Metabolic parameters using ¹⁸F-FDG PET/CT correlate with occult lymph node metastasis in squamous cell lung carcinoma

A clinical nomogram for predicting occult lymph node metastasis in patients with non-small-cell lung cancer ≤2 cm

OBJECTIVES

Sublobar resection has been shown to be feasible for non-small-cell lung cancers (NSCLC) <2 cm in size based on several prospective studies. However, the prognosis of clinical N0 patients who experience an N-stage upgrade after surgery [known as occult lymph node metastasis (OLM)] may be worse. The ability of predict OLM in patients eligible for sublobar resection remains a controversial issue.

METHODS

Patients with NSCLC ≤2 cm in diameter and containing a solid component who underwent surgical treatment at the Affiliated Hospital of Qingdao University were retrospectively enrolled, and 1:1 case matching was performed. The risk factors were identified through logistic regression analyses and theoretical criteria, followed by the development of a nomogram that was evaluated using 200 iterations of 10-fold cross-validation.

RESULTS

After case matching, 130 pairs of patients were selected for modelling. According to the multivariable logistic regression analysis, the carcinoembryonic antigen level, consolidation tumour ratio, mean computed tomography number and tumour margin were included in the nomogram. The cross-validated average area under the receiver operating characteristic curve was found to be 0.86. Furthermore, calibration curve and decision curve analyses demonstrated the excellent predictive accuracy and clinical utility of the nomogram respectively.

CONCLUSIONS

By utilizing accessible characteristics, we developed a nomogram that predicts the probability of OLM in patients with NSCLC ≤2 cm with a solid component. Risk stratification with this nomogram could aid in surgical method decision-making.

CLINICAL REGISTRATION NUMBER

Not applicable.

PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer

Occult nodal metastasis (ONM) plays a significant role in comprehensive treatments of non-small cell lung cancer (NSCLC). This study aims to develop a deep learning signature based on positron emission tomography/computed tomography to predict ONM of clinical stage N0 NSCLC. An internal cohort (n = 1911) is included to construct the deep learning nodal metastasis signature (DLNMS). Subsequently, an external cohort (n = 355) and a prospective cohort (n = 999) are utilized to fully validate the predictive performances of the DLNMS. Here, we show areas under the receiver operating characteristic curve of the DLNMS for occult N1 prediction are 0.958, 0.879 and 0.914 in the validation set, external cohort and prospective cohort, respectively, and for occult N2 prediction are 0.942, 0.875 and 0.919, respectively, which are significantly better than the single-modal deep learning models, clinical model and physicians. This study demonstrates that the DLNMS harbors the potential to predict ONM of clinical stage N0 NSCLC.

Additional Value of PET and CT Image-Based Features in the Detection of Occult Lymph Node Metastases in Lung Cancer: A Systematic Review of the Literature

Lung cancer represents the second most common malignancy worldwide and lymph node (LN) involvement serves as a crucial prognostic factor for tailoring treatment approaches. Invasive methods, such as mediastinoscopy and endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), are employed for preoperative LN staging. Among the preoperative non-invasive diagnostic methods, computed tomography (CT) and, recently, positron emission tomography (PET)/CT with fluorine-18-fludeoxyglucose ([¹⁸F]FDG) are routinely recommended by several guidelines; however, they can both miss pathologically proven LN metastases, with an incidence up to 26% for patients staged with [¹⁸F]FDG PET/CT. These undetected metastases, known as occult LN metastases (OLMs), are usually cases of micro-metastasis or small LN metastasis (shortest radius below 10 mm). Hence, it is crucial to find novel approaches to increase their discovery rate. Radiomics is an emerging field that seeks to uncover and quantify the concealed information present in biomedical images by utilising machine or deep learning approaches. The extracted features can be integrated into predictive models, as numerous reports have emphasised their usefulness in the staging of lung cancer. However, there is a paucity of studies examining the detection of OLMs using quantitative features derived from images. Hence, the objective of this review was to investigate the potential application of PET- and/or CT-derived quantitative radiomic features for the identification of OLMs.

Preoperative PET-SUVmax and volume based PET parameters of the primary tumor fail to predict nodal upstaging in early-stage lung cancer

OBJECTIVES

Accurate nodal staging is of utmost importance in patients with lung cancer. FDG-PET/CT imaging is now part of the routine staging. Despite thorough preoperative staging nodal upstaging still occurs in early-stage lung cancer. However, the predictive value of preoperative PET metrics of the primary tumor on nodal upstaging remains to be unexplored. Our aim was to assess the association of these preoperative PET-parameters with nodal upstaging in histologically confirmed lung adenocarcinoma and squamous cell carcinoma.

METHODS

From January 2016 to November 2018, 500 patients with pT1-T2/cN0 lung cancer received an anatomical resection with curative intent. 171 patients with adenocarcinoma and squamous cell carcinoma and available PET-CTs were retrospectively included. We analyzed the the association of nodal upstaging with preoperative PET-SUVmax and metabolic PET metrics including total lesion glycolysis (TLG) and metabolic tumor volume (MTV) with different defined thresholds.

RESULTS

High values of preoperative PET-SUVmax of the primary tumor were associated with squamous cell carcinoma (p < 0.0001) and with larger tumors (p < 0.0001). Increased preoperative C-reactive protein levels (<1mg/dL) correlated significantly with high preoperative PET-SUVmax values (p < 0.0001). No significant relationship between PET-SUVmax and lactate dehydrogenase activity (p = 0.6818), white blood cell count (p = 0.7681), gender (p = 0.1115) or age (p = 0.9284) was observed. Nodal upstaging rate was 14.0 % with 8.8 % N1 and 5.3 % N2 upstaging. Tumor size (p = 0.0468) and number of removed lymph nodes (p = 0.0461) were significant predictors of nodal upstaging but no significant association was found with histology or PET parameters. Of note, increased MTV - regardless of the threshold - tended to associate with nodal upstaging.

CONCLUSION

Early-stage lung cancer patients with squamous histology and T2 tumors presented increased preoperative PET-SUVmax values. Nevertheless, beyond tumor size and number of removed lymph nodes neither SUVmax nor metabolic PET parameters MTV and TLG were significant predictors of nodal upstaging.

18F-FDG PET/CT radiomics nomogram for predicting occult lymph node metastasis of non-small cell lung cancer

Purpose

To investigate the ability of a PET/CT-based radiomics nomogram to predict occult lymph node metastasis in patients with clinical stage N0 non-small cell lung cancer (NSCLC).

Materials and methods

This retrospective study included 228 patients with surgically confirmed NSCLC (training set, 159 patients; testing set, 69 patients). ITKsnap3.8.0 was used for image(CT and PET images) segmentation, AK version 3.2.0 was used for radiomics feature extraction, and Python3.7.0 was used for radiomics feature screening. A radiomics model for predicting occult lymph node metastasis was established using a logistic regression algorithm. A nomogram was constructed by combining radiomics scores with selected clinical predictors. Receiver operating characteristic (ROC) curves were used to verify the performance of the radiomics model and nomogram in the training and testing sets.

Results

The radiomics nomogram comprising six selected features achieved good prediction efficiency, including radiomics characteristics and tumor location information (central or peripheral), which demonstrated good calibration and discrimination ability in the training (area under the ROC curve [AUC] = 0.884, 95% confidence interval [CI]: 0.826-0.941) and testing (AUC = 0.881, 95% CI: 0.8031-0.959) sets. Clinical decision curves demonstrated that the nomogram was clinically useful.

Conclusion

The PET/CT-based radiomics nomogram is a noninvasive tool for predicting occult lymph node metastasis in NSCLC.

PET/CT for Predicting Occult Lymph Node Metastasis in Gastric Cancer

A portion of gastric cancer patients with negative lymph node metastasis at an early stage eventually die from tumor recurrence or advanced metastasis. Occult lymph node metastasis (OLNM] is a potential risk factor for the recurrence and metastasis in these patients, and it is highly important for clinical prognosis. Positron emission tomography (PET)/computed tomography (CT) is used to assess lymph node metastasis in gastric cancer due to its advantages in anatomical and functional imaging and non-invasive nature. Among the major metabolic parameters of PET, the maximum standardized uptake value (SUVmax) is commonly used for examining lymph node status. However, SUVmax is susceptible to interference by a variety of factors. In recent years, the exploration of new PET metabolic parameters, new PET imaging agents and radiomics, has become an active research topic. This paper aims to explore the feasibility and predict the effectiveness of using PET/CT to detect OLNM. The current landscape and future trends of primary metabolic parameters and new imaging agents of PET are reviewed. For gastric cancer patients, the possibility to detect OLNM non-invasively will help guide surgeons to choose the appropriate lymph node dissection area, thereby reducing unnecessary dissections and providing more reasonable, personalized and comprehensive treatments.

