Noise sensitivity of 89Zr-Immuno-PET radiomics based on count-reduced clinical images

PURPOSE: Low photon count in (89)Zr-Immuno-PET results in images with a low signal-to-noise ratio (SNR). Since PET radiomics are sensitive to noise, this study focuses on the impact of noise on radiomic features from (89)Zr-Immuno-PET clinical images. We hypothesise that (89)Zr-Immuno-PET derived radiomic features have: (1) noise-induced variability affecting their precision and (2) noise-induced bias affecting their accuracy. This study aims to identify those features that are not or only minimally affected by noise in terms of precision and accuracy. METHODS: Count-split (89)Zr-Immuno-PET patient scans from previous studies with three different (89)Zr-labelled monoclonal antibodies were used to extract radiomic features at 50% (S50p) and 25% (S25p) of their original counts. Tumour lesions were manually delineated on the original full-count (89)Zr-Immuno-PET scans. Noise-induced variability and bias were assessed using intraclass correlation coefficient (ICC) and similarity distance metric (SDM), respectively. Based on the ICC and SDM values, the radiomic features were categorised as having poor [0, 0.5), moderate [0.5, 0.75), good [0.75, 0.9), or excellent [0.9, 1] precision and accuracy. The number of features classified into these categories was compared between the S50p and S25p images using Fisher’s exact test. All p values < 0.01 were considered statistically significant. RESULTS: For S50p, a total of 92% and 90% features were classified as having good or excellent ICC and SDM respectively, while for S25p, these decreased to 81% and 31%. In total, 148 features (31%) showed robustness to noise with good or moderate ICC and SDM in both S50p and S25p. The number of features classified into the four ICC and SDM categories between S50p and S25p was significantly different statistically. CONCLUSION: Several radiomic features derived from low SNR (89)Zr-Immuno-PET images exhibit noise-induced variability and/or bias. However, 196 features (43%) that show minimal noise-induced variability and bias in S50p images have been identified. These features are less affected by noise and are, therefore, suitable candidates to be further studied as prognostic and predictive quantitative biomarkers in (89)Zr-Immuno-PET studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-022-00444-4

Baseline radiomics features and MYC rearrangement status predict progression in aggressive B-cell lymphoma

We investigated whether the outcome prediction of patients with aggressive B-cell lymphoma can be improved by combining clinical, molecular genotype, and radiomics features. MYC, BCL2, and BCL6 rearrangements were assessed using fluorescence in situ hybridization. Seventeen radiomics features were extracted from the baseline positron emission tomography–computed tomography of 323 patients, which included maximum standardized uptake value (SUV(max)), SUV(peak), SUV(mean), metabolic tumor volume (MTV), total lesion glycolysis, and 12 dissemination features pertaining to distance, differences in uptake and volume between lesions, respectively. Logistic regression with backward feature selection was used to predict progression after 2 years. The predictive value of (1) International Prognostic Index (IPI); (2) IPI plus MYC; (3) IPI, MYC, and MTV; (4) radiomics; and (5) MYC plus radiomics models were tested using the cross-validated area under the curve (CV-AUC) and positive predictive values (PPVs). IPI yielded a CV-AUC of 0.65 ± 0.07 with a PPV of 29.6%. The IPI plus MYC model yielded a CV-AUC of 0.68 ± 0.08. IPI, MYC, and MTV yielded a CV-AUC of 0.74 ± 0.08. The highest model performance of the radiomics model was observed for MTV combined with the maximum distance between the largest lesion and another lesion, the maximum difference in SUV(peak) between 2 lesions, and the sum of distances between all lesions, yielding an improved CV-AUC of 0.77 ± 0.07. The same radiomics features were retained when adding MYC (CV-AUC, 0.77 ± 0.07). PPV was highest for the MYC plus radiomics model (50.0%) and increased by 20% compared with the IPI (29.6%). Adding radiomics features improved model performance and PPV and can, therefore, aid in identifying poor prognosis patients

Optimal imaging time points considering accuracy and precision of Patlak linearization for 89Zr-immuno-PET: a simulation study

