Prognostic utility of serial 18F-FDG-PET/CT in patients with locally advanced rectal cancer who underwent tri-modality treatment

[18F]FDG-PET-Based Personalized Radiotherapy Dose Prescription

PET imaging with 2'-deoxy-2'-[18F]fluoro-D-glucose ([18F]FDG) has become one of the pillars in the management of malignant diseases. It has proven value in diagnostic workup, treatment policy, follow-up, and as prognosticator for outcome. [18F]FDG is widely available and standards have been developed for PET acquisition protocols and quantitative analyses. More recently, [18F]FDG-PET is also starting to be appreciated as a decision aid for treatment personalization. This review focuses on the potential of [18F]FDG-PET for individualized radiotherapy dose prescription. This includes dose painting, gradient dose prescription, and [18F]FDG-PET guided response-adapted dose prescription. The current status, progress, and future expectations of these developments for various tumor types are discussed.

Evaluation of survival of the patients with metastatic rectal cancer by staging 18F-FDG PET/CT radiomic and volumetric parameters

OBJECTIVE

The aim of this study is to predict the prognosis in patients with metastatic rectal cancer (mRC) by obtaining a model with machine learning (ML) algorithms through volumetric and radiomic data obtained from baseline 18-Fluorine Fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) images.

METHODS

Sixty-two patients with mRC who underwent 18F-FDG PET/CT imaging for staging between January 2015 and January 2021 were evaluated using LIFEx software. The volume of interest (VOI) of the primary tumor was generated and volumetric and textural features were obtained from this VOI. In addition, metabolic tumor volume (tMTV) and total lesion glycolysis (tTLG) values of tumor foci in the whole body. Clinical and radiomic data were evaluated with ML algorithms to create a model that predicts survival. Significant associations between these features and 1-year and 2-year survival were investigated.

RESULTS

Random forest algorithm was the most successful algorithm in predicting 2-year survival (AUC: 0.843, PRC: 0.822, and MCC: 0.583). The model obtained with this algorithm was able to predict 49 patients with 79.03% accuracy. While tMTV and tTLG values were successful in predicting 1-year survival (p: 0.002 and 0.007, respectively), texture characteristics from the primary tumor did not show a significant relationship with 1-year survival.

CONCLUSIONS

In addition to the important role of 18F-FDG PET/CT in staging patients with mRC, this study shows that it is possible to predict survival with ML methods, with parameters obtained using texture analysis from the primary tumor and whole body volumetric parameters.

The reduction of 18F-FDG uptake ability of tumor tissue after neoadjuvant chemoradiotherapy in locally advanced rectal cancer can effectively reflect the degree of tumor regression

Introduction

To evaluate the predictive value of ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET-CT) imaging parameters for the response to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC).

Methods

From January 2016 to March 2020, 52 LARC patients who underwent ¹⁸F-FDG PET-CT scans within 1 week before and 8-9 weeks after nCRT, were enrolled in this study according to a pre-designed screening criteria. After total mesorectal excision (TME) surgery, we assessed tumor response to treatment and analyzed the correlation between imaging parameters obtained from two PET-CT scans and tumor regression status.

Results

Tumor response assessment showed that 13 of 52 patients received good response (GR), including 9 cases with pathological complete regression (pCR) and 4 cases with near-pathological complete regression (near-pCR). We also found that the maximum standard uptake value after nCRT (post-SUVmax), the response index (RI), the mean standard uptake values after nCRT (post-SUVmean), and the ratio of tumor SUVmean to liver SUVmean after nCRT (post-Ratio), were correlated with GR and pCR. Among these parameters, post-SUVmax and RI had a near-strong correlation with pCR (r_s= -0.58 and 0.59, respectively), and also had a strong correlation with GR (r_s = -0.7 and 0.63, respectively). Further ROC analysis showed that post-SUVmax and RI had higher values in predicting whether patients could achieve GR and pCR after nCRT, and the area under the curve (AUC) of both were greater than 0.9. The positive predictive values (PPVs) and negative predictive values (NPVs) of post-SUVmax for GR were 80.01% and 97.3%, and for pCR were 66.68% and 97.5%, respectively. The PPVs and NPVs of the RI values for GR were 84.61% and 94.87%, and for pCR were 69.24% and 100%, respectively.

