Primary vs nodal site PET/CT response as a prognostic marker in oropharyngeal squamous cell carcinoma treated with intensity-modulated radiation therapy

Predicting cancer outcomes with radiomics and artificial intelligence in radiology

The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the application of AI-based cancer imaging analysis to address other, more complex, clinical needs. In this Perspective, we discuss the next generation of challenges in clinical decision-making that AI tools can solve using radiology images, such as prognostication of outcome across multiple cancers, prediction of response to various treatment modalities, discrimination of benign treatment confounders from true progression, identification of unusual response patterns and prediction of the mutational and molecular profile of tumours. We describe the evolution of and opportunities for AI in oncology imaging, focusing on hand-crafted radiomic approaches and deep learning-derived representations, with examples of their application for decision support. We also address the challenges faced on the path to clinical adoption, including data curation and annotation, interpretability, and regulatory and reimbursement issues. We hope to demystify AI in radiology for clinicians by helping them to understand its limitations and challenges, as well as the opportunities it provides as a decision-support tool in cancer management.

Whole-body hybrid positron emission tomography imaging yields clinically relevant information in the staging and restaging of sinonasal tumors

Background

Whole‐body hybrid positron emission tomography (PET) imaging is increasingly used for sinonasal tumors. However, only empirical data exist on the additional, clinically relevant information derived from these techniques.

Methods

This study included 96 regionalized magnetic resonance imaging (MRI) of the sinonasal tract/neck and separate hybrid FDG‐PET/CT or FDG‐PET/MRI in 74 patients. Additional radiological information (ARI) obtained from each hybrid examination was analyzed and its clinically relevance was determined. Clinically relevant information (CRI) was categorized with regard to primary tumor site, regional lymph node metastases, distant metastases, second primary tumors, and non‐neoplastic findings.

Results

A total of 45/96 (46.9%) hybrid PET examinations revealed ARI. CRI was found in 32/96 (33.3%) examinations and concerned the primary tumor site (6.1%), regional lymph node metastases (4.1%), distant metastases (14.3%), second primary tumors (7.3%), and non‐neoplastic findings (5.1%).

Conclusions

Hybrid PET imaging yields additional radiological information translating into clinically relevant information in a substantial proportion of patients with sinonasal tumors.

Advances in Imaging for HPV-Related Oropharyngeal Cancer: Applications to Radiation Oncology

While there has been an overall decline of tobacco and alcohol-related head and neck cancer in recent decades, there has been an increased incidence of HPV-associated oropharyngeal cancer (OPC). Recent research studies and clinical trials have revealed that the cancer biology and clinical progression of HPV-positive OPC is unique relative to its HPV-negative counterparts. HPV-positive OPC is associated with higher rates of disease control following definitive treatment when compared to HPV-negative OPC. Thus, these conditions should be considered unique diseases with regards to treatment strategies and survival. In order to sufficiently characterize HPV-positive OPC and guide treatment strategies, there has been a considerable effort to diagnose, prognose, and track the treatment response of HPV-associated OPC through advanced imaging research. Furthermore, HPV-positive OPC patients are prime candidates for radiation de-escalation protocols, which will ideally reduce toxicities associated with radiation therapy and has prompted additional imaging research to detect radiation-induced changes in organs at risk. This manuscript reviews the various imaging modalities and current strategies for tackling these challenges as well as provides commentary on the potential successes and suggested improvements for the optimal treatment of these tumors.

Hybrid positron emission tomography imaging for initial staging of sinonasal tumors: Total lesion glycolysis as prognosticator of treatment response

BACKGROUND

To assess hybrid positron emission tomography (PET) imaging in the initial staging and outcome prediction of sinonasal malignancies.

METHODS

Retrospective study on patients with sinonasal malignancies undergoing hybrid PET imaging for initial staging.

RESULTS

Complete remission (CR) was achieved in 45 of 65 patients (69.2%). Overall sensitivity for detection of primaries using 18F-fluoro-deoxy-d-glucose PET (FDG-PET) was 95.4%, for lymph node metastases 100% and distant metastases (DM) 100%. On univariate analysis, PET parameter total lesion glycolysis (TLG) was associated with achieving CR after primary treatment (176.8 ± 157.2 vs 83.7 ± 110.8, P = .03). Multivariate logistic regression demonstrated that TLG adjusted for the T classification best predicted achievement of CR.

CONCLUSIONS

Hybrid PET imaging yields an excellent sensitivity in detecting primary tumors, lymph node metastases and DM in sinonasal malignancies. TLG of the primary tumor is an independent prognostic factor for achieving CR after initial treatment.