Heterogeneity Analysis of (18)F-FDG Uptake in Differentiating Between Metastatic and Inflammatory Lymph Nodes in Adenocarcinoma of the Lung: Comparison with Other Parameters and its Application in a Clinical Setting

Coefficient of Variation in Metastatic Lymph Nodes Determined by 18F-FDG PET/CT in Patients with Advanced NSCLC: Combination with Coefficient of Variation in Primary Tumors

Purpose The aim of the present study was to test whether the coefficient of variation (CoV) of 18F-FDG PET/CT images of metastatic lymph nodes and primary tumors may predict clinical outcome in patients with advanced non-small cell lung cancer (NSCLC). Materials and Methods Fifty-eight NSCLC patients who had undergone 18F-FDG PET/CT at diagnosis were evaluated. SUVmax, SUVmean, CoV, MTV and TLG were determined in targeted lymph nodes and corresponding primary tumors along with Total MTV (MTVTOT) and Whole-Body TLG (TLGWB) of all malignant lesions. Univariate analysis was performed using Cox proportional hazards regression whereas the Kaplan-Meier method and log-rank tests were used for survival analysis. Results Fifty-eight metastatic lymph nodes were analyzed and average values of SUVmax, SUVmean, CoV, MTV and TLG were 11.89 ± 8.54, 4.85 ± 1.90, 0.37 ± 0.16, 46.16 ± 99.59 mL and 256.84 ± 548.27 g, respectively, whereas in primary tumors they were 11.92 ± 6.21, 5.47 ± 2.34, 0.36 ± 0.14, 48.03 ± 64.45 mL and 285.21 ± 397.95 g, respectively. At univariate analysis, overall survival (OS) was predicted by SUVmax (p = 0.0363), SUVmean (p = 0.0200) and CoV (p = 0.0139) of targeted lymph nodes as well as by CoV of primary tumors (p = 0.0173), MTVTOT (p = 0.0007), TLGWB (p = 0.0129) and stage (p = 0.0122). Using Kaplan-Meier analysis, OS was significantly better in patients with CoV of targeted lymph nodes ≤ 0.29 than those with CoV > 0.29 (p = 0.0147), meanwhile patients with CoV of primary tumors > 0.38 had a better prognosis compared to those with CoV ≤ 0.38 (p = 0.0137). Finally, we combined the CoV values of targeted lymph nodes and primary tumors in all possible arrangements and a statistically significant difference was found among the four survival curves (p = 0.0133). In particular, patients with CoV of targeted lymph nodes ≤ 0.29 and CoV of primary tumors > 0.38 had the best prognosis. Conclusions The CoV of targeted lymph nodes combined with the CoV of primary tumors can predict prognosis of NSCLC patients.

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.

The diagnostic value of metabolic, morphological and heterogeneous parameters of 18F-FDG PET/CT in mediastinal lymph node metastasis of non-small cell lung cancer

OBJECTIVES

To investigate the value of PET/CT metabolic, morphological and heterogeneous parameters in the diagnosis of 18F-FDG positive mediastinal lymph node metastasis in non-small cell lung cancer (NSCLC).

PATIENTS AND METHODS

A total of 156 patients with pathologically diagnosed NSCLC and underwent 18F-FDG PET/CT scans were enrolled in this study. Mediastinal lymph nodes with 18F-FDG uptake greater than the mediastinum were analyzed. The metabolic parameters of maximum and mean standardized uptake value (SUVmax, SUVmean), SUVratio (node SUVmax/mediastinum SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), morphological parameters of maximum short diameter (Dmin), CT values and metabolic heterogeneity parameter of coefficient of variation (COV) were measured. The performance of each parameter and their combinations for diagnosis of lymph node metastasis was evaluated through receiver operating characteristic (ROC) curves and binary logistic regression analysis.

RESULTS

There were 206 lymph nodes with pathological evidence included in the study, including 103 metastatic and 103 nonmetastatic nodes. The SUVmax, SUVmean, SUVratio, TLG, COV and Dmin of metastatic lymph nodes were significantly higher/greater than those in nonmetastatic ones (P < 0.05). ROC curve analysis revealed that the combination of SUVratio, Dmin and COV showed the highest diagnostic efficacy among all single and combined parameters, the area under the curve (AUC) was 0.907 (P = 0.000), these three parameters all increased the risk of lymph node metastasis, with odds ratios of 1.848, 1.293 and 1.258, respectively (all P < 0.05).