Conclusion

For LARC patients, the analysis of imaging parameters such as post-SUVmax and RI, which can reflect the changes of ¹⁸F-FDG uptake capacity of tumor tissues before and after nCRT, is of great value for predicting the response of patients to neoadjuvant therapy and guiding the selection of subsequent treatment strategies.

Predicting neoadjuvant chemoradiotherapy response with functional imaging and liquid biomarkers in locally advanced rectal cancer

INTRODUCTION

Non-invasive predictive quantitative biomarkers are required to guide treatment individualization in patients with locally advanced rectal cancer (LARC) in order to maximise therapeutic outcomes and minimise treatment toxicity. Magnetic resonance imaging (MRI), positron emission tomography (PET) and blood biomarkers have the potential to predict chemoradiotherapy (CRT) response in LARC.

AREAS COVERED

This review examines the value of functional imaging (MRI and PET) and liquid biomarkers (circulating tumor cells (CTCs) and circulating tumor nucleic acid (ctNA)) in the prediction of CRT response in LARC. Selected imaging and liquid biomarker studies are presented and the current status of the most promising imaging (apparent diffusion co-efficient (ADC), K^trans, SUV_max, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) and liquid biomarkers (circulating tumor cells (CTCs), circulating tumor nucleic acid (ctNA)) is discussed. The potential applications of imaging and liquid biomarkers for treatment stratification and a pathway to clinical translation are presented.

EXPERT OPINION

Functional imaging and liquid biomarkers provide novel ways of predicting CRT response. The clinical and technical validation of the most promising imaging and liquid biopsy biomarkers in multi-centre studies with harmonised acquisition techniques is required. This will enable clinical trials to investigate treatment escalation or de-escalation pathways in rectal cancer.

Correlation between apparent diffusion coefficient and tumor-stroma ratio in hybrid 18F-FDG PET/MRI: preliminary results of a rectal cancer cohort study

Background

To explore possible correlations between the tumor-stroma ratio (TSR) and different imaging features of fluorine-18-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (¹⁸F-FDG PET/MRI) in untreated rectal cancer patients.

Methods

A patients with rectal cancer were included in this study. All participants were examined preoperatively with whole-body ¹⁸F-FDG PET/MRI. Two pathologists evaluated the TSR of tumors together. Apparent diffusion coefficient (ADC) values and PET-related parameters of the primary lesions were measured and compared between the stroma-high and stroma-low groups. Pearson's correlation or Spearman's rank correlation were used to evaluate the correlation between the ADC values, PET-related parameters, and pathological indices.

Results

Our results showed that in the untreated rectal cancer patients, the ADC mean values correlated with the TSR (r=0.327; P=0.007), and stroma-high (low TSR) rectal cancer corresponded to relatively lower ADC mean values (813.54±88.68 vs. 879.92±133.18; P=0.018). The ADC mean and ADC minimum (ADCmin) values were found to be negatively correlated with the pathological T stages (r=-0.384, P=0.001; r=-0.416, P=0.001, respectively) as well as the largest tumor diameters (r=-0.340, P=0.005; r=-0.314, P=0.010, respectively) of rectal cancer. In addition, the pathological T stages correlated with all PET-related metabolic parameters, including mean standard uptake value (SUV), maximum SUV (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) (r=0.338, P=0.006; r=0.350, P=0.004; r=0.326, P=0.007; and r=0.472, P<0.001, respectively). Our results also identified associations between the ADCmin values and SUVmean, SUVmax, and TLG (r=-0.335, P=0.006; r=-0.343, P=0.005; and r=-0.343, P=0.005, respectively). However, there were no statistical correlations between the PET/MRI parameters and the immunohistochemical (IHC) results.

