Prognostic Value of Volumetric Parameters on Staging and Posttreatment FDG PET/CT in Patients With Stage IV Non-Small Cell Lung Cancer

FDG PET/CT Tumor Dissemination Characteristic Predicts the Outcome of First-Line Systemic Therapy in Non-small Cell Lung Cancer

RATIONALE AND OBJECTIVES

To explore the correlation between the tumor dissemination characteristic at 18F-fluoro-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) images and the outcome of first-line systemic therapy for stage IV non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

The current retrospective study included 101 NSCLC patients receiving first-line systemic therapy with baseline 18F-FDG PET/CT images available. The distance between the two lesions that were the farthest apart was defined as Dmax to calculate the tumor dissemination. The tumor metabolic volume (MTV) of the primary tumor and the MTV of the whole-body tumor lesions (MTVwb) were calculated using 18F-FDG PET/CT imaging. The Kaplan-Meier survival analyses and Cox predictive model were performed to assess the relationship between the parameters and survival.

RESULTS

Dmax and MTVwb were independent prognostic factors for overall survival (OS) (p = 0.019 and p = 0.011, respectively) and progression-free survival (PFS) (p = 0.043 and p = 0.009, respectively). Poor PFS and OS were associated with high MTVwb (>54.0 cm3) and high Dmax (>48.5 cm) (p = 0.006 and p = 0.008, respectively). When MTVwb and Dmax were combined, three risk groups were stratified with no (score 0), one (score 1), or two (score 2) factors (p < 0.001 for PFS, p < 0.001 for OS). The group with a score of 0 had a considerably longer PFS and OS than those who received a score of 1 or 2 (PFS: 61.1%, 43.5%, and 21.1%, respectively, OS: 77.8%, 54.3%, and 36.8%, respectively).

CONCLUSION

The combination of tumor dissemination characteristic (Dmax) and tumor burden (MTVwb) can further improve the prognosis stratification of NSCLC.

Usefulness of 18 F-FDG PET/computed tomography metabolic parameters in predicting sarcopenia and prognosis of treatment-naive patients with non-small cell lung cancer

PURPOSE

Sarcopenia tremendously impacts the quality of life but remains debatable in prognostication in treatment-naive patients with non-small cell lung cancer (NSCLC). Hence, this study aimed to find a clinically feasible approach using 18 F-FDG PET/computed tomography (CT) imaging parameters and clinical characteristics to predict sarcopenia and determine independent prognostic factors.

METHODS

Clinical characteristics and 18 F-FDG PET/CT metabolic parameters, including maximum standard uptake value, metabolic tumor volume, and total lesion glycolysis of primary tumor (SUVmax_P, MTV_P, and TLG_P) and combination of whole-body lesions (MTV_C and TLG_C) were collected in 344 treatment-naive patients with NSCLC. Skeletal muscle index at the third lumbar vertebra was calculated to determine sarcopenia. SUVmax of the psoas major muscle (SUVmax_M) was measured at the third lumbar vertebra as well. The diagnostic endpoint is the probability of sarcopenia, and the survival endpoints include progression-free survival (PFS) and overall survival (OS).

RESULTS

Among 344 patients with NSCLC there were 271 patients with adenocarcinoma and 73 with squamous cell carcinoma (SCC). One hundred forty-seven patients (42.7%) were diagnosed with sarcopenia. Higher age, male, lower BMI, SCC, and lower SUVmax_M were correlated with a higher incidence of sarcopenia ( P  < 0.05), while age, sex and SUVmax_M were independently predictive of sarcopenia. Multivariate Cox-regression analysis revealed that BMI, advanced stage and TLG_C were independent predictors of PFS and OS, while sex was independently predictive of OS.

CONCLUSIONS

The incidence of sarcopenia increased with declining SUVmax of muscle. BMI, tumor stage, and TLG_C, but not sarcopenia, were found independently predictive of both PFS and OS.

Role of 18F-FDG PET/CT and sarcopenia in untreated non-small cell lung cancer with advanced stage

BACKGROUND

Sarcopenia is essential in managing advanced stage (III-IV) non-small cell lung cancer (NSCLC) but is laborious to diagnose using currently available method. This study aimed to establish a simple approach to predict sarcopenia using ¹⁸F-FDG PET/CT parameters and clinical characteristics and determine their roles in prognostication in advanced stage NSCLC.

