Predicting response to radiotherapy in tumors with PET/CT: when and how?

How Imaging Advances Are Defining the Future of Precision Radiation Therapy

Radiation therapy is fundamental in the treatment of cancer. Imaging has always played a central role in radiation oncology. Integrating imaging technology into irradiation devices has increased the precision and accuracy of dose delivery and decreased the toxic effects of the treatment. Although CT has become the standard imaging modality in radiation therapy, the development of recently introduced next-generation imaging techniques has improved diagnostic and therapeutic decision making in radiation oncology. Functional and molecular imaging techniques, as well as other advanced imaging modalities such as SPECT, yield information about the anatomic and biologic characteristics of tumors for the radiation therapy workflow. In clinical practice, they can be useful for characterizing tumor phenotypes, delineating volumes, planning treatment, determining patients' prognoses, predicting toxic effects, assessing responses to therapy, and detecting tumor relapse. Next-generation imaging can enable personalization of radiation therapy based on a greater understanding of tumor biologic factors. It can be used to map tumor characteristics, such as metabolic pathways, vascularity, cellular proliferation, and hypoxia, that are known to define tumor phenotype. It can also be used to consider tumor heterogeneity by highlighting areas at risk for radiation resistance for focused biologic dose escalation, which can impact the radiation planning process and patient outcomes. The authors review the possible contributions of next-generation imaging to the treatment of patients undergoing radiation therapy. In addition, the possible roles of radio(geno)mics in radiation therapy, the limitations of these techniques, and hurdles in introducing them into clinical practice are discussed. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Predictive impact of human papillomavirus circulating tumor DNA in treatment response monitoring of HPV-associated cancers; a meta-analysis on recurrent event endpoints

BACKGROUND

HPV infection can cause cancer, and standard treatments often result in recurrence. The extent to which liquid biopsy using HPV circulating tumor DNA (HPV ctDNA) can be used as a promising marker for predicting recurrence in HPV-related cancers remains to be validated. Here we conducted a systematic review and meta-analysis to assess its effectiveness in predicting treatment response.

METHODS

We conducted a systematic literature search of online databases, including PubMed, Embase, Scopus, and the Cochrane Library, up to December 2022. The goal was to identify survival studies that evaluated the potential of plasma HPV ctDNA at baseline and end-of-treatment (EoT) in predicting recurrence of related cancers. Hazard ratios were estimated directly from models or extracted from Kaplan-Meier plots.

RESULTS

The pooled effect of HPV ctDNA presence on disease recurrence was estimated to be HR = 7.97 (95% CI: [3.74, 17.01]). Subgroup analysis showed that the risk of recurrence was HR = 2.17 (95% CI: [1.07, 4.41]) for baseline-positive cases and HR = 13.21 (95% CI: [6.62, 26.36]) for EoT-positive cases. Significant associations were also observed between recurrence of oropharyngeal squamous cell carcinoma (HR = 12.25 (95% CI: [2.62, 57.36])) and cervical cancer (HR = 4.60 (95% CI: [2.08, 10.17])) in plasma HPV ctDNA-positive patients.

CONCLUSIONS

The study found that HPV ctDNA detection can predict the rate of relapse or recurrence after treatment, with post-treatment measurement being more effective than baseline assessment. HPV ctDNA could be used as a surrogate or incorporated with other methods for detecting residual disease.

Pepsin enhances glycolysis to promote malignant transformation of vocal fold leukoplakia epithelial cells with dysplasia

PURPOSE

The mechanism underlying malignant transformation of vocal fold leukoplakia (VFL) and the precise role of the expression of pepsin in VFL remain unclear. This study aimed to investigate the effects of acidified pepsin on VFL epithelial cell growth and migration, and also identify pertinent molecular mechanisms.

METHODS

Immunochemistry and Western blotting were performed to measure glucose transporter type 1 (GLUT1), monocarboxylate transporters 4 (MCT4), and Hexokinase-II (HK-II) expressions. Cell viability, cell cycle, apoptosis, and migration were investigated by CCK-8 assay, flow cytometry and Transwell chamber assay, respectively. Glycolysis-related contents were determined using the corresponding kits. Mitochondrial HK-II was photographed under a confocal microscope using Mito-Tracker Red.