[18F]FDG-PET/CT radiomics and artificial intelligence in lung cancer: Technical aspects and potential clinical applications

Lung cancer is the second most common cancer and the leading cause of cancer-related death worldwide. Molecular imaging using [¹⁸F]fluorodeoxyglucose Positron Emission Tomography and/or Computed Tomography ([¹⁸F]FDG-PET/CT) plays an essential role in the diagnosis, evaluation of response to treatment, and prediction of outcomes. The images are evaluated using qualitative and conventional quantitative indices. However, there is far more information embedded in the images, which can be extracted by sophisticated algorithms. Recently, the concept of uncovering and analyzing the invisible data extracted from medical images, called radiomics, is gaining more attention. Currently, [¹⁸F]FDG-PET/CT radiomics is growingly evaluated in lung cancer to discover if it enhances the diagnostic performance or implication of [¹⁸F]FDG-PET/CT in the management of lung cancer. In this review, we provide a short overview of the technical aspects, as they are discussed in different articles of this special issue. We mainly focus on the diagnostic performance of the [¹⁸F]FDG-PET/CT-based radiomics and the role of artificial intelligence in non-small cell lung cancer, impacting the early detection, staging, prediction of tumor subtypes, biomarkers, and patient's outcomes.

New PET/CT criterion for predicting lymph node metastasis in resectable advanced (stage IB-III) lung cancer: The standard uptake values ratio of ipsilateral/contralateral hilar nodes

Background

The aim of the present study was to use surgical and histological results to develop a simple noninvasive technique to improve nodal staging using preoperative PET/CT in patients with resectable lung cancer.

Methods

Preoperative PET/CT findings (pStage IB–III 182 patients) and pathological diagnoses after surgical resection were evaluated. Using PET/CT images to determine the standardized uptake value (SUV) ratio, the SUV_max of a contralateral hilar lymph node (on the side of the chest opposite to the primary tumor) was measured simultaneously. The I/C‐SUV ratio was calculated as ipsilateral hilar node SUV/contralateral hilar node SUV. Receiver operating characteristic (ROC) curves were then used to analyze those data.

Results

Based on ROC analyses, the cutoff I/C‐SUV ratio for diagnosis of lymph node metastasis was 1.34. With a tumor ipsilateral lymph node SUV_max ≥2.5, an IC‐SUV ratio ≥1.34 had the highest accuracy for predicting N1/N2 metastasis; the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of nodal staging were 60.66, 85.11, 84.09, 62.5 and 71.29%, respectively.

Conclusions

When diagnosing nodal stage, a lymph node I/C‐SUV ratio ≥1.34 can be an effective criterion for determining surgical indications in advanced lung cancer.

A Radiomics Nomogram for Preoperative Prediction of Clinical Occult Lymph Node Metastasis in cT1-2N0M0 Solid Lung Adenocarcinoma

Background

Clinical occult lymph node metastasis (cOLNM) means that the lymph node is negatively diagnosed by preoperative computed tomography (CT), but has been proven to be positive by postoperative pathology. The aim of this study was to establish and validate a nomogram based on radiomics features for the preoperative prediction of cOLNM in early-stage solid lung adenocarcinoma patients.

Methods

A total of 244 patients with clinical T1-2N0M0 solid lung adenocarcinoma who underwent preoperative contrast-enhanced chest CT were divided into a primary group (n = 160) and an independent validation group from another hospital (n = 84). The records of 851 radiomics features of each primary tumor were extracted. LASSO analysis was used to reduce the data dimensionality and select features. Multivariable logistic regression was utilized to identify independent predictors of cOLNM and develop a predictive nomogram. The performance of the predictive model was assessed by its calibration and discrimination. Decision curve analysis (DCA) was performed to estimate the clinical usefulness of the nomogram.

Results

The predictive model consisted of a clinical factor (CT-reported tumor size) and a radiomics feature (Rad-score). The nomogram presented good discrimination, with a C-index of 0.782 (95% CI, 0.768–0.796) in the primary cohort and 0.813 (95% CI, 0.787–0.839) in the validation cohort, and good calibration. DCA showed that the radiomics nomogram was clinically useful.

Conclusion

This study develops and validates a nomogram that incorporates clinical and radiomics factors. It can be tailored for the individualized preoperative prediction of cOLNM in early-stage solid lung adenocarcinoma patients.

The metabolic parameters based on volume in PET/CT are associated with clinicopathological N stage of colorectal cancer and can predict prognosis

Background

A combination of positron emission tomography and computed tomography (PET/CT) is an important modality for the diagnosis of carcinoma. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have been reported as metabolic parameters in PET/CT since the late 1990s, and they are expected to be useful in diagnosing diverse cancers and as prognostic biomarkers. We evaluated the potential of these parameters in the prognosis of colorectal cancer (CRC) by comparing them with conventional parameters, including the maximum standardized uptake value (SUVmax). We enrolled 84 patients who underwent surgery for CRC without distal metastasis between April 2015 and April 2019. SUVmax, MTV, and TLG were measured by ¹⁸F-fluorodeoxyglucose (FDG)-PET/CT. To find an optimal threshold value related to prognosis, the volume of interest in the primary carcinoma was measured at fixed relative and absolute thresholds based on SUVmax (30%, 40%, and 50%; 2.5, 3.0, and 3.5, respectively), tumor-to-liver standardized uptake ratios, TLR (1.0, 1.5, and 2.0), and SUV normalized to lean body mass, SUL (2.0, 2.5, and 3.0). After classifying the patients into two groups according to pathological N stage, the optimal threshold values of all metabolic parameters were compared between groups using a non-parametric comparison test.

Result

The most suitable thresholds for MTV were a SUVmax of 3.5 and a TLR 2.0. TLG with a SUVmax value of 40% showed the most significant difference. The MTV standard uptake ratio of 2.0 was significantly associated with pathological N stage.

Conclusion

Our results suggest that an MTV TLR 2.0 on PET/CT reflects pathological N stage in local patients with CRC.

Diagnostic utility of metabolic parameters on FDG PET/CT for lymph node metastasis in patients with cN2 non-small cell lung cancer

Background

The aim of this study was to assess the diagnostic utility of metabolic parameters on fluorine-18-fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET)/computed tomography (CT) for predicting lymph node (LN) metastasis in patients with cN2 non-small cell lung cancer (NSCLC).

Methods

We retrospectively reviewed patients who underwent surgery for cN2 NSCLC between 2007 and 2020. Those who had clinically diagnosed positive hilar and mediastinal LNs by routine CT and PET/CT imaging were investigated. To measure the metabolic parameters of LNs, the data according to maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and LN-to-primary tumor ratio of SUVmax (LPR) were examined. The diagnosis of each retrieved LN was confirmed based on histopathological examination of surgical tissue specimens. Receiver operating characteristics (ROC) curves with area under the curve (AUC) calculations and multivariate analysis by logistic regression were performed.

Results

Forty-five patients with 84 clinically diagnosed positive hilar or mediastinal LNs were enrolled in the present study. Of the 84 LNs, 63 LNs were pathologically proven as positive (75%). The SUVmax, MTV, TLG, and LPR of LN metastasis were significantly higher than those of benign nodes. In the ROC analysis, the AUC value of LPR [AUC, 0.776; 95% confidence interval (CI), 0.640–0.913] was higher than that of LN SUVmax (AUC, 0.753; 95% CI, 0.626–0.880) or LN TLG3.5 (AUC, 0.746; 95% CI, 0.607–0.885). Using the optimal LPR cutoff value of 0.47, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 84.1, 66.7, 88.3, 58.3, and 79.8%, respectively. Multivariate analysis by logistic regression showed that LPR was an independent predictor for LN metastasis (odds ratio, 6.45; 95% CI, 1.785–23.301; P = 0.004). In the subgroup analysis of adenocarcinoma patients (n = 18; 32 LNs), TLG3.5 was a better predictor (AUC, 0.816; 95% CI, 0.639–0.985) than LPR (AUC, 0.792; 95% CI, 0.599–0.986) or LN SUVmax (AUC, 0.792; 95% CI, 0.625–0.959).

Conclusions

Our findings suggest that LPR on FDG-PET is a useful predictor for LN metastasis in patients with cN2 NSCLC. TLG can be a good predictor for LN metastasis in patients with adenocarcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08688-6.

Prediction Model for Tumor Budding Status Using the Radiomic Features of F-18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Cervical Cancer

OBJECTIVE

To compare the radiomic features of F-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and intratumoral heterogeneity according to tumor budding (TB) status and to develop a prediction model for the TB status using the radiomic feature of 18F-FDG PET/CT in patients with cervical cancer.

MATERIALS AND METHODS

Seventy-six patients with cervical cancer who underwent radical hysterectomy and preoperative 18F-FDG PET/CT were included. We assessed the status of intratumoral budding (ITP) and peritumoral budding (PTB) in all available hematoxylin and eosin-stained specimens. Three conventional metabolic parameters and fifty-nine features were extracted and analyzed. Univariate analysis was used to identify significant metabolic parameters and radiomic findings for TB status. The prediction model for TB status was built using 3 machine learning classifiers (random forest, support vector machine, and neural network).