CONCLUSION

Heterogeneity parameter was helpful for the accurate distinction of mediastinal lymph node metastasis in NSCLC. The combination of the SUVratio, Dmin and COV could improve the diagnostic accuracy. Multiple-parameters analysis plays an important complementary role in the diagnosis of lymph node metastasis.

Diagnostic Value of Conventional PET Parameters and Radiomic Features Extracted from 18F-FDG-PET/CT for Histologic Subtype Classification and Characterization of Lung Neuroendocrine Neoplasms

Aim: To evaluate if conventional Positron emission tomography (PET) parameters and radiomic features (RFs) extracted by 18F-FDG-PET/CT can differentiate among different histological subtypes of lung neuroendocrine neoplasms (Lu-NENs). Methods: Forty-four naïve-treatment patients on whom 18F-FDG-PET/CT was performed for histologically confirmed Lu-NEN (n = 46) were retrospectively included. Manual segmentation was performed by two operators allowing for extraction of four conventional PET parameters (SUVmax, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG)) and 41 RFs. Lu-NENs were classified into two groups: lung neuroendocrine tumors (Lu-NETs) vs. lung neuroendocrine carcinomas (Lu-NECs). Lu-NETs were classified according to histological subtypes (typical (TC)/atypical carcinoid (AC)), Ki67-level, and TNM staging. The least absolute shrink age and selection operator (LASSO) method was used to select the most predictive RFs for classification and Pearson correlation analysis was performed between conventional PET parameters and selected RFs. Results: PET parameters, in particular, SUVmax (area under the curve (AUC) = 0.91; cut-off = 5.16) were higher in Lu-NECs vs. Lu-NETs (p < 0.001). Among RFs, HISTO_Entropy_log10 was the most predictive (AUC = 0.90), but correlated with SUVmax/SUVmean (r = 0.95/r = 0.94, respectively). No statistical differences were found between conventional PET parameters and RFs (p > 0.05) and TC vs. AC classification. Conventional PET parameters were correlated with N+ status in Lu-NETs. Conclusion: In our study, conventional PET parameters were able to distinguish Lu-NECs from Lu-NETs, but not TC from AC. RFs did not provide additional information.

Machine learning-based diagnostic method of pre-therapeutic 18F-FDG PET/CT for evaluating mediastinal lymph nodes in non-small cell lung cancer

OBJECTIVES

We aimed to find the best machine learning (ML) model using ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for evaluating metastatic mediastinal lymph nodes (MedLNs) in non-small cell lung cancer, and compare the diagnostic results with those of nuclear medicine physicians.

METHODS

A total of 1329 MedLNs were reviewed. Boosted decision tree, logistic regression, support vector machine, neural network, and decision forest models were compared. The diagnostic performance of the best ML model was compared with that of physicians. The ML method was divided into ML with quantitative variables only (MLq) and adding clinical information (MLc). We performed an analysis based on the ¹⁸F-FDG-avidity of the MedLNs.

RESULTS

The boosted decision tree model obtained higher sensitivity and negative predictive values but lower specificity and positive predictive values than the physicians. There was no significant difference between the accuracy of the physicians and MLq (79.8% vs. 76.8%, p = 0.067). The accuracy of MLc was significantly higher than that of the physicians (81.0% vs. 76.8%, p = 0.009). In MedLNs with low ¹⁸F-FDG-avidity, ML had significantly higher accuracy than the physicians (70.0% vs. 63.3%, p = 0.018).

CONCLUSION

Although there was no significant difference in accuracy between the MLq and physicians, the diagnostic performance of MLc was better than that of MLq or of the physicians. The ML method appeared to be useful for evaluating low metabolic MedLNs. Therefore, adding clinical information to the quantitative variables from ¹⁸F-FDG PET/CT can improve the diagnostic results of ML.

KEY POINTS

• Machine learning using two-class boosted decision tree model revealed the highest value of area under curve, and it showed higher sensitivity and negative predictive values but lower specificity and positive predictive values than nuclear medicine physicians. • The diagnostic results from machine learning method after adding clinical information to the quantitative variables improved accuracy significantly than nuclear medicine physicians. • Machine learning could improve the diagnostic significance of metastatic mediastinal lymph nodes, especially in mediastinal lymph nodes with low 18F-FDG-avidity.

