PET/CT radiomics for prediction of hyperprogression in metastatic melanoma patients treated with immune checkpoint inhibitors

Purpose

This study evaluated pretreatment 2[18F]fluoro-2-deoxy-D-glucose (FDG)-PET/CT-based radiomic signatures for prediction of hyperprogression in metastatic melanoma patients treated with immune checkpoint inhibition (ICI).

Material and method

Fifty-six consecutive metastatic melanoma patients treated with ICI and available imaging were included in the study and 330 metastatic lesions were individually, fully segmented on pre-treatment CT and FDG-PET imaging. Lesion hyperprogression (HPL) was defined as lesion progression according to RECIST 1.1 and doubling of tumor growth rate. Patient hyperprogression (PD-HPD) was defined as progressive disease (PD) according to RECIST 1.1 and presence of at least one HPL. Patient survival was evaluated with Kaplan-Meier curves. Mortality risk of PD-HPD status was assessed by estimation of hazard ratio (HR). Furthermore, we assessed with Fisher test and Mann-Whitney U test if demographic or treatment parameters were different between PD-HPD and the remaining patients. Pre-treatment PET/CT-based radiomic signatures were used to build models predicting HPL at three months after start of treatment. The models were internally validated with nested cross-validation. The performance metric was the area under receiver operating characteristic curve (AUC).

Results

PD-HPD patients constituted 57.1% of all PD patients. PD-HPD was negatively related to patient overall survival with HR=8.52 (95%CI 3.47-20.94). Sixty-nine lesions (20.9%) were identified as progressing at 3 months. Twenty-nine of these lesions were classified as hyperprogressive, thereby showing a HPL rate of 8.8%. CT-based, PET-based, and PET/CT-based models predicting HPL at three months after the start of treatment achieved testing AUC of 0.703 +/- 0.054, 0.516 +/- 0.061, and 0.704 +/- 0.070, respectively. The best performing models relied mostly on CT-based histogram features.

Conclusions

FDG-PET/CT-based radiomic signatures yield potential for pretreatment prediction of lesion hyperprogression, which may contribute to reducing the risk of delayed treatment adaptation in metastatic melanoma patients treated with ICI.

NTCP modelling for high-grade temporal radionecrosis in a large cohort of patients receiving pencil beam scanning proton therapy for skull base and head and neck tumors

PURPOSE/OBJECTIVES

To develop a normal tissue complication probability (NTCP) model including clinical and dosimetric parameters for high-grade temporal lobe radionecroses (TRN) after pencil beam scanning (PBS) proton therapy (PT).

MATERIALS/METHODS

Data of 299 patients with skull base and Head and Neck tumors treated with PBS PT with a total dose of ≥60 Gy_RBE from 05/2004-11/2018 were included. Patients with a ≥ grade (G) 2 TRN (CTCAE v5.0 criteria) were considered as having a high-grade TRN. Nine clinical and 27 dosimetric parameters were considered for structure-wise modelling. After elimination of strongly cross-correlated variables, logistic regression models were generated using penalized LASSO regression. Bootstrapping was performed to assess parameter selection robustness. Model performance was evaluated via cross-correlation by assessing the area under the curve of receiver operating characteristic curves (AUC-ROC) and calibration with a Hosmer-Lemeshow test statistic.

RESULTS

After a median radiological follow-up of 51.5 months (range, 4-190), 27 (9%) patients developed a ≥ G2 TRN. Eleven patients had bitemporal necrosis, resulting in 38 events in 598 temporal lobes for structure-wise analysis. During Bootstrapping analysis, the highest selection frequency was found for prescription dose (PD), followed by Age, V_40Gy[%], Hypertension (HBP) and D_1cc[Gy]. During cross validation Age*PD* D_1cc[Gy]*HBP was superior in all described test statistics. Full cohort structure wise and patient wise models were built with a maximum AUC-ROC of 0.79 (structure-wise) and 0.76 (patient-wise).

CONCLUSION

While developing a logistic regression NTCP model to predict ≥ G2 TRN, the best fit was found for the model containing Age, PD, D_1cc[Gy] and HBP as risk factors. External validation will be the next step to improve generalizability and potential introduction into clinical routine.

Modelling the immunosuppressive effect of liver SBRT by simulating the dose to circulating lymphocytes: an in-silico planning study

Background

Tumor immune-evasion and associated failure of immunotherapy can potentially be overcome by radiotherapy, which however also has detrimental effects on tumor-infiltrating and circulating lymphocytes (CL). We therefore established a model to simulate the radiation-dose delivered to CL.

Methods

A MATLAB-model was established to quantify the CL-dose during SBRT of liver metastases by considering the factors: hepatic blood-flow, −velocity and transition-time of individual hepatic segments, as well as probability-based recirculation. The effects of intra-hepatic tumor-location and size, fractionation and treatment planning parameters (VMAT, 3DCRT, photon-energy, dose-rate and beam-on-time) were analyzed. A threshold dose ≥0.5Gy was considered inactivating CL and CL0.5 (%) is the proportion of inactivated CL.

Results

Mean liver dose was mostly influenced by treatment-modality, whereas CL0.5 was mostly influenced by beam-on-time. 3DCRT and VMAT (10MV-FFF) resulted in lowest CL0.5 values of 16 and 19%. Metastasis location influenced CL0.5, with a mean of 19% for both apical and basal and 31% for the central location. PTV-volume significantly increased CL0.5 from 27 to 67% (10MV-FFF) and from 31 to 98% (6MV-FFF) for PTV-volumes ranging from 14cm³ to 268cm³.

Conclusion

A simulation-model was established, quantifying the strong effects of treatment-technique, tumor-location and tumor-volume on dose to CL with potential implications for immune-optimized treatment-planning in the future.

Electronic supplementary material

The online version of this article (doi: 10.1186/s13014-018-0952-y) contains supplementary material, which is available to authorized users.

Sampling the Mouse Hippocampal Dentate Gyrus

Sampling is a critical step in procedures that generate quantitative morphological data in the neurosciences. Samples need to be representative to allow statistical evaluations, and samples need to deliver a precision that makes statistical evaluations not only possible but also meaningful. Sampling generated variability should, e.g., not be able to hide significant group differences from statistical detection if they are present. Estimators of the coefficient of error (CE) have been developed to provide tentative answers to the question if sampling has been “good enough” to provide meaningful statistical outcomes. We tested the performance of the commonly used Gundersen-Jensen CE estimator, using the layers of the mouse hippocampal dentate gyrus as an example (molecular layer, granule cell layer and hilus). We found that this estimator provided useful estimates of the precision that can be expected from samples of different sizes. For all layers, we found that a smoothness factor (m) of 0 generally provided better estimates than an m of 1. Only for the combined layers, i.e., the entire dentate gyrus, better CE estimates could be obtained using an m of 1. The orientation of the sections impacted on CE sizes. Frontal (coronal) sections are typically most efficient by providing the smallest CEs for a given amount of work. Applying the estimator to 3D-reconstructed layers and using very intense sampling, we observed CE size plots with m = 0 to m = 1 transitions that should also be expected but are not often observed in real section series. The data we present also allows the reader to approximate the sampling intervals in frontal, horizontal or sagittal sections that provide CEs of specified sizes for the layers of the mouse dentate gyrus.

[Significance of x-ray diagnosis in the control of calcitonin therapy of Paget's disease: case report]

5-years survey in a case of solitary Paget's disease of the right tibial bone. x-ray controls at 6 month intervals allow quantification of Calcitonin dose and document an excellent result of the therapy.