RESULTS

Univariate analysis led to the identification of 2 significant metabolic parameters and 12 significant radiomic features according to intratumoral budding (ITB) status. Among these parameters, following multivariate analysis for the ITB status, only compacity remained significant (odds ratio, 5.0047; 95% confidence interval, 1.1636-21.5253; p = 0.0305). Two conventional metabolic parameters and 25 radiomic features were selected by the Lasso regularization, and the prediction model for the ITB status had a mean area under the curve of 0.762 in the test dataset.

CONCLUSION

Radiomic features of 18F-FDG PET/CT were associated with the ITB status. The prediction model using radiomic features successfully predicted the TB status in patients with cervical cancer. The prediction models for the ITB status may contribute to personalized medicine in the management of patients with cervical cancer.

Pre-Operative Prediction of Mediastinal Node Metastasis Using Radiomics Model Based on 18F-FDG PET/CT of the Primary Tumor in Non-Small Cell Lung Cancer Patients

Purpose: We investigated whether a fluorine-18-fluorodeoxy glucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT)-based radiomics model (RM) could predict the pathological mediastinal lymph node staging (pN staging) in patients with non-small cell lung cancer (NSCLC) undergoing surgery.

Methods: A total of 716 patients with a clinicopathological diagnosis of NSCLC were included in this retrospective study. The prediction model was developed in a training cohort that consisted of 501 patients. Radiomics features were extracted from the ¹⁸F-FDG PET/CT of the primary tumor. Support vector machine and extremely randomized trees were used to build the RM. Internal validation was assessed. An independent testing cohort contained the remaining 215 patients. The performances of the RM and clinical node staging (cN staging) in predicting pN staging (pN0 vs. pN1 and N2) were compared for each cohort. The area under the curve (AUC) of the receiver operating characteristic curve was applied to assess the model's performance.

Results: The AUC of the RM [0.81 (95% CI, 0.771–0.848); sensitivity: 0.794; specificity: 0.704] for the predictive performance of pN1 and N2 was significantly better than that of cN in the training cohort [0.685 (95% CI, 0.644–0.728); sensitivity: 0.804; specificity: 0.568], (P-value = 8.29e-07, as assessed by the Delong test). In the testing cohort, the AUC of the RM [0.766 (95% CI, 0.702–0.830); sensitivity: 0.688; specificity: 0.704] was also significantly higher than that of cN [0.685 (95% CI, 0.619–0.747); sensitivity: 0.799; specificity: 0.568], (P = 0.0371, Delong test).

Conclusions: The RM based on ¹⁸F-FDG PET/CT has a potential for the pN staging in patients with NSCLC, suggesting that therapeutic planning could be tailored according to the predictions.

Prognostic Value of Combing Primary Tumor and Nodal Glycolytic-Volumetric Parameters of 18F-FDG PET in Patients with Non-Small Cell Lung Cancer and Regional Lymph Node Metastasis

We investigated whether the combination of primary tumor and nodal ¹⁸F-FDG PET parameters predict survival outcomes in patients with nodal metastatic non-small cell lung cancer (NSCLC) without distant metastasis. We retrospectively extracted pre-treatment ¹⁸F-FDG PET parameters from 89 nodal-positive NSCLC patients (stage IIB–IIIC). The Cox proportional hazard model was used to identify independent prognosticators of overall survival (OS) and progression-free survival (PFS). We devised survival stratification models based on the independent prognosticators and compared the model to the American Joint Committee on Cancer (AJCC) staging system using Harrell’s concordance index (c-index). Our results demonstrated that total TLG (the combination of primary tumor and nodal total lesion glycolysis) and age were independent risk factors for unfavorable OS (p < 0.001 and p = 0.001) and PFS (both p < 0.001), while the Eastern Cooperative Oncology Group scale independently predicted poor OS (p = 0.022). Our models based on the independent prognosticators outperformed the AJCC staging system (c-index = 0.732 versus 0.544 for OS and c-index = 0.672 versus 0.521 for PFS, both p < 0.001). Our results indicate that incorporating total TLG with clinical factors may refine risk stratification in nodal metastatic NSCLC patients and may facilitate tailored therapeutic strategies in this patient group.

18F-FDG PET/CT and circulating tumor cells in treatment-naive patients with non-small-cell lung cancer

PURPOSE

This study retrospectively investigated the clinical utility of 2-deoxy-18F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) and circulating tumor cells (CTCs) in the diagnosis and prognosis of treatment-naive patients with non-small-cell lung cancer (NSCLC).

METHODS

The blood samples of treatment-naive patients with NSCLC were collected for CTCs detection, and the tumor metabolic parameters of ¹⁸F-FDG PET/CT, including maximum standard uptake value (SUVmax), metabolic tumor volume of primary lesion (MTV-P) and combination of primary lesion and metastases (MTV-C), and total lesion glycolysis of primary lesion (TLG-P) and combination of primary lesion and metastases (TLG-C), were analyzed. Age, sex, smoking, serum tumor markers, tumor size, location, TNM stage, and genetic mutations were also reviewed. Moreover, progression-free survival (PFS) and overall survival (OS) of these patients were analyzed.

RESULTS

A total of 309 patients with NSCLC (200 men, 109 women; mean age: 61 ± 9 years) were enrolled in this study, including 217 patients with adenocarcinoma and 92 with squamous cell carcinoma. Of the 309 cases, 11 were misdiagnosed with benign diseases by ¹⁸F-FDG PET/CT. CTCs positivity was detected in 234 cases. The sensitivity of ¹⁸F-FDG PET/CT and CTCs in NSCLC were 96.4% and 75.7%, respectively. SUVmax, MTV-P, TLG-P, MTV-C, TLG-C, tumor size, and serum CYFRA211 levels were significantly higher in CTCs positive group than negative group; and advanced TNM stage, squamous cell carcinoma, and EGFR wild type presented higher CTCs positivity. Multivariate logistic regression analysis revealed that SUVmax was significantly associated with CTCs positivity. Multivariate cox regression analysis showed that TLG-P, TLG-C, and CTCs were independent predictors of PFS in patients with NSCLC, and TLG-C and CTCs were independent predictors of OS.

CONCLUSIONS

¹⁸F-FDG PET/CT was superior to CTCs in the diagnosis of treatment-naive patients with NSCLC. The levels of CTCs in the peripheral blood were associated with tumor glucose metabolism in NSCLC. Metabolic parameters of ¹⁸F-FDG PET/CT and CTCs could separately predict the outcomes of treatment-naive patients with NSCLC.

PET-Based Volumetric Biomarkers for Risk Stratification of Non-Small Cell Lung Cancer Patients

Despite the recent advances in lung cancer biology, molecular pathology, and treatment, this malignancy remains the leading cause of cancer-related death worldwide and non-small cell lung cancer (NSCLC) is the most common form found at diagnosis. Accurate staging of the disease is a fundamental prognostic factor that correctly predicts progression-free (PFS) and overall survival (OS) of NSCLC patients. However, outcome of patients within each TNM staging group can change widely highlighting the need to identify additional prognostic biomarkers to better stratify patients on the basis of risk. 18F-FDG PET/CT plays an essential role in staging, evaluation of treatment response, and tumoral target delineation in NSCLC patients. Moreover, a number of studies showed the prognostic role of imaging parameters derived from PET images, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG). These parameters represent three-dimensional PET-based measurements providing information on both tumor volume and metabolic activity and previous studies reported their ability to predict OS and PFS of NSCLC patients. This review will primarily focus on the studies that showed the prognostic and predictive role of MTV and TLG in NSCLC patients, addressing also their potential utility in the new era of immunotherapy of NSCLC.

Tumor-to-liver standard uptake ratio using fluorine-18 fluorodeoxyglucose positron emission tomography computed tomography effectively predict occult lymph node metastasis of non-small cell lung cancer patients

OBJECTIVES

We aimed to investigate predictive factors of occult lymph node metastasis and to explore the diagnostic value of various standardized uptake value (SUV) parameters using fluorine-18 fluorodeoxyglucose (F-FDG) positron emission tomography computed tomography (PET/CT) in predicting occult lymph node metastasis of clinical N0 non-small cell lung cancer patients.

METHODS

We retrospectively analyzed PET/computed tomography parameters of tumor and clinical data of 124 clinical N0 non-small cell lung cancer patients who underwent both preoperative F-FDG PET/computed tomography and anatomical pulmonary resection with systematic lymph node dissections. The SUVmax, SUVmean, metabolic total volume, and total lesion glycolysis of the primary tumor was automatically measured on the PET/computed tomography workstation. Standardized uptake ratio (SUR) were derived from tumor standardized uptake value divided by blood SUVmean (B-SUR) or liver SUVmean (L-SUR), respectively.

RESULTS

According to postoperative pathology, 19 (15%) were diagnosed as occult lymph node metastasis among 124 clinical N0 non-small cell lung cancer patients. On univariate analysis, carcinoembryonic antigen, cytokeratin 19 fragment, lobulation, and all PET parameters were associated with occult lymph node metastasis. The area under the receiver operating characteristic curve, sensitivity, and negative predictive value of L-SURmax were the highest among all PET parameters (0.778, 94.7%, and 98.4%, respectively). On multivariate analysis, carcinoembryonic antigen, cytokeratin 19 fragment, and L-SURmax were independent risk factors for predicting occult lymph node metastasis. Compared to L-SURmax alone and the combination of carcinoembryonic antigen and cytokeratin 19 fragment, the model consisting of three independent risk factors achieved a greater area under the receiver operating characteristic curve (0.901 vs. 0.778 vs. 0.780, P = 0.021 and 0.0141).