Preoperative staging of the mediastinum is an essential and multidisciplinary task

Mediastinal staging is a crucial step in the management of patients with NSCLC. With the recent development of novel techniques, mediastinal staging has evolved from an activity of interest mainly for thoracic surgeons to a joint effort carried out by many specialists. In this regard, the debate of cases in MDT sessions is crucial for optimal management of patients. Current evidence-based clinical guidelines for preoperative NSCLC staging recommend that mediastinal staging should be performed with increasing invasiveness. Image-based techniques are the first approach, although they have limited accuracy and findings must be confirmed by pathology in almost all cases. In this setting, the advent of radiomics is promising. Invasive staging depends on procedural factors rather than diagnostic performance. The choice between endoscopy-based or surgical procedures should depend on the local expertise of each centre. As the extension of mediastinal disease in terms of number of involved lymph nodes and nodal stations affects prognosis and the choice of treatment, systematic samplings are preferred over random targeted samplings. Following this approach, a diagnosis of single mediastinal nodal involvement can be unreliable if all reachable mediastinal nodal stations have not been assessed. The performance of confirmatory mediastinoscopy after a negative endoscopy-based procedure is controversial but currently recommended. Current indications of invasive staging in patients with radiologically normal mediastinum have to be re-evaluated, especially for central tumour location.

The association between 18F-fluorodeoxyglucose PET intratumoral metabolic heterogeneity and pathological parameters in non-small cell lung cancer

OBJECTIVE

The aim of this study was to evaluate the association between intratumoral metabolic heterogeneity on F-fluorodeoxyglucose (F-FDG) PET imaging and the pathological type, differentiation and T stage of non-small cell lung cancer (NSCLC).

METHODS

Two hundred thirty-four consecutive patients who were performed pretreatment F-FDG PET/computed tomography and pathologically diagnosed as NSCLC were assessed retrospectively. Metabolic heterogeneity factor (MHF) derived from the volume-threshold function from 40 to 90% was calculated for primary lesions. The association between MHF and the pathological type, differentiation and T stage of NSCLC were analyzed, respectively.

RESULTS

The MHF values were statistically different among pathological types, differentiation and T stages (F = 17.611, 23.932 and 11.082, P all < 0.001). MHF showed a stepwise increase with the reduced degree of differentiation and increase of T stage. The trend analysis presented a strong positive relationship between MHF and T stage (P < 0.05), but a correlated inversely and strongly relationship was demonstrated between MHF and diffferentiation (P < 0.001). Moreover, multivariate ordinal logistic regression analysis showed that MHF was independently associated with tumor T stage and differentiation after adjusting for clinical factors.

CONCLUSION

MHF showed high association with pathological parameters, which can be used to accurately predict the biological behaviors of tumors from the molecular level thus to provide important biological information for tumor diagnosis and treatment.

Improved detection of metastatic lymph nodes in oesophageal squamous cell carcinoma by combined interpretation of fluorine-18-fluorodeoxyglucose positron-emission tomography/computed tomography

Background

We sought to evaluate the diagnostic performance of fluorine-18-fluorodeoxyglucose positron-emission tomography/computed tomography (¹⁸F-FDG PET/CT) in the detection of metastatic lymph nodes by combined interpretation of PET/CT images in patients with oesophageal squamous cell carcinoma.

Methods

Two hundred three patients with oesophageal squamous cell carcinoma underwent ¹⁸F-FDG PET/CT before oesophagectomy and lymph node dissection. Maximum standardized uptake value (SUV_max), mean Hounsfield unit (HU), short axis diameter (size), and visual CT attenuation (high, iso-, low) were evaluated on noncontrast CT and PET images following PET/CT scan. In this combined interpretation protocol, the high attenuated lymph nodes were considered benign, even if the SUV_max value was high. The diagnostic accuracy of each method was compared using the postoperative histologic result as a reference standard.

Results

A total of 1099 nodal stations were dissected and 949 nodal stations were proven to demonstrate metastasis. SUV_max and size of the malignant lymph nodes were higher than those of the benign nodes, and visual CT attenuation was significantly different among the two groups (P < 0.001). Using cutoff values of 2.6 for SUV_max and 10.2 mm for size, the combined interpretation of an SUV_max of more than 2.6 with iso- or low CT attenuation [area under the curve (AUC): 0.846, 95% confidence interval (CI): 0.824–0.867] showed significantly better diagnostic performance for detecting malignant lymph nodes than SUV_max only (AUC: 0.791, 95% CI: 0.766–0.815) and size (AUC: 0.693, 95% CI: 0.665–0.720) methods (P < 0.001) in a receiver operating characteristic curve analysis.