RESULTS

It was found: the expression of pepsin and proportion of pepsin+ cells in VFL increased with the increased dysplasia grade; acidified pepsin enhanced cell growth and migration capabilities of VFL epithelial cells, reduced mitochondrial respiratory chain complex I activity and oxidative phosphorylation, and enhanced aerobic glycolysis and GLUT1 expression in VFL epithelial cells; along with the transfection of GLUT1 overexpression plasmid, 18FFDG uptake, lactate secretion and growth and migration capabilities of VFL epithelial cell were increased; this effect was partially blocked by the glycolysis inhibitor 2-deoxy-glucose; acidified pepsin increased the expression of HK-II and enhanced its distribution in mitochondria of VFL epithelial cells.

CONCLUSION

It was concluded that acidified pepsin enhances VFL epithelial cell growth and migration abilities by reducing mitochondrial respiratory complex I activity and promoting metabolic reprogramming from oxidative phosphorylation to aerobic glycolysis.

Association between Preoperative 18-FDG PET-CT SUVmax and Next-Generation Sequencing Results in Postoperative Ovarian Malignant Tissue in Patients with Advanced Ovarian Cancer

This study investigated the association between maximum standardized uptake values (SUVmax) on preoperative 18-FDG PET-CT and next-generation sequencing (NGS) results in post-surgical ovarian malignant tissue in patients with advanced ovarian cancer. Twenty-five patients with stage IIIC or IV ovarian cancer who underwent both preoperative 18-FDG PET-CT and postoperative NGS for ovarian malignancies were retrospectively enrolled. Two patients had no detected variants, 21 of the 23 patients with any somatic variant had at least one single nucleotide variant (SNV) or insertion/deletion (indel), 10 patients showed copy number variation (CNV), and two patients had a fusion variant. SUVmax differed according to the presence of SNVs/indels, with an SUVmax of 13.06 for patients with ≥ 1 SNV/indel and 6.28 for patients without (p = 0.003). Seventeen of 20 patients with Tier 2 variants had TP53 variants, and there was a statistically significant association between SUVmax and the presence of TP53 variants (13.21 vs. 9.35, p = 0.041). Analysis of the correlation between the sum of the Tier 1 and Tier 2 numbers and SUVmax showed a statistically significant correlation (p = 0.002; Pearson’s r = 0.588). In conclusion, patients with advanced ovarian cancer with SNVs/indels on NGS, especially those with TP53 Tier 2 variants, showed a proportional association with tumor SUVmax on preoperative PET-CT.

Response Evaluation Following Radiation Therapy With 18F-FDG PET/CT: Common Variants of Radiation-Induced Changes and Potential Pitfalls

Radiation therapy (RT) is one of the cornerstones in cancer treatment and approximately half of all patients will receive some form of RT during the course of their cancer management. Response evaluation after RT and follow-up imaging with ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) can be complicated by RT-induced acute, chronic or consequential effects. There is a general consensus that ¹⁸F-FDG PET/CT for response evaluation should be delayed for 12 weeks after completing RT to minimize the risk of false-positive findings. Radiation-induced late side effects in normal tissue can take years to develop and eventually cause symptoms that on imaging can potentially mimic recurrent disease. Imaging findings in radiation induced injuries depend on the normal tissue included in the irradiated volume and the radiation therapy regime including the total dose delivered, dose per fraction and treatment schedule. The intent for radiation therapy should be taken in consideration when evaluating the response on imaging, that is palliative vs curative or neoadjuvant vs adjuvant RT. Imaging findings can further be distorted by altered anatomy and sequelae following surgery within the radiation field. An awareness of common PET/CT-induced changes/injuries is essential when interpreting ¹⁸F-FDG PET/CT as well as obtaining a complete medical history, as patients are occasionally scanned for an unrelated cause to previously RT treated malignancy. In addition, secondary malignancies due to carcinogenic effects of radiation exposure in long-term cancer survivors should not be overlooked. ¹⁸F-FDG PET/CT can be very useful in response evaluation and follow-up in patients treated with RT, however, variants and pitfalls are common and it is important to remember that radiation-induced injury is often a diagnosis of exclusion.