CONCLUSIONS

L-SURmax showed the most powerful predictive performance than the other PET parameters in predicting occult lymph node metastasis. The combination of three independent risk factors (carcinoembryonic antigen, cytokeratin 19 fragment, and L-SURmax) can effectively predict occult lymph node metastasis in clinical N0 non-small cell lung cancer patients.

A machine learning-based radiomics model for the prediction of axillary lymph-node metastasis in breast cancer

OBJECTIVE

The aim of this study was to develop and validate machine learning-based radiomics model for predicting axillary lymph-node (ALN) metastasis in invasive ductal breast cancer (IDC) using F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT).

METHODS

A total of 100 consecutive IDC patients who underwent surgical resection of primary tumor with sentinel lymph-node biopsy and/or ALN dissection without any neoadjuvant treatment were analyzed. Volume of interests (VOIs) were drawn more than 2.5 of standardized uptake value in the primary tumor on the PET scan using 3D slicer. Pyradiomics package was used for the extraction of texture features in python. The radiomics prediction model for ALN metastasis was developed in 75 patients of the training cohort and validated in 25 patients of the test cohort. XGBoost algorithm was utilized to select features and build radiomics model. The sensitivity, specificity, and accuracy of the predictive model were calculated.

RESULTS

ALN metastasis was found in 43 patients (43%). The sensitivity, specificity, and accuracy of F-18 FDG PET/CT for the diagnosis of ALN metastasis in the entire patients were 55.8%, 93%, and 77%, respectively. The radiomics model for the prediction of ALN metastasis was successfully developed. The sensitivity, specificity, and accuracy of the radiomics model for the prediction of ALN metastasis in the test cohorts were 90.9%, 71.4%, and 80%, respectively.

CONCLUSION

The machine learning-based radiomics model showed good sensitivity for the prediction of ALN metastasis and could assist the preoperative individualized prediction of ALN status in patients with IDC.

Predictive Value of 18F-Fluorodeoxyglucose Positron Emission Tomography or Positron Emission Tomography/Computed Tomography for Assessment of Occult Lymph Node Metastasis in Non-Small Cell Lung Cancer

OBJECTIVE

The purpose of the current study was to investigate the diagnostic performance of 18F fluorodeoxyglucose (FDG) positron emission tomography (PET) or positron emission tomography/computed tomography (PET/CT) for the prediction of occult lymph node metastasis (OLNM) in non-small cell lung cancer (NSCLC) patients through a systematic review and meta-analysis.

METHODS

The PubMed, Cochrane, and EMBASE database, from the earliest available date of indexing through March 31, 2020, were searched for studies evaluating the diagnostic performance of preoperative 18F FDG PET or PET/CT for the prediction of OLNM in NSCLC patients.

RESULTS

Across 14 studies (3,535 patients), the pooled sensitivity for 18F FDG PET or PET/CT was 0.79 (95% CI; 0.70-0.86) with heterogeneity (I2 = 81.5, p < 0.001) and a pooled specificity of 0.65 (95% CI; 0.57-0.72) with heterogeneity (I2 = 93.7, p < 0.001). Likelihood ratio (LR) syntheses gave an overall positive likelihood ratio (LR+) of 2.3 (95% CI; 1.9-2.6) and a negative likelihood ratio (LR-) of 0.32 (95% CI; 0.23-0.44). The pooled diagnostic odds ratio (DOR) was 7 (95% CI; 5-10). The hierarchical summary receiver operating characteristic curve indicates that the area under the curve was 0.77 (95% CI; 0.74-0.81).

CONCLUSION

The current meta-analysis showed a moderate sensitivity and specificity of 18F FDG PET or PET/CT for the prediction of OLNM in NSCLC patients. The DOR was low and the likelihood ratio scatter-gram indicated that 18F FDG PET or PET/CT might not be useful for the prediction of OLNM in NSCLC patients and not for its exclusion.

Prediction of cervical metastasis and survival in cN0 oral cavity cancer using tumour 18F-FDG PET/CT functional parameters

PURPOSE

Oral cavity squamous cell carcinoma (OCC) can spread to the neck without apparent lymphadenopathy. Pretreatment detection or prediction of occult metastasis might contribute to proper management of clinically node-negative (cN0) OCC. We examined the role of tumour quantitative 18-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/computed tomography (CT) measurements for predicting OCC occult metastasis and survival.

METHODS

This study included 130 cN0 OCC patients who underwent ¹⁸F-FDG PET/CT scanning and subsequent curative surgery and neck dissection. Maximum, peak, and mean standardized uptake value (SUV_max, SUV_peak, and SUV_mean), metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were measured on pretreatment ¹⁸F-FDG PET/CT. Binary logistic regression was used to identify factors predicting occult cervical metastasis. Univariate and multivariate Cox proportional hazard regression were used to find factors associated with overall survival (OS).

RESULTS

Pathological cervical metastasis (pN +) was found in 29 (22.3%) patients. Age, tumour differentiation, lymphovascular invasion, and T classification were significantly associated with pN + (all P < 0.05). After adjustment for these factors, MTV and TLG independently predicted pN + (P < 0.05). Invasion depth, lymphovascular invasion, T and N classifications, and overall TNM stage were significantly associated with OS. After adjustment for these factors, SUV_max and TLG independently predicted OS (all P < 0.05). Patients with TLG > 9.3 g had a 5.7-fold increased risk of overall mortality.

CONCLUSIONS

Tumour ¹⁸F-FDG PET/CT parameters might predict occult metastasis and survival in cN0 OCC patients.

Nomogram using F-18 fluorodeoxyglucose positron emission tomography/computed tomography for preoperative prediction of lymph node metastasis in gastric cancer

BACKGROUND

Lymph node (LN) metastasis is an important prognostic factor in patients with gastric cancer (GC). However, the evaluation of LN metastasis status in the preoperative setting is not accurate. Therefore, precise preoperative prediction of LN metastasis status is crucial for optimal treatment in patients with GC.

AIM

To develop a preoperative nomogram for LN metastasis using F-18 fluorodeoxyglucose (F-18 FDG) positron emission tomography/computed tomography (PET/CT) and preoperative laboratory test findings in GC.

METHODS

In this study, the data of 566 GC patients who underwent preoperative F-18 FDG PET/CT and subsequent surgical resection were analyzed. The LN metastasis prediction model was developed in the training cohort and validated in the internal validation cohort. Routine preoperative laboratory tests, including albumin and carbohydrate antigen (CA) 19-9 were performed in all patients. Univariate and multivariable logistic regression was performed to validate the preoperative predictive indicators for LN metastasis.

RESULTS

Of the 566 patients, 232 (41%) had confirmed histopathologic LN metastasis. Univariate logistic regression revealed that the tumor location, blood hemoglobin, serum albumin levels, neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, CA 19-9, maximum standardized uptake value (SUVmax) of the primary tumor (T_SUVmax), and SUVmax of LN (N_SUVmax) were significantly associated with LN metastasis. In multivariate analysis, T_SUVmax (OR = 1.08; 95%CI: 1.02–1.15; P = 0.011) and N_SUVmax (OR = 1.49; 95%CI: 1.19–1.97; P = 0.002) were found to be significant predictive factors for LN metastasis. The LN metastasis prediction model using T_SUVmax, N_SUVmax, serum albumin, and CA 19-9 yielded an area under the curve (AUC) of 0.733 (95%CI: 0.683–0.784, P = 0.025) in the training cohort and AUC of 0.756 (95%CI: 0.678–0.833, P < 0.001) in the test cohort.

CONCLUSION

T_SUVmax and N_SUVmax measured by preoperative F-18 FDG PET/CT are independent predictive factors for LN metastasis in GC.

Retrospective analysis of the prognostic value of PD-L1 expression and 18F-FDG PET/CT metabolic parameters in colorectal cancer

Background: It has been rarely reported whether ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) uptake in colorectal cancer cells is associated with the expression of PD-L1. We performed a clinical pathology study to evaluate PD-L1 expression in patients undergoing surgical resection of colorectal cancer with preoperative ¹⁸F-FDG PET/CT imaging, with the aim of predicting the response of CRC patients to immune checkpoint inhibitors.

Material and Methods: A retrospective analysis of patients with CRC who underwent FDG-PET imaging before surgery was performed to measure the parameters of FDG-PET imaging: the maximum standardized uptake value (SUVmax), the metabolic tumor volume (MTV), and the total lesion glycolysis (TLG) were evaluated to determine whether each parameter was associated with clinical pathology. Tumor specimens were subjected to PD-L1 staining by immunohistochemistry. Analysis of whether there is a correlation between PD-L1 expression and ¹⁸F-FDG uptake parameters in CRC.

