The value of global quantification of PET imaging in hematological disorders

Introduction: PET/CT imaging has been established as a useful modality to assess hematological malignancies, particularly lymphoma and multiple myeloma (MM). The visual interpretation of PET/CT images is based on the Deauville five-point scale in lymphoma [1]. In MM, the number and site of FDG-avid focal lesions, the number of osteolytic lesions, and the presence of extramedullary disease have also been evaluated. In addition to visual assessment, reporting different quantitative metrics is a common practice in the interpretation of PET/CT scans. The common quantification techniques are based on reporting SUV values for each focal lesion[]. Hematological malignancies are widespread diseases. Therefore, assessing focal lesions without considering the diffuse nature of these diseases cannot provide comprehensive data on total tumor metabolic burden.

1. Review the commonly used interpretation techniques of PET images in hematological diseases

2. Discuss the shortcomings of focal-based quantification techniques

3. Discuss the global quantification technique and its application in multiple myeloma, lymphoma, leukemia, and polycythemia vera

Methods A literature review was conducted to collect current published studies on the subject using PubMed and Google Scholar databases. Conclusion We recently introduced a CT-based segmentation method, which can be applied in both clinical and research settings. In this technique, a 3D growing region algorithm with a lower and upper threshold of 150-1500 Hounsfield units (HU) followed by a morphological closing algorithm with a structuring element radius of 20 is applied to the fused FDG-PET/CT images. This allows for the segmentation of cortical and trabecular bone (OsiriX software, Pixmeo SARL; Bernex, Switzerland). The global mean SUV (G SUV mean) was reported. Recent studies have shown that higher values of G SUVmean in pre-treatment scans are associated with poor response to treatment in MM. Moreover, this technique has been applied to assess the increased bone marrow metabolic activity in patients with polycythemia vera and CLL compared to healthy controls.