Conclusions

This study indicated that the intratumoral heterogeneity measured by PET/MRI may reflect characteristics of the tumor microenvironment. Hence, PET/MRI parameters might be helpful in predicting tumor aggressiveness and prognosis.

Dynamic Contrast-enhanced Magnetic Resonance Imaging Evaluation of Whole Tumour Perfusion Heterogeneity Predicts Distant Disease-free Survival in Locally Advanced Rectal Cancer

AIMS

To evaluate diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging for the prediction of disease-free survival (DFS) in patients with locally advanced rectal cancer.

MATERIALS AND METHODS

Patients with stage II or III rectal adenocarcinoma undergoing neoadjuvant chemoradiotherapy (CRT) and surgery were eligible. Patients underwent multi-parametric magnetic resonance imaging (diffusion-weighted imaging and dynamic contrast-enhanced) before CRT, during CRT (week 3) and after CRT (1 week prior to surgery). Whole tumour apparent diffusion coefficient (ADC) and K^trans histogram quantiles (10th, 25th, 50th, 75th, 90th) were extracted for analysis. The associations between ADC and K^trans at three timepoints with time to relapse were analysed as a continuous variable using a Cox proportional hazard model.

RESULTS

Thirty-three patients were included in this analysis. The median follow-up was 4.4 years. No patient had locoregional relapse. Nine patients developed distant metastases. The hazard ratios for after CRT K^trans 10th (P = 0.035), 25th (P = 0.048), 50th (P = 0.046) and 75th (P = 0.045) quantiles were statistically significant for DFS. The best K^trans cut-off point after CRT for predicting relapse was 28 × 10^-3 mL/g/min (10th quantile), with a higher K^trans value predicting distant relapse. The 4-year DFS probability was 0.93 for patients with after CRT K^trans value ≤28 × 10^-3 mL/g/min versus 0.45 for patients with after CRT K^trans value >28 × 10^-3 mL/g/min. ADC was not able to predict DFS.

CONCLUSIONS

Patients with higher K^trans values after CRT (before surgery) in a histogram analysis of whole tumour heterogeneity had a significantly lower 4-year distant DFS and could be considered for more intense systemic therapy.

A Nomogram for Predicting Pathological Complete Response to Neoadjuvant Chemoradiotherapy Using Semiquantitative Parameters Derived From Sequential PET/CT in Locally Advanced Rectal Cancer

We evaluated the predictive value of semiquantitative volumetric parameters derived from sequential PET/CT and developed a nomogram to predict pathological complete response (pCR) in patients with rectal cancer treated by neoadjuvant chemoradiotherapy (nCRT). From April 2008 to December 2013, among the patients who underwent nCRT, those who were taken sequential PET/CT before and after nCRT were included. MRI-based staging and semiquantitative parameters of PET/CT including standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were evaluated before and after nCRT. Multivariable analysis was performed to select significant predictors to construct a nomogram. Sensitivity, specificity, accuracy, and area under the receiver operating characteristics curve (AUC) of the model were evaluated to determine its performance. Among 137 eligible patients, 17 (12.4%) had pCR. All post-PET/CT parameters showed significant differences between pCR and non-pCR groups. Patients were randomly assigned to a training group (91 patients) and a validation group (46 patients). In multivariable analysis with the training group, post-CEA, post-MRI T staging, post-SUV_max, and post-MTV were significantly associated with pCR. There was no significant pre-nCRT variable for predicting pCR. Using significant predictors, a nomogram was developed. Sensitivity, specificity, accuracy, and AUC of the nomogram were 0.882, 0.808, 0.848, and 0.884 with the training group and 0.857, 0.781, 0.783, and 0.828 with the validation group, respectively. This model showed the better performance than other predictive models that did not contain PET/CT parameters. A nomogram containing semiquantitative post-PET/CT could effectively select candidates for organ-sparing strategies.