METHODS

Untreated 202 NSCLC patients with stage III-IV were retrospectively reviewed. Sarcopenia was defined using the skeletal muscle index (SMI) measured at the third lumbar vertebra (L3). ¹⁸F-FDG PET/CT metabolic parameters of maximum standard uptake value, metabolic tumor volume, and total lesion glycolysis of the primary tumor (SUVmax_T, MTV_T, and TLG_T) and of whole-body lesions (MTV_WB and TLG_WB) were measured. Besides, SUVmax of the psoas major muscle (SUVmax_Muscle) was measured at the L3 level. The diagnostic endpoint was the probability of sarcopenia, and the survival endpoints included progression-free survival (PFS) and overall survival (OS).

RESULTS

Among the enrolled 202 patients, 82 (40.6%) were diagnosed with sarcopenia. Higher age, male, lower BMI, and lower SUVmax_Muscle were correlated with a higher incidence of sarcopenia (P < 0.05), while age, sex, BMI, and SUVmax_Muscle were independently predictive of sarcopenia, and thus were utilized to construct a nomogram model. Multivariate Cox regression analysis revealed that sarcopenia score derived from the nomogram model, sarcopenia, stage, and TLG_WB were independently predictive of both PFS and OS.

CONCLUSION

The incidence of sarcopenia increased with declining SUVmax_Muscle in advanced stage NSCLC. Our model using age, sex, BMI, and SUVmax_Muscle might be substituted for the complicated measurement of SMI. After adjustment by stage and TLG_WB, both sarcopenia score and sarcopenia were found to be independently predictive of PFS and OS.

Prognostic value of node-to-primary tumor maximum standardized uptake value ratio in T1-4N1-3M0 non-small cell lung cancer patients treated with concurrent chemo-radiotherapy

BACKGROUND

This study aimed to identify whether NTR is the independent risk factor for progression-free survival (PFS) and overall survival (OS) in patients treated with concurrent chemo-radiotherapy (cCRT).

METHODS

We retrospectively studied 106 T1-4N1-3M0 non-small cell lung cancer patients treated with cCRT. The maximum standardized uptake value (SUVTumor) of the primary tumor and the metastatic lymph nodes (SUVLN) were measured. The prognostic significance of NTR for predicting PFS and OS was assessed. A multi-adjusted spline regression model was conducted to provide more precise estimates and examine the shape of the associations between NTR and the risk of progression.

RESULTS

From 2012 to 2017, 106 eligible patients were analyzed. The median follow-up time was 15.3 months (3.5-44.6 months). We determined the maximizing area under the time-dependent receiver operating characteristic curve was at an NTR of 0.73 for predicting PFS. The two-year PFS was significantly lower in the high-NTR group (35.7% vs. 55.4%, P = 0.02) and two-year OS (43.4% vs. 61.1%, P = 0.03 was also significantly worse. Multivariable analysis revealed that only NTR was an independent prognostic factor for PFS (hazard ratio [HR]: 10.04, P < 0.001) and OS (HR: 4.19, P = 0.03). The restricted cubic spline regression model showed that NTR had a non-linear relationship with log relative risk for progression.

CONCLUSION

NTR was an independent risk factor for predicting PFS and OS in T1-4N1-3M0 non-small cell lung cancer patients treated with cCRT.

Role of PET/CT in post-therapeutic assessment of bronchogenic carcinoma

Background

Lung cancer is the most common among all kinds of cancers. It still constitutes the leading cause of cancer-related deaths worldwide, even with major advancements in prevention and treatments available. More than 85% of the cases are of non-small cell lung cancer (NSCLC), while less than 15% are of small cell lung cancers (SCLCs).

Patients and methods

This is a prospective study of 20 patients confirmed histopathologically to have bronchogenic carcinoma, who came for assessment of therapeutic response. All patients underwent positron emission tomography/computed tomography (PET/CT) before and after therapy. Semiquantitative assessment was used to determine maximum standardized uptake value (SUVmax). Treatment response evaluation was assessed according to the Response Evaluation Criteria in Solid Tumors (RECIST) criteria.