Results: PD-L1 expression level was significantly correlated with SUVmax, MTV3.0 and TLG3.0. Multivariate analysis showed that PD-L1 and TLG3.0 were independent predictors of poor DFS in patients with CRC (P=0.009; P=0.016), PD-L1 expression is closely related to the patient's lesion (TLG3.0) (P<0.01).

Conclusion: The results of this study indicate that there was a significant correlation between PD-L1 expression and TLG3.0 which suggested that FDG-PET could serve as a noninvasive tool to assess the tumor microenvironment and as a predictor of PD-L1 inhibitor activity to determine the optimal therapeutic strategy for CRC. High PD-L1 expression levels and high TLG3.0 are independent risk factors for DFS differences in CRC patients.

18F-FDG PET/CT in lung adenosquamous carcinoma and its correlation with clinicopathological features and prognosis

OBJECTIVE

Lung adenosquamous carcinoma (ASC) is a rare histological subtype of non-small cell lung cancer (NSCLC). Due to its rarity, the studies about ¹⁸F-FDG PET/CT in this kind of pulmonary tumor were quite limited. Thus, this study investigated ¹⁸F-FDG PET/CT findings in ASC and its correlation with clinicopathological features and clinical outcomes.

METHODS

Preoperative ¹⁸F-FDG PET/CT findings and parameters of maximum standard uptake value (SUV_max), metabolic tumor volume and total lesion glycolysis of primary lesion (MTV-P, TLG-P), combination of primary lesion and metastases (MTV-C, TLG-C), and clinicopathological features were retrospectively investigated in patients with ASC. Moreover, progression-free survival (PFS) was also analyzed.

RESULTS

All 41 patients (25 men; 16 women; age: 60 ± 7 years) had single ASC with the mean diameter of 33 ± 14 mm. Six lesions were located centrally and 35 peripherally. Serum tumor markers were abnormally increased sporadically. Twenty-two cases were at TNM stage I, 9 at II, and 10 at III. The primary tumors were FDG-avid in all cases, with the average SUV_max of 11.5 ± 6.0. SUV_max was significantly associated with tumor location, size, and TNM stage (P < 0.05). Forty-one lesions were subgrouped into 23 AC-predominant and 18 SCC-predominant lesions, and significant differences were observed for age, tumor size, and SUV_max in two groups (P < 0.05). The median PFS of 41 cases was 19 months, and 12-month and 24-month PFS rates were 72.1% and 36.1%, respectively. SUV_max, MTV-P, and TLG-C were significantly associated with PFS (P < 0.05).

CONCLUSIONS

ASC of the lung displayed high SUV_max on ¹⁸F-FDG PET/CT, which was associated with tumor location, size, TNM stage, and predominant histologic component. Moreover, metabolic parameters of ¹⁸F-FDG PET/CT were independent prognostic factors of this rare lung malignancy.

Minor components of micropapillary and solid subtypes in lung invasive adenocarcinoma (≤ 3 cm): PET/CT findings and correlations with lymph node metastasis

OBJECTIVE

To investigate the PET/CT findings in lung invasive adenocarcinoma with minor components of micropapillary or solid contents and its association with lymph node metastasis.

MATERIALS AND METHODS

A total of 506 lung invasive adenocarcinoma (≤ 3 cm) patients who underwent a PET/CT examination and resection surgery were included. According to the proportion of solid/micropapillary components, the patients were classified into three groups: solid/micropapillary-negative (SMPN) (n = 258), solid/micropapillary-minor (SMPM; > 5% not predominant) (n = 158) and solid/micropapillary-predominant (SMPP; > 5% most dominant) (n = 90). The patients' PET/CT findings, including SUVmax, MTV, TLG and CT characteristics, and other clinical factors were compared by one-way ANOVA test. Logistic regression analysis was done to identify the most predictive findings for lymph node metastasis.

RESULTS

The value of SUVmax, MTV, TLG and tumor size was highest in SMPP group, followed by SMPM and SMPN group (P < 0.001).The areas under the curve for SUVmax, MTV and TLG for node metastasis were 0.822, 0.843 and 0.835, respectively. Univariate analysis found that the SMPP and SMPM group had more lymph node metastasis than the SMPN group (P < 0.001). Furthermore, the lymph node metastasis group had higher CEA, SUVmax, MTV, TLG, tumor size and more pleural invasion (P < 0.001). Logistic regression analysis found that SMPP pathological type, SMPM pathological type, higher CEA and male patients were risk factors for lymph node metastasis (P < 0.01).

CONCLUSIONS

Lung invasive adenocarcinoma with micropapillary or solid contents had higher SUVmax, MTV, TLG and tumor size and was associated with lymph node metastasis, even if they were not predominant.

Diagnostic Value of 18F-fluorodeoxyglucose Positron Emission Tomography with Computed Tomography for Lymph Node Staging in Patients with Upper Tract Urothelial Carcinoma

BACKGROUND

Presence of lymph node metastases (LNM) is an important prognostic factor for cancer-specific survival (CSS) in patients with upper tract urothelial carcinoma (UTUC). In various neoplasms, ¹⁸F-fluorodeoxyglucose positron emission tomography with computed tomography (FDG-PET/CT) is an established modality for preoperative lymph node (LN) staging. In UTUC, the diagnostic value of FDG-PET/CT for LN staging is unknown.

OBJECTIVE

To determine the diagnostic value of FDG-PET/CT for LN staging in patients with UTUC.

DESIGN, SETTING, AND PARTICIPANTS

Data of 152 patients with UTUC who underwent FDG-PET/CT followed by surgical treatment in eight centers between 2007 and 2017 were retrospectively collected. Patients receiving neoadjuvant chemotherapy were excluded.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

FDG-PET/CT results were compared with histopathology after lymph node dissection (LND). Recurrence-free survival (RFS), CSS, and overall survival (OS) were analyzed using Kaplan-Meier estimates, and compared for patients with and without suspicious LNs on FDG-PET/CT.

RESULTS AND LIMITATIONS

We included 117 patients, of whom 62 underwent LND. Seventeen patients had LNM at histopathological evaluation. Sensitivity and specificity of FDG-PET/CT for diagnosis of LNM were 82% (95% confidence interval [CI]: 57-96) and 84% (95% CI: 71-94), respectively. RFS was significantly worse in patients with LN-positive FDG-PET/CT than in those with LN-negative FDG-PET/CT (p=0.03). CSS (p=0.11) and OS (p=0.5) were similar between groups. This study is limited by its retrospective design and by its sample size. Our results warrant further validation.

CONCLUSIONS

FDG-PET/CT has 82% sensitivity and 84% specificity for the detection of LNM in patients with UTUC. Presence of suspicious LNs on FDG-PET/CT is associated with worse RFS.

PATIENT SUMMARY

In patients with upper tract urothelial cancer, positron emission tomography with computed tomography (PET/CT) scans can detect lymph node metastases with noteworthy accuracy. Presence of suspicious lymph nodes on ¹⁸F-fluorodeoxyglucose PET/CT is associated with worse recurrence-free survival.

Prediction of occult lymph node metastasis using SUV, volumetric parameters and intratumoral heterogeneity of the primary tumor in T1-2N0M0 lung cancer patients staged by PET/CT

OBJECTIVE

The aim of this study was to identify whether PET/CT-related metabolic parameters of the primary tumor could predict occult lymph node metastasis (OLM) in patients with T1-2N0M0 NSCLC staged by ¹⁸F-FDG PET/CT.

METHODS

215 patients with clinical T1-2N0M0 (cT1-2N0M0) NSCLC who underwent both preoperative FDG PET/CT and surgical resection with the systematic lymph node dissection were included in the retrospective study. Heterogeneity factor (HF) was obtained by finding the derivative of the volume-threshold function from 40 to 80% of the maximum standardized uptake value (SUVmax). Univariate and multivariate stepwise logistic regression analyses were used to identify these PET parameters and clinicopathological variables associated with OLM.

RESULTS

Statistically significant differences were detected in sex, tumor site, SUVmax, mean SUV (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis and HF between patients with adenocarcinoma (ADC) and squamous cell carcinoma (SQCC). OLM was detected in 36 (16.7%) of 215 patients (ADC, 27/152 = 17.8% vs. SQCC, 9/63 = 14.3%). In multivariate analysis, MTV (OR = 1.671, P = 0.044) in ADC and HF (OR = 8.799, P = 0.023) in SQCC were potent associated factors for the prediction of OLM. The optimal cutoff values of 5.12 cm³ for MTV in ADC, and 0.198 for HF in SQCC were determined using receiver operating characteristic curve analysis.

CONCLUSIONS

In conclusion, MTV was an independent predictor of OLM in cT1-2N0M0 ADC patients, while HF might be the most powerful predictor for OLM in SQCC. These findings would be helpful in selecting patients who might be considered as candidates for sublobar resection or new stereotactic ablative radiotherapy.

