Comparison of novel multi-level Otsu (MO-PET) and conventional PET segmentation methods for measuring FDG metabolic tumor volume in patients with soft tissue sarcoma

Accuracy of gross tumour volume delineation with [68Ga]-PSMA-PET compared to histopathology for high-risk prostate cancer

BACKGROUND

The delineation of intraprostatic lesions is vital for correct delivery of focal radiotherapy boost in patients with prostate cancer (PC). Errors in the delineation could translate into reduced tumour control and potentially increase the side effects. The purpose of this study is to compare PET-based delineation methods with histopathology.

MATERIALS AND METHODS

The study population consisted of 15 patients with confirmed high-risk PC intended for prostatectomy. [68Ga]-PSMA-PET/MR was performed prior to surgery. Prostate lesions identified in histopathology were transferred to the in vivo [68Ga]-PSMA-PET/MR coordinate system. Four radiation oncologists manually delineated intraprostatic lesions based on PET data. Various semi-automatic segmentation methods were employed, including absolute and relative thresholds, adaptive threshold, and multi-level Otsu threshold.

RESULTS

The gross tumour volumes (GTVs) delineated by the oncologists showed a moderate level of interobserver agreement with Dice similarity coefficient (DSC) of 0.68. In comparison with histopathology, manual delineations exhibited the highest median DSC and the lowest false discovery rate (FDR) among all approaches. Among semi-automatic approaches, GTVs generated using standardized uptake value (SUV) thresholds above 4 (SUV > 4) demonstrated the highest median DSC (0.41), with 0.51 median lesion coverage ratio, FDR of 0.66 and the 95th percentile of the Hausdorff distance (HD95%) of 8.22 mm.

INTERPRETATION

Manual delineations showed a moderate level of interobserver agreement. Compared to histopathology, manual delineations and SUV > 4 exhibited the highest DSC and the lowest HD95% values. The methods that resulted in a high lesion coverage were associated with a large overestimation of the size of the lesions.

Clinical Perspectives for 18F-FDG PET Imaging in Pediatric Oncology: Μetabolic Tumor Volume and Radiomics

Pediatric cancer, although rare, requires the most optimized treatment approach to obtain high survival rates and minimize serious long-term side effects in early adulthood. 18F-FDG PET/CT is most helpful and widely used in staging, recurrence detection, and response assessment in pediatric oncology. The well-known 18F-FDG PET metabolic indices of metabolic tumor volume (MTV) and tumor lesion glycolysis (TLG) have already revealed an independent significant prognostic value for survival in oncologic patients, although the corresponding cut-off values remain study-dependent and not validated for use in clinical practice. Advanced tumor “radiomic” analysis sheds new light into these indices. Numerous patterns of texture 18F-FDG uptake features can be extracted from segmented PET tumor images due to new powerful computational systems supporting complex “deep learning” algorithms. This high number of “quantitative” tumor imaging data, although not decrypted in their majority and once standardized for the different imaging systems and segmentation methods, could be used for the development of new “clinical” models for specific cancer types and, more interestingly, for specific age groups. In addition, data from novel techniques of tumor genome analysis could reveal new genes as biomarkers for prognosis and/or targeted therapies in childhood malignancies. Therefore, this ever-growing information of “radiogenomics”, in which the underlying tumor “genetic profile” could be expressed in the tumor-imaging signature of “radiomics”, possibly represents the next model for precision medicine in pediatric cancer management. This paper reviews 18F-FDG PET image segmentation methods as applied to pediatric sarcomas and lymphomas and summarizes reported findings on the values of metabolic and radiomic features in the assessment of these pediatric tumors.

Multi-level otsu method to define metabolic tumor volume in positron emission tomography

This study was to validate reliability and clinical utility of a PET tumor segmentation method using multi-level Otsu (MO-PET) in standard National Electrical Manufacturers Association (NEMA) image quality (IQ) phantom and patients with osteosarcoma. The NEMA IQ phantom was prepared with a lesion-to-background ratio (LBR) of either 8:1, 4:1, or 1.5:1. The artificial lesions in the phantom were segmented using MO-PET, gradient-based method (PETedge), relative threshold methods, and background threshold methods. Metabolic tumor volumes (MTVs) using MO-PET and PETedge were named as MTV (MO-PET) and MTV (PETedge), respectively. Among the MTVs using multiple methods, only MTV (MO-PET) and MTV (PETedge) showed excellent agreements with the actual volume of NEMA IQ phantom across the different LBRs (intraclass correlation coefficient, ICC = 0.987, 0.985 in LBR 8:1, 0.981, 0.993 in LBR 4:1 and 0.947, 0.994 in LBR 1.5:1). Repeated measurements of MTV (MO-PET) of the primary tumors showed excellent reproducibility with ICC of 0.994 (0.989-0.997) in patients with osteosarcoma. Also, MTV (MO-PET) was found to be predictive of Event Free Survival (EFS) [Hazard ratio (95% CI) = 6.1 (2.1-17.2), log rank P = 0.0003] in patients with osteosarcoma. We have validated in NEMA IQ phantom that the MTV (MO-PET) is accurate, and importantly, stable and consistent across a range of lesion sizes and LBRs representative of clinical tumor lesions. Furthermore, MTV (MO-PET) showed excellent reproducibility and was predictive for EFS in patients with osteosarcoma.