Conclusions

The diagnostic accuracy of PET/CT for nodal metastasis in oesophageal squamous cell carcinoma was improved by the combined interpretation of ¹⁸F-FDG uptake and visual CT attenuation pattern.

Diagnostic value of positron-emission tomography textural indices for malignancy of 18F-fluorodeoxyglucose-avid adrenal lesions

BACKGROUND

PET Textural indices could have an add-on diagnostic value for diagnosis of malignancy in patients with FDG-avid adrenal lesions.

METHODS

Consecutive patients referred for a FDG-PET/CT to our nuclear medicine department from June 2012 to June 2017 were retrospectively screened. Inclusion criteria were: patients with a FDG-avid adrenal lesion (uptake≥liver background); malignant/benign lesion confirmed histologically or with follow-up imaging examination. Pheochromocytomas were not included in the analysis. For each adrenal lesion, 5 quantitative PET parameters (SUV<inf>max</inf>, MTV, TLG, TLR<inf>max</inf> and TLRmean<inf>)</inf> were calculated. Thirty-seven textural indices were extracted using LIFEx software^®. Diagnostic performance to determine malignancy was assessed with a ROC analysis. Parameters with a significantly AUC>0.5 were selected and groups of highly correlated (r>0.8) parameters were created. A scoring system combining PET and textural indices was examined.

RESULTS

PET textural indices were calculated for 53 lesions (37 malignant, 16 benign). Three PET metabolic parameters (SUV<inf>max</inf>, TLR<inf>max</inf>, TLRmean) and 13 textural indices had an AUC>0.5. Seven groups of highly correlated parameters (r>0.8) were extracted. For PET parameters, SUV<inf>max</inf> had the best AUC (0.89 95% CI [0.79-0.98]; cut-off=7.0). For textural indices, ZLNU had the best AUC (0.87 95% CI [0.78-0.96]; cut-off=34.7) and specificity of 100%. Three scores combining the best four textural indices alone (Contrast<inf>GLCM</inf>, LRHGE, SZE and ZLNU) or with one PET parameters (SUV<inf>max</inf>, TLR<inf>max</inf>) were developed but did not increase the diagnostic performance (AUC≤0.89). ZLNU was the best parameter to distinguish primary adrenal cancer from adrenal metastases in malignant lesions (P<0.001).

CONCLUSIONS

Our study highlighted excellent diagnostic performance of several PET textural indices comparable to that of PET metabolic parameters. However, our results did not find any additional diagnostic value of textural indices when combined with metabolic parameters.

Utility of metabolic heterogeneity factor in differentiating malignant versus benign parotid uptake on 18F FDG PET-CT

Differentiation of benign and malignant parotid uptake on Fluorine 18 Fluro-Deoxy-Glucose Positron Emission Tomography-Computed Tomography (¹⁸F FDG PET-CT) is of paramount importance due to the poor prognosis of the later but usual quantitative measures such as standardized uptake value (SUV) are not reliable for this purpose. Metabolic heterogeneity, being a characteristic of malignant tumors, would potentially be able to make this distinction. In this study, seventy-one FDG-avid parotid lesions were retrospectively separated histologically into benign and malignant groups. The heterogeneity factor (HF) of all the lesions was then calculated and compared between the two groups. There was significant difference in HF between malignant (median -0.17) and benign group (median -0.03); P=0.0006. On receiver operating characteristic (ROC) analysis, a cut-off value of ≤ -0.06 for HF was associated with the highest sensitivity and specificity (sensitivity and specificity of 94.6% and 60.0%, respectively-AUC=0.789; P=0.0001). Hence, it was concluded that HF is a reliable value in distinguishing benign from malignant parotid uptake on ¹⁸F FDG PET-CT.

Prediction of pathological nodal involvement by CT-based Radiomic features of the primary tumor in patients with clinically node-negative peripheral lung adenocarcinomas

PURPOSE

The purpose of this study was to investigate the potential of computed tomography (CT) based radiomic features of primary tumors to predict pathological nodal involvement in clinically node-negative (N0) peripheral lung adenocarcinomas.

