cetuximab and 89Zr-durvalumab, respectively. CONCLUSIONS: Image-derived blood concentrations should be obtained from delineating the ascending aorta in 89Zr-immuno-PET scans, as this results in the lowest variability with respect to sample-derived blood concentrations.

First exploration of the on-treatment changes in tumor and organ uptake of a radiolabeled anti PD-L1 antibody during chemoradiotherapy in patients with non-small cell lung cancer using whole body PET.

BACKGROUND: In patients with locally advanced unresectable non-small cell lung cancer (NSCLC), durvalumab, an anti-programmed cell death ligand-1 (PD-L1) antibody, has shown improved overall survival when used as consolidation therapy following concurrent chemoradiotherapy (CRT). However, it is unclear whether CRT itself upregulates PD-L1 expression. Therefore, this study aimed to explore the changes in the uptake of the anti PD-L1 antibody [89Zr]Zr-durvalumab in tumors and healthy organs during CRT in patients with NSCLC. METHODS: Patients with NSCLC scheduled to undergo CRT were scanned 7±1 days after administration of 37±1 MBq [89Zr]Zr-durvalumab at baseline, 1-week on-treatment and 1 week after finishing 6 weeks of CRT. First, [89Zr]Zr-durvalumab uptake was visually assessed in a low dose cohort with a mass dose of 2 mg durvalumab (0.13% of therapeutic dose) and subsequently, quantification was done in a high dose cohort with a mass dose of 22.5 mg durvalumab (1.5% of therapeutic dose). Tracer pharmacokinetics between injections were compared using venous blood samples drawn in the 22.5 mg cohort. Visual assessment included suspected lesion detectability. Positron emission tomography (PET) uptake in tumoral and healthy tissues was quantified using tumor to plasma ratio (TPR) and organ to plasma ratio, respectively. RESULTS: In the 2 mg dose cohort, 88% of the 17 identified tumor lesions were positive at baseline, compared with 69% (9/13) for the 22.5 mg cohort. Although the absolute plasma concentrations between patients varied, the intrapatient variability was low. The ten quantitatively assessed lesions in the 22.5 mg cohort had a median TPR at baseline of 1.3 (IQR 0.7-1.5), on-treatment of 1.0 (IQR 0.7-1.4) and at the end of treatment of 0.7 (IQR 0.6-0.7). On-treatment, an increased uptake in bone marrow was seen in three out of five patients together with a decreased uptake in the spleen in four out of five patients. CONCLUSIONS: This study successfully imaged patients with NSCLC with [89Zr]Zr-durvalumab PET before and during CRT. Our data did not show any increase in [89Zr]Zr-durvalumab uptake in the tumor 1-week on-treatment and at the end of treatment. The changes observed in bone marrow and spleen may be due to an CRT-induced effect on immune cells. TRIAL REGISTRATION NUMBER: EudraCT number: 2019-004284-51.

Non-specific irreversible 89Zr-mAb uptake in tumours: evidence from biopsy-proven target-negative tumours using 89Zr-immuno-PET.

BACKGROUND: Distribution of mAbs into tumour tissue may occur via different processes contributing differently to the 89Zr-mAb uptake on PET. Target-specific binding in tumours is of main interest; however, non-specific irreversible uptake may also be present, which influences quantification. The aim was to investigate the presence of non-specific irreversible uptake in tumour tissue using Patlak linearization on 89Zr-immuno-PET data of biopsy-proven target-negative tumours. Data of two studies, including target status obtained from biopsies, were retrospectively analysed, and Patlak linearization provided the net rate of irreversible uptake (Ki). RESULTS: Two tumours were classified as CD20-negative and two as CD20-positive. Four tumours were classified as CEA-negative and nine as CEA-positive. Ki values of CD20-negative (0.43 µL/g/h and 0.92 µL/g/h) and CEA-negative tumours (mdn = 1.97 µL/g/h, interquartile range (IQR) = 1.50-2.39) were higher than zero. Median Ki values of target-negative tumours were lower than CD20-positive (1.87 µL/g/h and 1.90 µL/g/h) and CEA-positive tumours (mdn = 2.77 µL/g/h, IQR = 2.11-3.65). CONCLUSION: Biopsy-proven target-negative tumours showed irreversible uptake of 89Zr-mAbs measured in vivo using 89Zr-immuno-PET data, which suggests the presence of non-specific irreversible uptake in tumours. Consequently, for 89Zr-immuno-PET, even if the target is absent, a tumour-to-plasma ratio always increases over time.

Explainable artificial intelligence (XAI) in radiology and nuclear medicine: a literature review.

Rational: Deep learning (DL) has demonstrated a remarkable performance in diagnostic imaging for various diseases and modalities and therefore has a high potential to be used as a clinical tool. However, current practice shows low deployment of these algorithms in clinical practice, because DL algorithms lack transparency and trust due to their underlying black-box mechanism. For successful employment, explainable artificial intelligence (XAI) could be introduced to close the gap between the medical professionals and the DL algorithms. In this literature review, XAI methods available for magnetic resonance (MR), computed tomography (CT), and positron emission tomography (PET) imaging are discussed and future suggestions are made. Methods: PubMed, Embase.com and Clarivate Analytics/Web of Science Core Collection were screened. Articles were considered eligible for inclusion if XAI was used (and well described) to describe the behavior of a DL model used in MR, CT and PET imaging. Results: A total of 75 articles were included of which 54 and 17 articles described post and ad hoc XAI methods, respectively, and 4 articles described both XAI methods. Major variations in performance is seen between the methods. Overall, post hoc XAI lacks the ability to provide class-discriminative and target-specific explanation. Ad hoc XAI seems to tackle this because of its intrinsic ability to explain. However, quality control of the XAI methods is rarely applied and therefore systematic comparison between the methods is difficult. Conclusion: There is currently no clear consensus on how XAI should be deployed in order to close the gap between medical professionals and DL algorithms for clinical implementation. We advocate for systematic technical and clinical quality assessment of XAI methods. Also, to ensure end-to-end unbiased and safe integration of XAI in clinical workflow, (anatomical) data minimization and quality control methods should be included.