Predictive Value of [18F]FDG PET/CT for Lymph Node Metastasis in Rectal Cancer

[¹⁸F]Fluorodeoxyglucose ([¹⁸F]FDG) Positron emission tomography/computed tomography (PET/CT) is commonly used for rectal cancer staging, but improved diagnostic methods for nodal metastases are needed. We aimed to evaluate whether the combination model of the metabolic tumor volume of primary tumor (T_MTV) and maximum standardized uptake value of lymph node (N_SUVmax) on pretreatment [¹⁸F]FDG PET/CT could improve nodal metastases prediction in rectal cancer. We enrolled a total of 166 rectal cancer patients who underwent pretreatment [¹⁸F]FDG PET/CT and surgical resection without neoadjuvant treatment between January 2009 and August 2016. Visual and semiquantitative PET/CT parameters were obtained. Associations between clinicopathological, PET/CT-derived variables and nodal metastases were evaluated by logistic regression analysis. Nodal metastases were confirmed histologically in 68 of the 166 patients (41%). Uni- and multivariate analyses demonstrated T_MTV and N_SUVmax were independent predictive factors for nodal metastases. The c-statistics of the combination model was 0.806 (Standard Error, 0.034; 95% Confidence Interval, 0.737-0.863), which showed significant improvement compared to T_MTV (0.698, P = 0.0002) or N_SUVmax (0.720, P = 0.0008) alone. T_MTV and N_SUVmax are independently correlated with nodal metastases. Furthermore, the combination model showed improved performance for risk prediction; thus, [¹⁸F]FDG PET/CT might have a role in rectal cancer staging and treatment planning.

Prognostic significance of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography-derived metabolic parameters in surgically resected clinical-N0 nonsmall cell lung cancer

OBJECTIVE

Our aim was to assess the significance of metabolic positron emission tomography (PET) parameters for the prediction of occult mediastinal lymph node metastasis (OLM) and recurrence in patients with clinical-N0 nonsmall cell lung cancer (NSCLC) after surgical resection and lymph node dissection.

MATERIALS AND METHODS

We evaluated 98 patients with NSCLC [52 adenocarcinoma (ADC), 46 squamous cell carcinoma (SQCC)] who had undergone initial/preoperative fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT). Eligibility criteria for participation were clinically staged as N0 and no FDG uptake in mediastinal lymph nodes on preoperative PET/CT. Clinicopathological characteristics and the diagnosis of recurrence were obtained by reviewing the hospital records. Metabolic parameters [maximum standardized uptake value, mean standardized uptake value, metabolic tumor volume (MTV), total lesion glycolysis] were determined on F-FDG PET/CT images. The association of metabolic parameters with OLM and recurrence was assessed.

RESULTS

OLM was found in 26 (26.53%) patients. T-stage, central location, and lymphovascular invasion were associated with OLM (respectively, P=0.007, 0.011, <0.001). None of the metabolic parameters was associated with OLM. Metabolic parameters of the tumor were significantly higher in patients with recurrence when the cohort was evaluated as a whole (P=0.002, 0.005, 0.016, and 0.004, respectively). In particular, there was a significant association between recurrence and tumor size, grade, stage, MTV (P<0.001), and TLG (P<0.001) in ADC. This association was not found in SQCC. Multivariate analysis showed that MTV was an independent prognostic factor for recurrence and associated with disease-free survival.

CONCLUSION

Metabolic parameters of the primary tumor on preoperative F-FDG PET/CT could not predict OLM in patients with clinical-N0 NSCLC. MTV was an independent risk factor for recurrence in ADC, but not in SQCC.

Prediction of Occult Lymph Node Metastasis Using Tumor-to-Blood Standardized Uptake Ratio and Metabolic Parameters in Clinical N0 Lung Adenocarcinoma

PURPOSE

We aimed to investigate whether the tumor-to-blood SUV ratio (SUR) and metabolic parameters of F-FDG uptake could predict occult lymph node metastasis (OLM) in clinically node-negative (cN0) lung adenocarcinoma.

MATERIALS AND METHODS

We retrospectively reviewed 157 patients with cN0 lung adenocarcinoma who underwent both preoperative F-FDG PET/CT and surgical resection with the systematic lymph node dissection. The SUVmax, SUVmean, MTV, and total lesion glycolysis (TLG) of the primary tumor was measured on the PET/CT workstation. SURmax, SURmean, and TLGsur were derived from each of them divided by descending aorta SUVmean. These PET parameters and clinicopathological variables were analyzed for OLM.

RESULTS

In our study, OLM was detected in 31 (19.7%) of 157 patients. Significantly higher values of tumor size, SUVmax, SUVmean, MTV, TLGsuv, SURmax, SURmean, and TLGsur were found in patients with OLM. In receiver operating characteristic curve analysis, the optimal cutoff values of the above parameters were 29.50, 4.38, 2.45, 6.37, 44.13, 5.30, 1.86, and 28.24, respectively. The multivariate analysis showed that TLGsur (odds ratio, 1.024; P = 0.002) was the most potent associated factor for the prediction of OLM in cN0 lung adenocarcinoma.

CONCLUSIONS

TLGsur showed the most powerful predictive performance than the other PET parameters for the prediction of OLM in cN0 lung adenocarcinoma. This normalized volumetric parameter would be helpful in selection of sublobar resection or aggressive tailored treatments in patients with cN0 lung adenocarcinoma.

A risk-based approach to identifying oligometastatic disease on imaging

Recognition of <3 metastases in <2 organs, particularly in cancers with a known predisposition to oligometastatic disease (OMD) (colorectal, prostate, renal, sarcoma and lung), offers the opportunity to focally treat the lesions identified and confers a survival advantage. The reliability with which OMD is identified depends on the sensitivity of the imaging technique used for detection and may be predicted from phenotypic and genetic factors of the primary tumour, which determine metastatic risk. Whole‐body or organ‐specific imaging to identify oligometastases requires optimization to achieve maximal sensitivity. Metastatic lesions at multiple locations may require a variety of imaging modalities for best visualisation because the optimal image contrast is determined by tumour biology. Newer imaging techniques used for this purpose require validation. Additionally, rationalisation of imaging strategies is needed, particularly with regard to timing of imaging and follow‐up studies. This article reviews the current evidence for the use of imaging for recognising OMD and proposes a risk‐based roadmap for identifying patients with true OMD, or at risk of metastatic disease likely to be OM.

Maximum Standardized Uptake Value (SUVmax) of Primary Tumor Predicts Occult Neck Metastasis in Oral Cancer

The aim of this study was to investigate the predictability of occult lymph node metastasis using maximum standardized uptake value (SUV_max) in the primary tumor on pre-treatment 18-fluorodeoxyglucose positron emission tomography FDG-PET in oral squamous cell carcinoma (OSCC) patients who were clinically node negative (cN0) before surgery. A retrospective analysis of all patients treated at the University Hospital Zurich from 2007 to 2016 for OSCC with available pre-therapeutic FDG-PET was performed. We assessed the correlation of SUV_max of the primary tumors with the presence of occult nodal disease in the neck dissection specimen (pN+). The study included a total of 71 patients. In the nodal negative group (cN0/pN0), the median SUV_max of primary tumors was 9.0 (interquartile range (IQR) 7.4–13.9), while it was 11.4 (IQR 9.9–15.7) in the occult metastatic group (cN0/pN+). The difference was statistically significant (independent samples median test, P = 0.037). In a multivariable model, the only independent predictor of occult metastatic disease for cN0 patients was a SUV_max ≥ 9.5 (P = 0.028). Further, primary tumors with SUV_max ≥ 9.5 had a significantly higher risk of local recurrence (Log rank test, P = 0.020). In conclusion, we showed that higher SUV_max (≥9.5) of the primary tumor is associated with higher occurrence of occult metastatic nodal disease and worse local survival. High SUV_max of the primary tumor may encourage clinicians towards more aggressive treatment.

A SUVmax-based propensity matched analysis of stereotactic body radiotherapy versus surgery in stage I non-small cell lung cancer: unveiling the role of 18F-FDG PET/CT in clinical decision-making

BACKGROUND

The value of maximum standard uptake value (SUV_max) was overlooked in current studies comparing stereotactic body radiotherapy (SBRT) versus surgery for stage I non-small cell lung cancer (NSCLC). Herein, we aimed to compare the 3-year outcomes based on patients for whom SUV_max were available, and to explore the role of SUV_max in clinical decision-making.

METHODS

From January 2010 to June 2016, data of eligible patients were collected. Patient variables and clinical outcomes were compared in both unmatched and matched groups using propensity score matching (PSM). Multivariate analysis was performed for predictors of poor outcome. The relationship between treatment approach and survival outcome was also evaluated in subgroup patients stratified by SUV_max level.

RESULTS

A total of 425 patients treated with either surgery (325) or SBRT (100) were included. Patients receiving SBRT were significantly older, had a higher level of SUV_max and were more likely to have tumor of centrally located. Multivariate analysis showed that SUV_max and tumor size were significant predictors for 3-year OS, LRC, and PFS, while better PFS was also related to peripheral tumor and surgery. The result of PSM analysis also showed that compared to SBRT, surgery could only achieve better PFS. Subgroup analysis indicated that surgery had added advantage of 3-year LRC and PFS for patients in high SUV_max group (SUV_max > 8), but not in low SUV_max group.

