The Current and Evolving Role of PET in Personalized Management of Lung Cancer

Pretreatment 18-FDG-PET/CT parameters can serve as prognostic imaging biomarkers in recurrent NSCLC patients treated with reirradiation-chemoimmunotherapy

BACKGROUND AND PURPOSE

Our study aimed to assess whether quantitative pretreatment 18F-FDG-PET/CT parameters could predict prognostic clinical outcome of recurrent NSCLC patients who may benefit from ablative reirradiation.

MATERIALS AND METHODS

Forty-eight patients with recurrent NSCLC of all UICC stages who underwent ablative thoracic reirradiation were analyzed. Twenty-nine (60%) patients received immunotherapy with or without chemotherapy in addition to reirradiation. Twelve patients (25%) received reirradiation only and seven (15%) received chemotherapy and reirradiation. Pretreatment 18-FDG-PET/CT was mandatory in initial diagnosis and recurrence, based on which volumetric and intensity quantitative parameters were measured before reirradiation and their impact on overall survival, progression-free survival, and locoregional control was assessed.

RESULTS

With a median follow-up time of 16.7 months, the median OS was 21.8 months (95%-CI: 16.2-27.3). On multivariate analysis, OS and PFS were significantly influenced by MTV (p < 0.001 for OS; p = 0.006 for PFS), TLG (p < 0.001 for OS; p = 0.001 for PFS) and SUL peak (p = 0.0024 for OS; p = 0.02 for PFS) of the tumor and MTV (p = 0.004 for OS; p < 0.001 for PFS) as well as TLG (p = 0.007 for OS; p = 0.015 for PFS) of the metastatic lymph nodes. SUL peak of the tumor (p = 0.05) and the MTV of the lymph nodes (p = 0.003) were only PET quantitative parameters that significantly impacted LRC.

CONCLUSION

Pretreatment tumor and metastastic lymph node MTV, TLG and tumor SUL peak significantly correlated with clinical outcome in recurrent NSCLC patients treated with reirradiation-chemoimmunotherapy.

Clinical Applications of Artificial Intelligence in Positron Emission Tomography of Lung Cancer

The ability of a computer to perform tasks normally requiring human intelligence or artificial intelligence (AI) is not new. However, until recently, practical applications in medical imaging were limited, especially in the clinic. With advances in theory, microelectronic circuits, and computer architecture as well as our ability to acquire and access large amounts of data, AI is becoming increasingly ubiquitous in medical imaging. Of particular interest to our community, radiomics tries to identify imaging features of specific pathology that can represent, for example, the texture or shape of a region in the image. This is conducted based on a review of mathematical patterns and pattern combinations. The difficulty is often finding sufficient data to span the spectrum of disease heterogeneity because many features change with pathology as well as over time and, among other issues, data acquisition is expensive. Although we are currently in the early days of the practical application of AI to medical imaging, research is ongoing to integrate imaging, molecular pathobiology, genetic make-up, and clinical manifestations to classify patients into subgroups for the purpose of precision medicine, or in other words, predicting a priori treatment response and outcome. Lung cancer is a functionally and morphologically heterogeneous disease. Positron emission tomography (PET) is an imaging technique with an important role in the precision medicine of patients with lung cancer that helps predict early response to therapy and guides the selection of appropriate treatment. Although still in its infancy, early results suggest that the use of AI in PET of lung cancer has promise for the detection, segmentation, and characterization of disease as well as for outcome prediction.

Update on Molecular Imaging and Precision Medicine in Lung Cancer

Precision medicine integrates molecular pathobiology, genetic make-up, and clinical manifestations of disease in order to classify patients into subgroups for the purposes of predicting treatment response and suggesting outcome. By identifying those patients who are most likely to benefit from a given therapy, interventions can be tailored to avoid the expense and toxicity of futile treatment. Ultimately, the goal is to offer the right treatment, to the right patient, at the right time. Lung cancer is a heterogeneous disease both functionally and morphologically. Further, over time, clonal proliferations of cells may evolve, becoming resistant to specific therapies. PET is a sensitive imaging technique with an important role in the precision medicine algorithm of lung cancer patients. It provides anatomo-functional insight during diagnosis, staging, and restaging of the disease. It is a prognostic biomarker in lung cancer patients that characterizes tumoral heterogeneity, helps predict early response to therapy, and may direct the selection of appropriate treatment.