Purpose: Zirconium-89-immuno-positron emission tomography (89Zr-immuno-PET) has enabled visualization of zirconium-89 labelled monoclonal antibody (89Zr-mAb) uptake in organs and tumors in vivo. Patlak linearization of 89Zr-immuno-PET quantification data allows for separation of reversible and irreversible uptake, by combining multiple blood samples and PET images at different days. As one can obtain only a limited number of blood samples and scans per patient, choosing the optimal time points is important. Tissue activity concentration curves were simulated to evaluate the effect of imaging time points on Patlak results, considering different time points, input functions, noise levels and levels of reversible and irreversible uptake. Methods: Based on 89Zr-mAb input functions and reference values for reversible (VT) and irreversible (Ki) uptake from literature, multiple tissue activity curves were simulated. Three different 89Zr-mAb input functions, five time points between 24 and 192 h p.i., noise levels of 5, 10 and 15%, and three reference Ki and VT values were considered. Simulated Ki and VT were calculated (Patlak linearization) for a thousand repetitions. Accuracy and precision of Patlak linearization were evaluated by comparing simulated Ki and VT with reference values. Results: Simulations showed that Ki is always underestimated. Inclusion of time point 24 h p.i. reduced bias and variability in VT, and slightly reduced bias and variability in Ki, as compared to combinations of three later time points. After inclusion of 24 h p.i., minimal differences were found in bias and variability between different combinations of later imaging time points, despite different input functions, noise levels and reference values. Conclusion: Inclusion of a blood sample and PET scan at 24 h p.i. improves accuracy and precision of Patlak results for 89Zr-immuno-PET; the exact timing of the two later time points is not critical

Potential and pitfalls of Zr-89-immuno-PET to assess target status: Zr-89-trastuzumab as an example: 89Zr-trastuzumab as an example

Background: 89Zirconium-immuno-positron emission tomography (89Zr-immuno-PET) is used for assessment of target status to guide antibody-based therapy. We aim to determine the relation between antibody tumor uptake and target concentration to improve future study design and interpretation. Methods: The relation between tumor uptake and target concentration was predicted by mathematical modeling of 89Zr-labeled antibody disposition in the tumor. Literature values for trastuzumab kinetics were used to provide an example. Results: 89Zr-trastuzumab uptake initially increases with increasing target concentration, until it levels off to a constant value. This is determined by the total administered mass dose of trastuzumab. For a commonly used imaging dose of 50 mg 89Zr-trastuzumab, uptake can discriminate between immunohistochemistry score (IHC) 0 versus 1–2–3. Conclusion: The example for 89Zr-trastuzumab illustrates the potential to assess target expression. The pitfall of false-positive findings depends on the cut-off to define clinical target positivity (i.e., IHC 3) and the administered mass dose

Immuno-Positron Emission Tomography with Zirconium-89-Labeled Monoclonal Antibodies in Oncology: What Can We Learn from Initial Clinical Trials?

Selection of the right drug for the right patient is a promising approach to increase clinical benefit of targeted therapy with monoclonal antibodies (mAbs). Assessment of in vivo biodistribution and tumor targeting of mAbs to predict toxicity and efficacy is expected to guide individualized treatment and drug development. Molecular imaging with positron emission tomography (PET) using zirconium-89 (89Zr)-labeled monoclonal antibodies also known as 89Zr-immuno-PET, visualizes and quantifies uptake of radiolabeled mAbs. This technique provides a potential imaging biomarker to assess target expression, as well as tumor targeting of mAbs. In this review we summarize results from initial clinical trials with 89Zr-immuno-PET in oncology and discuss technical aspects of trial design. In clinical trials with 89Zr-immuno-PET two requirements should be met for each 89Zr-labeled mAb to realize its full potential. One requirement is that the biodistribution of the 89Zr-labeled mAb (imaging dose) reflects the biodistribution of the drug during treatment (therapeutic dose). Another requirement is that tumor uptake of 89Zr-mAb on PET is primarily driven by specific, antigen-mediated, tumor targeting. Initial trials have contributed toward the development of 89Zr-immuno-PET as an imaging biomarker by showing correlation between uptake of 89Zr-labeled mAbs on PET and target expression levels in biopsies. These results indicate that 89Zr-immuno-PET reflects specific, antigen-mediated binding. 89Zr-immuno-PET was shown to predict toxicity of RIT, but thus far results indicating that toxicity of mAbs or mAb-drug conjugate treatment can be predicted are lacking. So far, one study has shown that molecular imaging combined with early response assessment is able to predict response to treatment with the antibody-drug conjugate trastuzumab-emtansine, in patients with human epithelial growth factor-2 (HER2)-positive breast cancer. Future studies would benefit from a standardized criterion to define positive tumor uptake, possibly supported by quantitative analysis, and validated by linking imaging data with corresponding clinical outcome. Taken together, these results encourage further studies to develop 89Zr-immuno-PET as a predictive imaging biomarker to guide individualized treatment, as well as for potential application in drug development