CONCLUSIONS

The study found a superior PFS after surgery while OS and LRC did not differ between SBRT and surgery. Surgery should be recommended for tumor of high SUV_max.

Prognostic value of intratumoral metabolic heterogeneity on F-18 fluorodeoxyglucose positron emission tomography/computed tomography in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy

OBJECTIVE

To evaluate the prognostic value for predicting tumor recurrence of intratumoral metabolic heterogeneity and traditional quantitative metabolic parameters on pre-treatment F-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy (CCRT).

MATERIALS AND METHODS

Ninety-three patients with biopsy-proven cervical cancer and treated with CCRT (FIGO stage IIB-IV) were enrolled in this study. The traditional metabolic parameters of the primary tumor, regional lymph node, and whole body (maximum standardized uptake value [SUVmax], metabolic tumor volume [MTV], and total lesion glycolysis), and intratumoral heterogeneity factor (HF) were measured on pre-treatment 18F-FDG PET/CT images. Univariate and multivariate analyses for disease-free survival (DFS) were performed using clinical and metabolic parameters. The additional HF prognostic value was evaluated by means of time-dependent receiver operating characteristic curve, integrated discrimination improvement, and net reclassification improvement.

RESULTS

On multivariate analysis, nodal SUVmax (hazard ratio 3.60; 95% CI, 1.66-7.85; p = 0.0012) and whole body MTV (WBMTV; hazard ratio 3.15; 95% CI, 1.17-8.53; p = 0.0236) were significant prognostic factors for DFS. When HF was combined with nodal SUVmax and WBMTV, a significant improvement in discrimination for recurrence was observed compared with nodal SUVmax alone (area under curve 0.817 vs. 0.732; p = 0.0028).

CONCLUSIONS

HF did not show superiority over traditional metabolic parameters. However, when HF was combined with nodal SUVmax and WBMTV, the predictive value for tumor recurrence improved. Therefore, HF may be a useful additional prognostic biomarker to improve the prognostic value of traditional metabolic parameters on 18F-FDG PET/CT.

Predictive Value of 18F-FDG PET/CT for Axillary Lymph Node Metastasis in Invasive Ductal Breast Cancer

BACKGROUND

This study assessed whether primary tumor maximum standardized uptake value (pSUV_max) measured by ¹⁸F-fluoro-2-deoxy-D-glucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) could improve the prediction of axillary lymph node (ALN) metastasis in invasive ductal breast cancer (IDC).

METHODS

In this study, 128 IDC patients who underwent pretreatment ¹⁸F-FDG PET/CT and surgical resection of primary tumor with sentinel lymph node biopsy, ALN dissection, or both were analyzed. All the patients were classified as five molecular subtypes. The optimal cutoff values of pSUVmax for all the patients and each molecular subtype for the prediction of ALN metastasis were determined using receiver operating characteristic (ROC) analysis. Furthermore, the prognostic accuracy of ALN metastasis was assessed using c-statistics.

RESULTS

The findings showed ALN metastasis in 52 patients (40.6%). The ¹⁸F-FDG PET/CT procedure had a sensitivity of 48.1% and a specificity of 94.7% for ALN metastasis. In the ROC analysis of pSUVmax for ALN metastasis, the optimal cutoff value was 3.9 for all the patients, 2.8 for the luminal A subtype, 3.3 for the luminal B (human epidermal growth factor receptor 2 [HER2]-negative) subtype, 5.3 for the luminal B (HER2-positive) subtype, 12.7 for the HER2-positive subtype, and 11.5 for the triple-negative subtype. A predictive ALN metastasis model using nodal ¹⁸F-FDG uptake finding gave a c-statistic of 0.714, and a model combination of nodal ¹⁸F-FDG uptake finding with pSUV_max of all the patients gave a c-statistic of 0.736 (P = 0.3926). However, the combination of nodal the ¹⁸F-FDG uptake finding with the pSUV_max of each molecular subtype gave a c-statistic of 0.791 (P = 0.0047).

CONCLUSIONS

Combining the pSUV_max of each molecular subtype with the nodal ¹⁸F-FDG uptake finding can improve the prediction of ALN metastasis in IDC.

Metabolic Tumor Volume and Total Lesion Glycolysis in PET/CT Correlate With the Pathological Findings of Colorectal Cancer and Allow Its Accurate Staging

INTRODUCTION

PET/CT plays an important role in cancer diagnosis. Recently, novel metabolic parameters in PET/CT such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have been reported to be diagnostic and prognostic biomarkers of various cancers. We evaluated the diagnostic value of these metabolic parameters in colorectal cancer (CRC).

METHODS

The study included 138 patients who underwent surgical resection of CRCs between August 2012 and March 2014. The MTVs and TLGs of tumors were measured using various SUV thresholds. The diagnostic abilities of the metabolic parameters were analyzed using ROC curves and classification and regression trees.

RESULTS

The AUCs of the MTVs and TLGs for predicting T stage (0.881-0.892) were significantly higher than the AUC of the SUVmax (0.824). In the M stage, the AUCs of MTVs and TLGs (0.688-0.723) were significantly higher than that of the SUVmax (0.606). Recursive partitioning applying classification and regression trees demonstrated that the optimal cutoff values of the most important variables for discriminating T, N, and M stages are MTV2.5 = 9.35 and 63.33 mL, TLG50% = 328.1, and TLG50% = 94.81, respectively.

CONCLUSION

Metabolic tumor volumes and TLGs in PET/CT are reliable diagnostic biomarkers. Using these parameters, more accurate preoperative diagnoses for CRC can be made.

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

PURPOSE

This study aimed to evaluate the prognostic value of metabolic tumor burden as measured with metabolic tumor volume (MTV) and total lesion glycolysis (TLG), as well as SUVmax on initial staging and posttreatment F-FDG PET/CT in patients with stage IV non-small cell lung cancer (NSCLC).

METHODS

Sixty-three NSCLC patients with stage IV who underwent staging and posttreatment FDG PET/CT after completion of the first-line chemotherapy were retrospectively enrolled. SUVmax, MTV, and TLG of primary cancer and all metastatic lesions (lymph node and distant metastases) on both PET/CT images were measured and their association with progression-free survival (PFS) and overall survival (OS) analyzed.

RESULTS

Median PFS and OS in the patient population were 5.9 and 23.1 months, respectively. Among the PET/CT parameters, MTV and TLG of primary cancer lesions on initial PET/CT and MTV and TLG of metastatic lesions on posttreatment PET/CT were independent prognostic factors for both PFS and OS (P < 0.05). The median OS in patients who showed low values of those PET/CT parameters was more than 26.0 months, whereas patients with high values of those parameters had a median OS of less than 15.0 months.

CONCLUSIONS

Metabolic tumor burdens of primary cancer lesions on staging PET/CT and metastatic lesions on posttreatment PET/CT were independent prognostic factors in patients with stage IV NSCLC. Volume-based PET parameters could further stratify the prognosis of stage IV NSCLC patients.

Quantification of Intratumoral Metabolic Macroheterogeneity on 18F-FDG PET/CT and Its Prognostic Significance in Pathologic N0 Squamous Cell Lung Carcinoma

PURPOSE

This study aimed to develop a novel quantification method for intratumoral metabolic macroheterogeneity (IMMH) on F-FDG PET/CT and evaluate its prognostic significance in pathologic N0 (pN0) squamous cell lung carcinoma (SQCLC) patients.

PATIENTS AND METHODS

A total of 83 patients who underwent pretreatment F-FDG PET/CT and were diagnosed with pN0 SQCLC after curative surgery were examined. Patients with tumor measuring greater than 2 cm were included. Metabolic parameters (SUVmax, metabolic tumor volume, and total lesion glycolysis) for the primary lesions were calculated on the F-FDG PET/CT, and IMMH was quantified as the macroheterogeneity factor (MHF), defined as surface/spherical surface area having volume of the primary tumor multiplied by the sphericity. Heterogeneity of the primary tumor was also visually assessed (visual heterogeneity score) and compared with MHF. Univariate and multivariate analyses for recurrence were performed using the Cox proportional hazards regression.

RESULTS

Recurrence was observed in 27 (32.5%) of 83 patients during follow-up period (37.6 ± 25.5 months). Significant correlations were observed between the visual heterogeneity score and the MHF (R = 0.534, P < 0.001). Macroheterogeneity factor was significantly higher in patients who experienced recurrence (median, 1.073 vs 1.016; P = 0.004). Univariate analysis showed that MHF was only significant prognostic factor for recurrence (P = 0.019), and multivariate analysis after adjusting for age, sex, tumor size, histologic grade, and pathologic T stage, high MHF exhibited an association with increased risk of recurrence.

CONCLUSIONS

New quantification method for IMMH on F-FDG PET/CT was developed, and the heterogeneity parameter MHF was well correlated with visual heterogeneity. Macroheterogeneity factor on pretreatment F-FDG PET/CT was the sole prognostic factor predicting recurrence in pN0 SQCLC patients.