Results

Comparison of the pre- and post-treatment SUVmax in the responder and non-responder groups revealed that the post-treatment SUV was significantly lower than the baseline SUV in the responder group (P = 0.008). The responder post-treatment SUV and ∆ SUV were significantly lower than the non-responder values (P = 0.014 and 0.0004 respectively). The optimum threshold values of post-treatment SUV and ∆ SUV threshold defined by the receiver operating characteristic (ROC) curve analysis were ≤ 8 and ≤ −48.3 respectively. The sensitivity, specificity, PPV, NPV, and AUC of post-treatment SUV for predicting tumor response were 100%, 66.67%, 66.7%, 100%, and 0.833 respectively. The sensitivity, specificity, PPV, NPV, and AUC of ∆ SUV for predicting tumor response were 100%, 91.67%, 88.9%, 100%, and 0.979% respectively.

Conclusion

PET/CT proved itself as useful, efficient, and reliable tool in follow-up of lung cancer patients as it gives an early and accurate metabolic response assessment before any CT changes, leading to early modification of therapy or confirmation of its efficiency.

Metabolic active tumour volume quantified on [18F]FDG PET/CT further stratifies TNM stage IV non-small cell lung cancer patients

PURPOSE

This study aimed to assess whether the whole body metabolic active tumour volume (MTV_WB), quantified on staging [¹⁸F]FDG PET/CT, could further stratify stage IV non-small cell lung cancer (NSCLC) patients.

METHODS

A group of 160 stage IV NSCLC patients, submitted to staging [¹⁸F]FDG PET/CT between July 2010 and May 2020, were retrospectively evaluated. MTV_WB was quantified. Univariate and multivariate Cox regressions were carried out to assess correlation with overall survival (OS). C-statistic was used to test predictive power. Kaplan-Meier survival curves with Log-Rank tests were performed to compute statistical differences between strata from dichotomized variables and to calculate the estimated mean survival times (EMST). Survival rates at 1 and 5 years were calculated.

RESULTS

MTV_WB was a statistically significant predictor of OS on univariate (p < 0.0001) and multivariate analyses (p < 0.0001). The multivariate model with MTV_WB (Cindex ± SE = 0.657 ± 0.024) worked significantly better as an OS predictor than the cTNM model (Cindex ± SE = 0.544 ± 0.028) (p = 0.003). An EMST of 29.207 ± 3.627(95% CI 22.099-36.316) months and an EMST of 10.904 ± 1.171(95% CI 8.609-13.199) months (Log-Rank p < 0.0001) were determined for patients with MTV_WB < 104.3 and MTV_WB ≥ 104.3, respectively. In subsamples of stage IVA (cut-off point = 114.5) and IVB patients (cut-off point = 191.1), statistically significant differences between EMST were also reported, with p-values of 0.0001 and 0.0002, respectively. In both substages and in the entire cohort, patients with MTV_WB ≥ cut-off points had lower EMST and survival rates.

CONCLUSION

Baseline MTV_WB, measured on staging [¹⁸F]FDG PET/CT, further stratifies stage IV NSCLC patients. This parameter is an independent predictor of OS and provides valuable prognostic information over the 8th edition of cTNM staging.

Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML)

The identification of reliable and non-invasive oncology biomarkers remains a main priority in healthcare. There are only a few biomarkers that have been approved as diagnostic for cancer. The most frequently used cancer biomarkers are derived from either biological materials or imaging data. Most cancer biomarkers suffer from a lack of high specificity. However, the latest advancements in machine learning (ML) and artificial intelligence (AI) have enabled the identification of highly predictive, disease-specific biomarkers. Such biomarkers can be used to diagnose cancer patients, to predict cancer prognosis, or even to predict treatment efficacy. Herein, we provide a summary of the current status of developing and applying Magnetic resonance imaging (MRI) biomarkers in cancer care. We focus on all aspects of MRI biomarkers, starting from MRI data collection, preprocessing and machine learning methods, and ending with summarizing the types of existing biomarkers and their clinical applications in different cancer types.

The Study of Tumor Volume as a Prognostic Factor in T Staging System for Non-Small Cell Lung Cancer: An Exploratory Study

Background:

This study aimed to evaluate T staging system for non-small cell lung cancer (NSCLC) using tumor volume (TV) and other prognostic factors.

Methods:

This study included 1309 cases. The TV and greatest tumor diameter (GTD) were semi-automatically measured. The receiver operating characteristic (ROC) curves of TV and GTD were used to predict survival. The regression analysis was used to describe the correlation between GTD and TV. Overall survival (OS) was analyzed using the Kaplan-Meier method. Cox’s proportional hazards regression model was applied for multivariate analysis.