METHODS

A total of 187 patients with clinical N0 peripheral lung adenocarcinomas who underwent preoperative CT scan and subsequently received systematic lymph node dissection were retrospectively reviewed. 219 quantitative 3D radiomic features of primary lung tumor were extracted; meanwhile, nine radiological semantic features were evaluated. Univariate and multivariate logistic regression analysis were used to explore the role of these features in predicting pathological nodal involvement. The areas under the ROC curves (AUCs) were compared between multivariate logistic regression models.

RESULTS

A total of 153 patients had pathological N0 status and 34 had pathological lymph node metastasis. On univariate analysis, fissure attachment and 17 radiomic features were significantly associated with pathological nodal involvement. Multivariate analysis revealed that semantic features of pleural retraction (P = 0.048) and fissure attachment (P = 0.023) were significant predictors of pathological nodal involvement (AUC = 0.659); and the radiomic feature F185 (Histogram SD Layer 1) (P = 0.0001) was an independent prognostic factor of pathological nodal involvement (AUC = 0.73). A logistic regression model produced from combining radiomic feature and semantic feature showed the highest AUC of 0.758 (95% CI: 0.685-0.831), and the AUC value computed by fivefold cross-validation method was 0.737 (95% CI: 0.73-0.744).

CONCLUSIONS

Features derived on primary lung tumor described by semantic and radiomic could provide information of pathological nodal involvement in clinical N0 peripheral lung adenocarcinomas.

Prognostic significance of 18F-fluorodeoxyglucose uptake of bone marrow measured on positron emission tomography in patients with small cell lung cancer

OBJECTIVES

We investigated whether ¹⁸F-fluorodeoxyglucse (FDG) uptake of bone marrow (BM) on positron emission tomography/computed tomography (PET/CT) has implications for predicting clinical outcomes in patients with small cell lung cancer (SCLC).

METHODS

We retrospectively enrolled 70 SCLC patients who underwent FDG PET/CT prior to treatment. On PET/CT, maximum FDG uptake of all tumor lesions (Tmax), coefficient of variation (COV) of FDG uptake of primary tumor, and mean FDG uptake of BM (BM SUV) were measured. The relationships of BM SUV with PET/CT parameters of SCLC and serum markers were evaluated. Univariate and multivariate analyses were performed to assess the significance of BM SUV for predicting progression-free survival (PFS) and overall survival (OS).

RESULTS

BM SUV had significant positive correlations with Tmax, COV of primary tumor, white blood cell count, and serum C-reactive protein level (p < .05). On univariate analysis, BM SUV showed significant association with only PFS (p = .006). On multivariate analysis, Veterans Administration Lung Cancer Study Group (VALSG) stage, N stage, M stage, Tmax, and BM SUV were independent prognostic factors for PFS (p < .05) and, for OS, VALSG stage and M stage were independent prognostic factors (p < .05). Among patients with limited disease, patients with high FDG uptake of BM had significantly worse PFS than did those with low FDG uptake of BM (p < .05), but, there was no significant difference in PFS between patients with extensive disease and patients with limited disease and high FDG uptake of BM (p > .05).

CONCLUSION

FDG uptake of BM was an independent predictor of disease progression in SCLC patients. Patients with limited disease and high FDG uptake of BM had similar PFS to those with extensive disease.

PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology

Imaging with positron emission tomography (PET)/computed tomography (CT) is crucial in the management of cancer because of its value in tumor staging, response assessment, restaging, prognosis and treatment responsiveness prediction. In the last years, interest has grown in texture analysis which provides an "in-vivo" lesion characterization, and predictive information in several malignances including NSCLC; however several drawbacks and limitations affect these studies, especially because of lack of standardization in features calculation, definitions and methodology reporting. The present paper provides a comprehensive review of literature describing the state-of-the-art of FDG-PET/CT texture analysis in NSCLC, suggesting a proposal for harmonization of methodology.