Utility of Molecular Imaging with 2-Deoxy-2-[Fluorine-18] Fluoro-DGlucose Positron Emission Tomography (18F-FDG PET) for Small Cell Lung Cancer (SCLC): A Radiation Oncology Perspective

BACKGROUND AND OBJECTIVE

Although accounting for a relatively small proportion of all lung cancers, small cell lung cancer (SCLC) remains to be a global health concern with grim prognosis. Radiotherapy (RT) plays a central role in SCLC management either as a curative or palliative therapeutic strategy. There has been considerable progress in RT of SCLC, thanks to improved imaging techniques leading to accurate target localization for precise delivery of RT. Positron emission tomography (PET) is increasingly used in oncology practice as a non-invasive molecular imaging modality.

METHODS

Herein, we review the utility of molecular imaging with 2-deoxy-2-[fluorine-18] fluoro-Dglucose PET (18F-FDG PET) for SCLC from a radiation oncology perspective.

RESULTS

There has been extensive research on the utility of PET for SCLC in terms of improved staging, restaging, treatment designation, patient selection for curative/palliative intent, target localization, response assessment, detection of residual/recurrent disease, and prediction of treatment outcomes.

CONCLUSION

PET provides useful functional information as a non-invasive molecular imaging modality and may be exploited to improve the management of patients with SCLC. Incorporation of PET/CT in staging of patients with SCLC may aid in optimal treatment allocation for an improved therapeutic ratio. From a radiation oncology perspective, combination of functional and anatomical data provided by integrated PET/CT improves discrimination between atelectasis and tumor, and assists in the designation of RT portals with its high accuracy to detect intrathoracic tumor and nodal disease. Utility of molecular imaging for SCLC should be further investigated in prospective randomized trials to acquire a higher level of evidence for future potential applications of PET.

Targeted Therapy and Imaging Findings

Non-small cell lung cancer (NSCLC) is usually diagnosed when it is not amenable to curative surgery or radiation. Many of these patients are candidates for systemic therapy. Median survival is only approximately 10 months, and, accordingly, treatment in advanced NSCLC is evolving toward a more personalized approach with the identification of genetic abnormalities based on biomarkers. For example, gene mutations in EGFR (epidermal growth factor receptor) and ALK (anaplastic lymphoma kinase) lead to a cascade of pathways resulting in uncontrolled growth, proliferation, and survival of tumor cells. Targeted therapies are aimed at the products of these mutated genes and include agents such as erlotinib and gefitinib (in EGFR-mutant NSCLC) or crizotinib (in ALK-positive NSCLC). Antiangiogenesis agents such as bevacizumab are another category of targeted therapy that inhibits vascular endothelial growth factors. The imaging characteristics of advanced NSCLC with genetic abnormalities, the evolution of targeted therapies and their imaging manifestations will be discussed.

Molecular Imaging and Precision Medicine in Lung Cancer

Precision medicine allows tailoring of preventive or therapeutic interventions to avoid the expense and toxicity of futile treatment given to those who will not respond. Lung cancer is a heterogeneous disease functionally and morphologically. PET is a sensitive molecular imaging technique with a major role in the precision medicine algorithm of patients with lung cancer. It contributes to the precision medicine of lung neoplasia by interrogating tumor heterogeneity throughout the body. It provides anatomofunctional insight during diagnosis, staging, and restaging of the disease. It is a biomarker of tumoral heterogeneity that helps direct selection of the most appropriate treatment, the prediction of early response to cytotoxic and cytostatic therapies, and is a prognostic biomarker in patients with lung cancer.