Results:

Using the OS in pN0M0 patients (997 cases), we obtained 4 optimal cutoff values and divided all cases into 5 TV groups (V1: TV ≤ 2.80 cm³; V2: TV > 2.80–6.40 cm³; V3: TV > 6.40–12.9 cm³; V4: TV > 12.9–55.01 cm³; V5: TV > 55.01 cm³) with significant OS (P < 0.001). Multivariate analysis showed that age, visceral pleural invasion (VPI), and all TV cutoff points were independent factors of OS (P < 0.05). For V3 and V4 groups, the OS in patients without VPI was better than that in patients with VPI. Using the values of TV, VPI, and N stages, we classified all cases into 5 stages from I to V depending on the OS. The OS in I, II, III, IV, and V stages were 71.3%, 65.5%, 59.8%, 47.7%, and 35.1% respectively (P < 0.001).

Conclusions:

We proposed a new T staging system using TV as the main prognostic descriptor in NSCLC patients, which may provide a better comprehensive clinical value than GTD in clinical applications.

The effect of systemic inflammation indexes and 18FDG PET metabolic parameters on survival in advanced lung adenocarcinoma

OBJECTIVE

To determine the effect of systemic inflammation indexes and fluorine-18 fluorodeoxyglucose (¹⁸FDG) positron emission tomography (PET) metabolic parameters on survival in advanced lung adenocarcinoma.

METHODS

A total of 133 patients who underwent ¹⁸FDG PET for initial staging were investigated retrospectively. Baseline patient characteristics, routine blood test results, ¹⁸FDG PET metabolic parameters, and treatment history were examined. Overall survival (OS) was demonstrated by Kaplan-Meier analysis, and the curves were compared by the log-rank test. Systemic inflammation response index (SIRI) was defined as neutrophil x monocyte/lymphocyte count.

RESULTS

Lymphocyte/monocyte ratio (LMR) and SIRI were found to be significant for OS. The cutoff point was 2.25 for LMR. Median OS was 8 months for ⩽2.25 and 14 months for >2.25 (p = 0.005). For SIRI, the cutoff point was 2. SIRI ⩽2 was associated with a median OS of 16 months compared to 10 months for patients with SIRI >2 (p = 0.043). Maximum of standardized uptake value, total lesion glycolysis, and metabolic tumor volume were not found to be significant for OS (p = 0.225, p = 0.061, p = 0.355, respectively). No correlation was found between inflammatory indexes and PET metabolic parameters.

CONCLUSION

Age and LMR parameters were prognostic for survival in Cox regression analysis. There was no correlation between ¹⁸FDG PET parameters and inflammatory indexes.

Comparison of different images in gross target volume delineating on VX2 nasopharyngeal transplantation tumor models

Background: To determine the optimum conditions for diagnosis of nasopharyngeal carcinoma, we established VX2 rabbit model to delineate gross target volume (GTV) in different imaging methods. Methods: The orthotopic nasopharyngeal carcinoma (NPC) was established in sixteen New Zealand rabbits. After 7-days inoculation, the rabbits were examined by CT scanning and then sacrificed for pathological examination. To achieve the best delineation, different GTVs of CT, MRI, ¹⁸F-FDG PET/CT, and ¹⁸F-FLT PET/CT images were correlated with pathological GTV (GTVp). Results: We found 45% and 60% of the maximum standardized uptake value (SUV_max) as the optimal SUV threshold for the target volume of NPC in ¹⁸F-FDG PET/CT and ¹⁸F-FLT PET/CT images, respectively (GTV_FDG45% and GTV_FLT60%). Moreover, the GTV_MRI and GTV_CT were significantly higher than the GTVp (P ≤ 0.05), while the GTV_FDG45% and especially GTV_FLT60% were similar to the GTVp (R = 0.892 and R = 0.902, respectively; P ≤ 0.001). Conclusions: Notably, the results suggested that ¹⁸F-FLT PET/CT could reflect the tumor boundaries more accurately than ¹⁸F-FDG PET/CT, MRI and CT, which makes ¹⁸F-FLT PET-CT more advantageous for the clinical delineation of the target volume in NPC.

Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions.