The Prognostic Value of the Albumin to Gamma-Glutamyltransferase Ratio in Patients with Hepatocellular Carcinoma Undergoing Radiofrequency Ablation

Albumin to gamma-glutamyltransferase ratio (AGR) is a newly developed biomarker for the prediction of patients' prognosis in solid tumors. The purpose of the study was to establish a novel AGR-based nomogram to predict tumor prognosis in patients with early-stage HCC undergoing radiofrequency ablation (RFA). 394 hepatocellular carcinoma (HCC) patients who had received RFA as initial treatment were classified into the training cohort and validation cohort. Independent prognostic factors were identified by univariate and multivariate analyses. The value of AGR was evaluated by the concordance index (C-index), receiver operating characteristic (ROC) curves, and likelihood ratio tests (LAT). Logistic regression and nomogram were performed to establish the pretreatment scoring model based on the clinical variables. As a result, AGR = 0.63 was identified as the best cutoff value to predict overall survival (OS) in the training cohort. According to the results of multivariate analysis, AGR was an independent indicator for OS and recurrence-free survival (RFS). In both training cohort and validation cohort, the high-AGR group showed better RFS and OS than the low-AGR group. What is more, the C-index, area under the ROC curves, and LAT χ 2 values suggested that AGR outperformed the Child-Pugh (CP) grade and albumin-bilirubin (ALBI) grade in terms of predicting OS. The AGR, AKP, and tumor size were used to establish the OS nomogram. Besides, the results of Hosmer-Lemeshow test and calibration curve analysis displayed that both nomograms in the training and validation cohorts performed well in terms of calibration. Therefore, the AGR-based nomogram can predict the postoperative prognosis of early HCC patients undergoing RFA.

A Novel Approach Using FDG-PET/CT-Based Radiomics to Assess Tumor Immune Phenotypes in Patients With Non-Small Cell Lung Cancer

PURPOSE

Tumor microenvironment immune types (TMITs) are closely related to the efficacy of immunotherapy. We aimed to assess the predictive ability of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT)-based radiomics of TMITs in treatment-naive patients with non-small cell lung cancer (NSCLC).

METHODS

A retrospective analysis was performed in 103 patients with NSCLC who underwent 18F-FDG PET/CT scans. The patients were randomly assigned into a training set (n = 71) and a validation set (n = 32). Tumor specimens were analyzed by immunohistochemistry for the expression of programmed death-ligand 1 (PD-L1), programmed death-1 (PD-1), and CD8+ tumor-infiltrating lymphocytes (TILs) and categorized into four TMITs according to their expression of PD-L1 and CD8+ TILs. LIFEx package was used to extract radiomic features. The optimal features were selected using the least absolute shrinkage and selection operator (LASSO) algorithm, and a radiomics signature score (rad-score) was developed. We constructed a combined model based on the clinical variables and radiomics signature and compared the predictive performance of models using receiver operating characteristic (ROC) curves.

RESULTS

Four radiomic features (GLRLM_LRHGE, GLZLM_SZE, SUVmax, NGLDM_Contrast) were selected to build the rad-score. The rad-score showed a significant ability to discriminate between TMITs in both sets (p < 0.001, p < 0.019), with an area under the ROC curve (AUC) of 0.800 [95% CI (0.688-0.885)] in the training set and that of 0.794 [95% CI (0.615-0.916)] in the validation set, while the AUC values of clinical variables were 0.738 and 0.699, respectively. When clinical variables and radiomics signature were combined, the complex model showed better performance in predicting TMIT-I tumors, with the AUC values increased to 0.838 [95% CI (0.731-0.914)] in the training set and 0.811 [95% CI (0.634-0.927)] in the validation set.

CONCLUSION

The FDG-PET/CT-based radiomic features showed good performance in predicting TMIT-I tumors in NSCLC, providing a promising approach for the choice of immunotherapy in a clinical setting.