Characterizing the Bone Marrow Environment in Advanced-Stage Myelofibrosis during Ruxolitinib Treatment Using PET/CT and MRI: A Pilot Study.

Current diagnostic criteria for myelofibrosis are largely based on bone marrow (BM) biopsy results. However, these have several limitations, including sampling errors. Explorative studies have indicated that imaging might form an alternative for the evaluation of disease activity, but the heterogeneity in BM abnormalities complicates the choice for the optimal technique. In our prospective diagnostic pilot study, we aimed to visualize all BM abnormalities in myelofibrosis before and during ruxolitinib treatment using both PET/CT and MRI. A random sample of patients was scheduled for examinations at baseline and after 6 and 18 months of treatment, including clinical and laboratory examinations, BM biopsies, MRI (T1-weighted, Dixon, dynamic contrast-enhanced (DCE)) and PET/CT ([15O]water, [18F]NaF)). At baseline, all patients showed low BM fat content (indicated by T1-weighted MRI and Dixon), increased BM blood flow (as measured by [15O]water PET/CT), and increased osteoblastic activity (reflected by increased skeletal [18F]NaF uptake). One patient died after the baseline evaluation. In the others, BM fat content increased to various degrees during treatment. Normalization of BM blood flow (as reflected by [15O]water PET/CT and DCE-MRI) occurred in one patient, who also showed the fastest clinical response. Vertebral [18F]NaF uptake remained stable in all patients. In evaluable cases, histopathological parameters were not accurately reflected by imaging results. A case of sampling error was suspected. We conclude that imaging results can provide information on functional processes and disease distribution throughout the BM. Differences in early treatment responses were especially reflected by T1-weighted MRI. Limitations in the gold standard hampered the evaluation of diagnostic accuracy.

Sensitivity of an AI method for [18F]FDG PET/CT outcome prediction of diffuse large B-cell lymphoma patients to image reconstruction protocols.

BACKGROUND: Convolutional neural networks (CNNs), applied to baseline [18F]-FDG PET/CT maximum intensity projections (MIPs), show potential for treatment outcome prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study is to investigate the robustness of CNN predictions to different image reconstruction protocols. Baseline [18F]FDG PET/CT scans were collected from 20 DLBCL patients. EARL1, EARL2 and high-resolution (HR) protocols were applied per scan, generating three images with different image qualities. Image-based transformation was applied by blurring EARL2 and HR images to generate EARL1 compliant images using a Gaussian filter of 5 and 7 mm, respectively. MIPs were generated for each of the reconstructions, before and after image transformation. An in-house developed CNN predicted the probability of tumor progression within 2 years for each MIP. The difference in probabilities per patient was then calculated between both EARL2 and HR with respect to EARL1 (delta probabilities or ΔP). We compared these to the probabilities obtained after aligning the data with ComBat using the difference in median and interquartile range (IQR). RESULTS: CNN probabilities were found to be sensitive to different reconstruction protocols (EARL2 ΔP: median = 0.09, interquartile range (IQR) = [0.06, 0.10] and HR ΔP: median = 0.1, IQR = [0.08, 0.16]). Moreover, higher resolution images (EARL2 and HR) led to higher probability values. After image-based and ComBat transformation, an improved agreement of CNN probabilities among reconstructions was found for all patients. This agreement was slightly better after image-based transformation (transformed EARL2 ΔP: median = 0.022, IQR = [0.01, 0.02] and transformed HR ΔP: median = 0.029, IQR = [0.01, 0.03]). CONCLUSION: Our CNN-based outcome predictions are affected by the applied reconstruction protocols, yet in a predictable manner. Image-based harmonization is a suitable approach to harmonize CNN predictions across image reconstruction protocols.

Prognostic model using 18F-FDG PET radiomics predicts progression-free survival in relapsed/refractory Hodgkin lymphoma.

Investigating prognostic factors in patients with relapsed or primary refractory classical Hodgkin lymphoma (R/R cHL) is essential to optimize risk-adapted treatment strategies. We built a prognostic model using baseline quantitative 18F-fluorodeoxyglucose positron emission tomography (PET) radiomics features and clinical characteristics to predict the progression-free survival (PFS) among patients with R/R cHL treated with salvage chemotherapy followed by autologous stem cell transplantation. Metabolic tumor volume and several novel radiomics dissemination features, representing interlesional differences in distance, volume, and standard uptake value, were extracted from the baseline PET. Machine learning using backward selection and logistic regression were applied to develop and train the model on a total of 113 patients from 2 clinical trials. The model was validated on an independent external cohort of 69 patients. In addition, we validated 4 different PET segmentation methods to calculate radiomics features. We identified a subset of patients at high risk for progression with significant inferior 3-year PFS outcomes of 38.1% vs 88.4% for patients in the low-risk group in the training cohort (P < .001) and 38.5% vs 75.0% in the validation cohort (P = .015), respectively. The overall survival was also significantly better in the low-risk group (P = .022 and P < .001). We provide a formula to calculate a risk score for individual patients based on the model. In conclusion, we developed a prognostic model for PFS combining radiomics and clinical features in a large cohort of patients with R/R cHL. This model calculates a PET-based risk profile and can be applied to develop risk-stratified treatment strategies for patients with R/R cHL. These trials were registered at www.clinicaltrials.gov as #NCT02280993, #NCT00255723, and #NCT01508312.