Prognostic value of metabolic tumour volume and total lesion glycolysis measured by 18F-fluorodeoxyglucose positron emission tomography/computed tomography in small cell lung cancer: A systematic review and meta-analysis

The aim of this study was to evaluate the prognostic value of metabolic tumour volume (MTV) and total lesion glycolysis (TLG) for small cell lung cancer (SCLC). MEDLINE, EMBASE and Cochrane Library databases were systematically searched. The pooled hazard ratio (HR) was used to measure the influence of MTV and TLG on survival. The subgroup analysis according to VALSG stage and the measured extent of MTV was performed. Patients with high MTV values experienced a significantly poorer prognosis with a HR of 2.42 (95% CI 1.46-4.03) for overall survival (OS) and a HR of 2.78 (95% CI 1.39-5.53) for progression-free survival (PFS) from the random effect model, and the pooled HR from the fixed effect model was 2.10 (95% CI 1.77-2.50) for OS and 2.27 (95% CI 1.83-2.81) for PFS. Patients with high TLG experienced a poorer prognosis with a HR of 1.61 (95% CI: 1.24-2.07) for OS from the random effect model, and the pooled HR from the fixed effect model was 1.64 (95% CI 1.37-1.96). Heterogeneity among studies was high for MTV in both OS and PFS meta-analyses (I²  = 87% and 88% respectively). After removing one outlier study the heterogeneity was substantially reduced (I²  = 0%) and the pooled HR for the effect of MTV on OS was 1.80 (1.51-2.16, P < 0.00001), and on PFS it was 1.86 (1.49-2.33, P < 0.00001), using either the fixed or random effects model. High MTV is associated with a significantly poorer prognosis OS and PFS, and high TLG is associated with a significantly poorer prognosis regarding OS for SCLC.

Correlation of quantified metabolic activity in nonsmall cell lung cancer with tumor size and tumor pathological characteristics

The aim of this study was to evaluate the relationship between maximum standardized uptake value (SUVmax) with tumor size and tumor pathological characteristics as well as suggesting equations between SUVmax and tumor size in patients with nonsmall cell lung cancer (NSCLC) to help differentiate between pathology types.We retrospectively analyzed the fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) findings of 98 patients with NSCLC. Statistical differences were considered significant when P < .05. Correlation between SUVmax and other variables was determined by Pearson and Spearman correlation. Both linear and nonlinear regression analysis were used to determine equations between SUVmax and tumor size to help differentiate between pathology types.The mean SUVmax in patients with squamous cell carcinoma was significantly higher than that of adenocarcinoma (21.35 ± 1.73 vs 13.75 ± 0.89, P = .000). The results of regression analysis indicated that among all equations determined with relative accuracy, the "cubic equation" has the highest accuracy when considering the relationship between SUVmax and tumor size in patients with adenocarcinoma. In patients with squamous cell carcinoma, the most accurate equation was obtained using the "quadratic equation."There was a significant correlation between SUVmax and tumor differentiation and tumor size in patients with adenocarcinoma. SUVmax of patients with squamous cell carcinoma also had a significant correlation with tumor size. Overall SUVmax of patients with NSCLC could be predicted by tumor size value. In patients with squamous cell carcinoma compared with those with adenocarcinoma, SUVmax with less accuracy can be determined by tumor size. Linear regression analysis line slope can be used as an index for distinguishing adenocarcinoma from squamous cell carcinoma.

Radiomics in Oncological PET/CT: Clinical Applications

18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is widely used for staging, evaluating treatment response, and predicting prognosis in malignant diseases. FDG uptake and volumetric PET parameters such as metabolic tumor volume have been used and are still used as conventional PET parameters to assess biological characteristics of tumors. However, in recent years, additional features derived from PET images by computational processing have been found to reflect intratumoral heterogeneity, which is related to biological tumor features, and to provide additional predictive and prognostic information, which leads to the concept of radiomics. In this review, we focus on recent clinical studies of malignant diseases that investigated intratumoral heterogeneity on PET/CT, and we discuss its clinical role in various cancers.

The prognostic value of volume-based parameters using 18F-FDG PET/CT in gastric cancer according to HER2 status

BACKGROUND

We aimed to find the clinical value of metastatic tumor burden evaluated with F18-FDG PET/CT in gastric cancer patients, considering the human epidermal growth factor receptor 2 (HER2) status.