Performance of ⁸⁹Zr-Labeled-Rituximab-PET as an Imaging Biomarker to Assess CD20 Targeting: A Pilot Study in Patients with Relapsed/Refractory Diffuse Large B Cell Lymphoma

<div><p>Purpose</p><p>Treatment of patients with diffuse large B cell lymphoma (DLBCL) includes rituximab, an anti-CD20 monoclonal antibody (mAb). Insufficient tumor targeting might cause therapy failure. Tumor uptake of ⁸⁹Zirconium (⁸⁹Zr)-mAb is a potential imaging biomarker for tumor targeting, since it depends on target antigen expression and accessibility. The aim of this pilot study was to describe the performance of ⁸⁹Zr-labeled-rituximab-PET to assess CD20 targeting in patients with relapsed/refractory DLBCL.</p><p>Methods</p><p>Six patients with biopsy-proven DLBCL were included. CD20 expression was assessed using immunohistochemistry (IHC). 74 MBq ⁸⁹Zr-rituximab (10 mg) was administered after the therapeutic dose of rituximab. Immuno-PET scans on day 0, 3 and 6 post injection (D0, D3 and D6 respectively) were visually assessed and quantified for tumor uptake.</p><p>Results</p><p>Tumor uptake of ⁸⁹Zr-rituximab and CD20 expression were concordant in 5 patients: for one patient, both were negative, for the other four patients visible tumor uptake was concordant with CD20-positive biopsies. Intense tumor uptake of ⁸⁹Zr-rituximab on PET (SUV_peak = 12.8) corresponded with uniformly positive CD20 expression on IHC in one patient. Moderate tumor uptake of ⁸⁹Zr-rituximab (range SUV_peak = 3.2–5.4) corresponded with positive CD20 expression on IHC in three patients. In one patient tumor uptake of ⁸⁹Zr-rituximab was observed (SUV_peak = 3.8), while the biopsy was CD20-negative.</p><p>Conclusions</p><p>This study suggests a positive correlation between tumor uptake of ⁸⁹Zr-rituximab and CD20 expression in tumor biopsies, but further studies are needed to confirm this. This result supports the potential of ⁸⁹Zr-rituximab-PET as an imaging biomarker for CD20 targeting. For clinical application of ⁸⁹Zr-rituximab-PET to guide individualized treatment, further studies are required to assess whether tumor targeting is related to clinical benefit of rituximab treatment in individual patients.</p></div

Quantitative tumor uptake measures of ⁸⁹Zr-rituximab in the biopsied tumor lesions.

<p>Quantitative tumor uptake measures of ⁸⁹Zr-rituximab in the biopsied tumor lesions.</p

Patient characteristics.

<p>Patient characteristics.</p

Example of tumor uptake on ⁸⁹Zr-rituximab-PET, concordant with CD20 expression in biopsy.

<p>Axial images, from left to right attenuation corrected PET, low dose CT and fused PET/CT image of patient 3. a) ⁸⁹Zr-rituximab-PET shows intense tumor uptake concordant with a CD20-positive biopsy (inguinal lymph node). b) Corresponding tumor location on ¹⁸F-FDG-PET.</p