Magnetic resonance (MR) imaging for tumor staging and definition of tumor volumes on radiation treatment planning in nonsmall cell lung cancer: A prospective radiographic cohort study of single center clinical outcome

We investigate the impact of magnetic resonance (MR) on the staging and radiotherapy planning for patients with nonsmall cell lung cancer (NSCLC).A total of 24 patients with NSCLC underwent MRI, which was fused with radiotherapy planning CT using rigid registration. Gross tumor volume (GTV) was delineated not only according to CT image alone (GTVCT), but also based on both CT and MR image (GTVCT/MR). For each patient, 2 conformal treatment plans were made according to GTVCT and GTVCT/MR, respectively. Dose-volume histograms (DVH) for lesion and normal organs were generated using both GTVCT and GTVCT/MR treatment plans. All patients were irradiated according to GTVCT/MR plan.Median volume of the GTVCT/MR and GTVCT were 105.42 cm and 124.45 cm, respectively, and the mean value of GTVCT/MR was significantly smaller than that of GTVCT (145.71 ± 145.04 vs 174.30 ± 150.34, P < 0.01). Clinical stage was modified in 9 patients (37.5%). The objective response rate (ORR) was 83.3% and the l-year overall survival (OS) was 87.5%.MR is a useful tool in radiotherapy treatment planning for NSCLC, which improves the definition of tumor volume, reduces organs at risk dose and does not increase the local recurrence rate.

An Algorithm of Image Heterogeneity with Contrast-Enhanced Ultrasound in Differential Diagnosis of Solid Thyroid Nodules

Enhancement heterogeneity on contrast-enhanced ultrasonography (CEUS) is used to differentiate between benign and malignant thyroid nodules. In this study, we used an algorithm to quantify enhancement heterogeneity of solid thyroid nodules on CEUS. The heterogeneity value (HV) is calculated as standard deviation/mean intensity × 100 (using Adobe Photoshop). The heterogeneity ratio (HR) is calculated as the ratio of the HV of the nodule to that of the surrounding parenchyma. Three phases-ascending, peak and descending phases-were studied. HV values at ascending (HV_a) and peak (HV_p) phases were significantly higher in malignant nodules than in benign nodules (95.57 ± 43.87 vs. 73.06 ± 44.04, p = 0.009, and 32.53 ± 10.73 vs. 26.44 ± 8.25, p = 0.002, respectively). HR_a, HR_p and HR_d were significantly higher in malignant nodules than in benign nodules (1.93 ± 1.03 vs. 1.00 ± 0.47, p = 0.000, 1.43 ± 0.51 vs. 1.09 ± 0.28, p = 0.000, and 1.33 ± 0.40 vs. 1.08 ± 0.33, p = 0.001, respectively). HR_a achieved optimal diagnostic performance on receiver operating characteristic curve analysis. The algorithm used for assessment of image heterogeneity on CEUS examination may be a useful adjunct to conventional ultrasound for differential diagnosis of solid thyroid nodules.

Value of 18F-FDG heterogeneity for discerning metastatic from benign lymph nodes in nasopharyngeal carcinoma patients with suspected recurrence

OBJECTIVE

This study investigated the value of fluorine-18 fludeoxyglucose (¹⁸F-FDG) heterogeneity as an indicator of metastatic lymph nodes (LNs) in patients with nasopharyngeal carcinoma (NPC). We further assessed whether addition of this parameter improves diagnostic performance beyond that provided by maximum standardized uptake value (SUV_max).

METHODS

We analyzed 74 LNs that were suspicious for metastasis. These LNs were measured for coefficient of variation (CV) of ¹⁸F-FDG uptake, which was used as a parameter for ¹⁸F-FDG heterogeneity.

RESULTS

Multivariate logistic regression analyses revealed that a high CV (hazard ratio, 20.97; 95% confidence interval, 2.26-194.62; p = 0.007) was an independent predictor of metastatic LNs. However, receiver-operating characteristic curve analysis (p = 0.278) and net reclassification (p = 0.539) were unable to show improved diagnostic performance by addition of CV to SUV_max.

CONCLUSION

High CV of ¹⁸F-FDG uptake is an independent risk factor for metastatic LNs in patients with NPC displaying suspicious LNs following treatment. Advances in knowledge: Heterogeneity of ¹⁸F-FDG uptake has a potential as a biomarker of metastatic LNs.

Ratio of Mediastinal Lymph Node SUV to Primary Tumor SUV in 18F-FDG PET/CT for Nodal Staging in Non-Small-Cell Lung Cancer

PURPOSE

Following determination of the maximum standardized uptake values (SUVmax) of the mediastinal lymph nodes (SUV-LN) and of the primary tumor (SUV-T) on ¹⁸F-FDG PET/CT in patients with non-small-cell lung cancer (NSCLC), the aim of the study was to determine the value of the SUV-LN/SUV-T ratio in lymph node staging in comparison with that of SUV-LN.