METHODS

We retrospectively reviewed 124 patients with locally advanced or metastatic gastric cancer at Yonsei Cancer Center between January 2006 and December 2014 who had undergone baseline FDG PET/CT before first-line chemotherapy. We measured the maximum standardized uptake value from the primary tumor (SUV_max) and whole-body (WB) PET/CT parameters, including WB SUV_max, WB SUV_mean, WB metabolic tumor volume (WB MTV), and WB total lesion glycolysis (WB TLG), in all metabolically active metastatic lesions (SUV threshold ≥2.5 or 40% isocontour for ≤2.5), and we determined their association with patient survival outcomes.

RESULTS

SUV_max was higher in HER2-positive gastric cancers (median 12.1, range 3.4-34.6) compared to HER-2 negative (7.4, 1.6-39.1, P < 0.001). Among all patients, WB TLG > 600, which is indicative of a high metastatic tumor burden, showed worse progression-free survival (PFS) [hazard ratio (HR), 2.003; 95% CI, 1.300-3.086; P = 0.002] and overall survival (OS) (HR, 3.001; 95% CI, 1.950-4.618; P < 0.001) than did WB TLG ≤ 600. Among HER2-positive gastric cancer patients treated with trastuzumab, higher metabolic tumor burden predicted worse OS, but not PFS.

CONCLUSIONS

HER2-positive gastric cancers had higher SUV_max compared to HER2-negative gastric cancers. In both HER2-negative patients and -positive patients receiving trastuzumab, FDG PET/CT volume-based parameters may have a role in further stratifying the prognosis of stage IV gastric cancer.

Implications of KRAS mutations in acquired resistance to treatment in NSCLC

Rationale

KRAS is the most common and, simultaneously, the most ambiguous oncogene implicated in human cancer. Despite KRAS mutations were identified in Non Small Cell Lung Cancers (NSCLCs) more than 20 years ago, selective and specific inhibitors aimed at directly abrogating KRAS activity are not yet available. Nevertheless, many therapeutic approaches have been developed potentially useful to treat NSCLC patients mutated for KRAS and refractory to both standard chemotherapy and targeted therapies.

The focus of this review will be to provide an overview of the network related to the intricate molecular KRAS pathways, stressing on preclinical and clinical studies that investigate the predictive value of KRAS mutations in NSCLC patients.

Materials and Methods

A bibliographic search of the Medline database was conducted for articles published in English, with the keywords KRAS, KRAS mutations in non-small cell lung cancer, KRAS and tumorigenesis, KRAS and TKIs, KRAS and chemotherapy, KRAS and monoclonal antibody, KRAS and immunotherapy, KRAS and drugs, KRAS and drug resistance.

Metabolic tumor burden quantified on [18F]FDG PET/CT improves TNM staging of lung cancer patients

PURPOSE

The purpose of our study was to test a new staging algorithm, combining clinical TNM staging (cTNM) with whole-body metabolic active tumor volume (MATV-WB), with the goal of improving prognostic ability and stratification power.

METHODS

Initial staging [¹⁸F]FDG PET/CT of 278 non-small cell lung cancer (NSCLC) patients, performed between January/2011 and April/2016, 74(26.6%) women, 204(73.4%) men; aged 34-88 years (mean ± SD:66 ± 10), was retrospectively evaluated, and MATV-WB was quantified. Each patient's follow-up time was recorded: 0.7-83.6 months (mean ± SD:25.1 ± 20.3).

RESULTS

MATV-WB was an independent and statistically-significant predictor of overall survival (p < 0.001). The overall survival predictive ability of MATV-WB (C index: mean ± SD = 0.7071 ± 0.0009) was not worse than cTNM (C index: mean ± SD = 0.7031 ± 0.007) (Z = -0.143, p = 0.773). Estimated mean survival times of 56.3 ± 3.0 (95%CI:50.40-62.23) and 21.7 ± 2.2 months (95%CI:17.34-25.98) (Log-Rank = 77.48, p < 0.001), one-year survival rate of 86.8% and of 52.8%, and five-year survival rate of 53.6% and no survivors, were determined, respectively, for patients with MATV-WB < 49.5 and MATV-WB ≥ 49.5. Patients with MATV-WB ≥ 49.5 had a mortality risk 2.9-5.8 times higher than those with MATV-WB < 49.5 (HR = 4.12, p < 0.001). MATV-WB cutoff points were also determined for each cTNM stage: 23.7(I), 49.5(II), 52(III), 48.8(IV) (p = 0.029, p = 0.227, p = 0.025 and p = 0.001, respectively). At stages I, III and IV there was a statistically-significant difference in the estimated mean overall survival time between groups of patients defined by the cutoff points (p = 0.007, p = 0.004 and p < 0.001, respectively). At stage II (p = 0.365), there was a clinically-significant difference of about 12 months between the groups. In all cTNM stages, patients with MATV-WB ≥ cutoff points had lower survival rates. Combined clinical TNM-PET staging (cTNM-P) was then tested: Stage I < 23.7; Stage I ≥ 23.7; Stage II < 49.5; Stage II ≥ 49.5; Stage III < 52; Stage III ≥ 52; Stage IV < 48.8; Stage IV ≥ 48.8. cTNM-P staging presented a superior overall survival predictive ability (C index = 0.730) compared with conventional cTNM staging (C index = 0.699) (Z = -4.49, p < 0.001).