Prognostic Value of Volumetric Parameters Measured by Pretreatment 18F FDG PET/CT in Patients With Cutaneous Malignant Melanoma

PURPOSE OF THE REPORT

This study was performed to evaluate the prognostic relevance of metabolic tumor volume (MTV) and total lesion glycolysis (TLG) measured using F FDG PET/CT in patients with primary cutaneous malignant melanoma (CMM).

MATERIALS AND METHODS

We conducted a retrospective review (July 2005 to November 2010) of 41 patients with a histological diagnosis of CMM who underwent pretreatment F FDG PET/CT. PET parameters (maximum standardized uptake value [SUVmax], MTV, and TLG) of the primary tumor were measured. Clinical variables such as age, sex, clinical stage, location and thickness of the primary lesion, and existence of ulceration were also assessed. Univariate and multivariate analyses for disease-free survival (DFS) and melanoma-specific survival (MSS) were performed using the Kaplan-Meier method and Cox proportional hazards models.

RESULTS

SUVmax and TLG were found to be significantly higher in patients with recurrence than in patients without recurrence (3.98 ± 2.91 vs 1.89 ± 1.35, P = 0.0145; 9.16 ± 8.44 vs 3.72 ± 3.64, P = 0.0249). SUVmax and TLG were also found to be significantly higher in nonsurvivors than in survivors (4.21 ± 3.06 vs 2.00 ± 1.46, P = 0.0260; 10.53 ± 8.83 vs 3.67 ± 3.44, P = 0.0170). The optimal cutoff values for DFS determined using a time-dependent receiver operating characteristic (ROC) curve were 1.8 for SUVmax, 6.07 cm for MTV, and 4.046 for TLG. Sixteen (39%) of the 41 patients experienced recurrence during the follow-up period. In univariate analysis, age (P = 0.0382), male sex (P = 0.0187), ulceration of the primary lesion (P = 0.0001), stage ≥ III (P = 0.0011), SUVmax greater than 1.8 (P = 0.0006), MTV greater than 6.07 cm (P = 0.0136), and TLG greater than 4.046 (P = 0.0010) affected DFS, whereas the other variables (location of the primary lesion and thickness of primary lesion) did not. After adjustment for the effects of the clinical parameters (age, sex, clinical stage, and existence of ulceration), SUVmax, MTV, and TLG were all significant predictors of DFS, and the best predictive factor was SUVmax. Thirteen (32%) of the 41 patients died because of CMM during the follow-up period. The optimal cutoff values for MSS determined using a time-dependent ROC curve were 2.2 for SUVmax, 4.02 cm for MTV, and 4.352 for TLG. In univariate analysis, ulceration of the primary lesion (P = 0.0005), SUVmax greater than 2.2 (P = 0.0001), MTV greater than 4.02 cm (P = 0.0071), and TLG greater than 4.352 (P = 0.0001) affected MSS, whereas the other variables (age, sex, clinical stage, primary lesion site, and thickness of the primary lesion) did not. After adjustment for the effect of the clinical parameter (existence of ulceration), MTV and TLG were significant predictors of MSS, and the best predictive factor of MSS was TLG.

CONCLUSIONS

Pretreatment MTV and TLG may be useful in stratifying the likelihood of recurrence and melanoma-specific death, and TLG was found to be the best predictive marker for predicting melanoma-specific death.

Prognostic Significance of Intratumoral Metabolic Heterogeneity on 18F-FDG PET/CT in Pathological N0 Non-Small Cell Lung Cancer

PURPOSE

The aim of the study was to evaluate the prognostic significance of intratumoral metabolic heterogeneity on pretreatment F-FDG PET/CT in patients with lung cancer who were pathologically N0 (pN0) after curative surgical resection.

METHODS

We examined 119 patients (M/F = 79/40; mean age, 64.6 ± 9.0 years) who had undergone pretreatment F-FDG PET/CT and were diagnosed as pN0 after curative surgery for adenocarcinoma (ADC; n = 67) or squamous cell carcinoma (SQCC; n = 52). Heterogeneity factor (HF) and other metabolic parameters (SUVmax, metabolic tumor volume [MTV] and total lesion glycolysis [TLG]) for the primary lesions were measured, and the results were analyzed for recurrence. The HF, defined as the derivative of the volume-threshold function from 20% to 80%, was computed for primary lesions. Univariate and multivariate analyses for recurrence were performed using the Kaplan-Meier method and using the Cox proportional hazards model.

RESULTS

SUVmax, MTV, TLG, and HF were statistically different between patients with ADC and SQCC. Forty-one (34.5%) of 119 patients experienced recurrence (ADC, 25/67 = 37.3% vs. SQCC, 16/52 = 30.8%). Results of univariate analysis indicate that SUVmax, MTV, TLG, and HF in ADC and TLG and HF in SQCC were predictors for recurrence. After adjusting for sex, age, and histological grade in multivariate analysis, high SUVmax, MTV, TLG, and HF in ADC exhibited an association with increased risk of recurrence.

CONCLUSIONS

Metabolic parameters and heterogeneity of primary tumor on pretreatment F-FDG PET/CT can predict recurrence in pN0 NSCLC patients of ADC type who have undergone curative surgery but not in patients of SQCC type.

Prediction of occult lymph node metastasis using volume-based PET parameters in small-sized peripheral non-small cell lung cancer

Background

Patients with small-sized peripheral non-small cell lung cancer (NSCLC), but without lymph node metastasis, may be optimal candidates for sublobar resection. We aim to identify the predictors of occult lymph node metastasis (OLNM) using F-18 fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) in clinically node-negative, small-sized NSCLC.

Methods

One hundred thirty nine patients with small-sized NSCLC (of less than 3 cm in diameter) who underwent surgical resection with mediastinal lymph node dissection were evaluated. The maximum standardized uptake value (SUVmax), metabolic total volume (MTV) and total lesion glycolysis (TLG) of the primary tumor were measured on pretreatment PET/CT. These metabolic parameters and pathological variables were analyzed for OLNM.

Results

The mean tumor size was 2.11 ± 0.63 cm, and the mean number of dissected lymph nodes was 19.74 ± 12.86. Adenocarcinoma occurred in 106 patients (76.3 %). Twenty-four patients (17.2 %) had lymph node metastasis. The mean SUVmax, MTV and TLG were 4.61 ± 3.99 (0.5 ~ 17.8), 4.18 ± 6.39 (0 ~ 34.6) and 16.13 ± 28.86 (0 ~ 164.2), respectively. On receiver operating characteristic (ROC) curve analysis, the areas under the curve (AUC) for SUVmax, MTV and TLG for node metastasis were 0.753, 0.783 and 0.775, respectively. On multivariate analysis, SUVmax (Odds ratio [OR] = 1.120, p = 0.044) and MTV (OR = 1.117, p = 0.007) were found to be risk factors for OLNM. The concordance index of MTV was 0.763, which was slightly higher than that of SUVmax.

Conclusion

SUVmax and volume-based parameters are significant risk factors for OLNM in small peripheral NSCLC. MTV showed a better predictive performance than that of the other PET parameters; therefore, MTV may be a possible indicator for sublobar resection in clinically node-negative small-sized NSCLC.

Preoperative Prediction of Cervical Lymph Node Metastasis Using Primary Tumor SUVmax on 18F-FDG PET/CT in Patients with Papillary Thyroid Carcinoma

Objectives

The aim of the current study was to evaluate the value of preoperative ¹⁸F-FDG (FDG) PET/CT in predicting cervical lymph node (LN) metastasis in patients with papillary thyroid carcinoma (PTC).

Methods

One hundred and ninety-three newly diagnosed PTC patients (M: F = 25:168, age = 46.8 ± 12.2) who had undergone pretreatment FDG PET/CT and had neck node dissection were included in this study. The FDG avidity of the primary tumor and the SUVmax of the primary tumor (pSUVmax) were analyzed for prediction of LN metastasis. Detectability by ultrasonography (US) and FDG PET/CT for cervical LN metastasis were also assessed and compared with the pSUVmax.

Results

The FDG avidity of the primary tumor was identified in 118 patients (FDG avid group: 61.0%, M: F = 16:102, age 47.0 ± 12.7 years) and pSUVmax ranged from 1.3 to 35.6 (median 4.6) in the FDG avid group. The tumor size in the FDG avid group was bigger and there was a higher incidence of LN metastasis compared to the FDG non-avid group (0.93 vs. 0.59 cm, p <0.001 and 49.2 vs. 33.3%, p <0.05). In the FDG avid group, patients with LN metastasis had higher pSUVmax than patients without LN metastasis (8.7 ± 8.3 vs. 5.7 ± 5.1, p <0.001). The incidence of central LN metastasis in patients with a pSUVmax >4.6 was 54%; however, the detectability of central LN metastasis by US and FDG PET/CT were 10.3% and 3.6%, respectively.

Conclusion

A high FDG avidity of the primary tumor was related to LN metastasis in PTC patients. Therefore, patients with a high pSUVmax should be cautiously assessed for LN metastasis and might need a more comprehensive surgical approach.