CONCLUSION

cTNM-P staging has superior prognostic value compared with conventional cTNM staging, and allows better stratification of NSCLC patients.

Volumetric parameters on FDG PET can predict early intrahepatic recurrence-free survival in patients with hepatocellular carcinoma after curative surgical resection

PURPOSE

This study assessed the prognostic values of volumetric parameters on ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in predicting early intrahepatic recurrence-free survival (RFS) after curative resection in patients with hepatocellular carcinoma (HCC).

METHODS

A retrospective analysis was performed on 242 patients with HCC who underwent staging FDG PET and subsequent curative surgical resection. The tumor-to-non-tumorous liver uptake ratio, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the HCC lesions on PET were measured. The prognostic values of clinical factors and PET parameters for predicting overall RFS, overall survival (OS), extrahepatic RFS, and early and late intrahepatic RFS were assessed.

RESULTS

The median follow-up period was 54.7 months, during which 110 patients (45.5%) experienced HCC recurrence and 62 (25.6%) died. Patients with extrahepatic and early intrahepatic recurrence showed worse OS than did those with no recurrence or late intrahepatic recurrence (p < 0.001). Serum bilirubin level, MTV, and TLG were independent prognostic factors for overall RFS and OS (p < 0.05). Only MTV and TLG were prognostic for extrahepatic RFS (p < 0.05). Serum alpha-fetoprotein and bilirubin levels, MTV, and TLG were prognostic for early intrahepatic RFS (p < 0.05) and hepatitis C virus (HCV) positivity and serum albumin level were independently prognostic for late intrahepatic RFS (p < 0.05).

CONCLUSION

Intrahepatic recurrence showed different prognoses according to the time interval of recurrence in which early recurrence had as poor survival as extrahepatic recurrence. MTV and TLG on initial staging PET were significant independent factors for predicting early intrahepatic and extrahepatic RFS in patients with HCC after curative resection. Only HCV positivity and serum albumin level were significant for late intrahepatic RFS, which is mainly attributable to the de novo formation of new primary HCC.

The role of 18F-fluorodeoxyglucose uptake of bone marrow on PET/CT in predicting clinical outcomes in non-small cell lung cancer patients treated with chemoradiotherapy

OBJECTIVES

This study aimed to assess the relationship between bone marrow (BM) FDG uptake on PET/CT and serum inflammatory markers and to evaluate the prognostic value of BM FDG uptake for predicting clinical outcomes in non-small cell lung cancer (NSCLC) patients.

METHODS

One hundred and six NSCLC patients who underwent FDG PET/CT for staging work-up and received chemoradiotherapy were enrolled. Mean BM FDG uptake (BM SUV) and BM-to-liver uptake ratio (BLR) were measured, along with volumetric parameters of PET/CT. The relationship of BM SUV and BLR with hematologic parameters and serum inflammatory markers was evaluated. Prognostic values of BM SUV and BLR for predicting progression-free survival (PFS) and overall survival (OS) were assessed.

RESULTS

BM SUV and BLR were significantly correlated with white blood cell count and C-reactive protein level. On univariate analysis, BLR was a significant prognostic factor for both PFS and OS. On multivariate analysis, TNM stage and BLR were independent prognostic factors for PFS, and only TNM stage was an independent prognostic factor for OS.

CONCLUSIONS

In NSCLC patients, FDG uptake of BM reflects the systemic inflammatory response and can be used as a biomarker to identify patients with poor prognosis.

KEY POINTS

• Bone marrow FDG uptake is correlated with serum inflammatory markers. • Bone marrow FDG uptake is an independent prognostic factor for progression-free survival. • Bone marrow FDG uptake can provide information on predicting lung cancer progression.