METHODS

We retrospectively reviewed a total of 289 mediastinal lymph node stations from 98 patients with NSCLC who were examined preoperatively for staging and subsequently underwent pathologic studies of the mediastinal lymph nodes. We determined SUV-LN and SUV-R for each lymph node station on ¹⁸F-FDG PET/CT and then classified each station into one of three groups based on SUV-T (low, medium and high SUV-T groups). Diagnostic performance was assessed based on receiver operating characteristic (ROC) curve analysis, and the optimal cut-off values that would best discriminate metastatic from benign lymph nodes were determined for each method.

RESULTS

The average of SUV-R of malignant lymph nodes was significantly higher than that of benign lymph nodes (0.79 ± 0.45 vs. 0.36 ± 0.23, P < 0.0001). In the ROC curve analysis, the area under the curve (AUC) of SUV-R was significantly higher than that of SUV-LN in the low SUV-T group (0.885 vs. 0.810, P = 0.019). There were no significant differences between the AUCs of SUV-LN and of SUV-R in the medium and high SUV-T groups. The optimal cut-off value for SUV-R in the low SUV-T group was 0.71 (sensitivity 87.5 %, specificity 85.9 %).

CONCLUSIONS

The SUV-R performed well in distinguishing between metastatic and benign lymph nodes. In particular, SUV-R was found to have a better diagnostic performance than SUV-LN in the low SUV-T group.

Diagnostic value of metabolic heterogeneity as a reliable parameter for differentiating malignant parotid gland tumors

OBJECTIVE

Exact classifying between malignant and benign tumors in the parotid gland is important because the cancer has relatively poor prognosis. There have been several studies that F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) can differentiate between malignant and benign parotid gland tumors. However, the role of FDG PET is still controversial because many benign parotid gland tumors, such as Warthin's tumor and pleomorphic adenoma, show high FDG uptake. We hypothesized that metabolic heterogeneity would differentiate malignant parotid tumors because tumoral heterogeneity is an important characteristic in the malignancies.

METHODS

From January 2010 to April 2015, we retrospectively reviewed the 46 patients who showed FDG uptake at the parotid gland. To differentiate malignant parotid gland tumors, we obtained maximum SUV and mean SUV. Metabolic tumor volume and total lesion glycolysis were measured as metabolic volumetric parameters. We also included heterogeneity parameters of FDG PET such as heterogeneity factor (HF) and the coefficient of variation for all patients.

RESULTS

There was significant difference of HF between malignant (-0.30 ± 0.25; range -0.937 to -0.084) and benign parotid gland tumors (-0.06 ± 0.05; range -0.291 to -0.012; p < 0.0001). In receiver operating characteristic analysis, when ≤-0.084 was used as the cut-off value for HF, the sensitivity and specificity were 100 % (95 % CI 81.5-100) and 89.2 % (95 % CI 71.8-97.7), respectively. HF showed the highest area under the curve of 0.947 among the parameters. In logistic regression analysis, the HF was the most powerful factor for differentiation of the parotid gland tumors (p = 0.002).

CONCLUSIONS

Our results suggest that HF can be utilized as a reliable and non-invasive method for differentiation of malignant and benign parotid gland tumors.

A phase II clinical trial to investigate the effect of pioglitazone on (18)F-FDG uptake in malignant lesions

BACKGROUND

We found that (18)F-2-fluoro-2-deoxy-D-glucose ((18)F-FDG) uptake in malignant lesion was enhanced, and it was decreased in the inflammatory lesion after the use of peroxisome proliferator activated receptor-γ (PPAR-γ) agonist in our previous preclinical study. The purpose of this study was to investigate the effect of PPAR-γ agonist on malignant lesions in clinical (18)F-FDG positron emission tomography/computed tomography (PET/CT) imaging.

METHODS

Forty-three patients were enrolled in this prospective study. We received the approval for the investigator-initiated trials for a phase II human clinical trial from the Korean Food and Drug Administration. On the first day, (18)F-FDG PET/CT images were acquired from patients without administration of pioglitazone (PIO), which is a PPAR-γ agonist. On the next day, (18)F-FDG PET/CT images were acquired once again from the same patients after administration of PIO. We measured the (18)F-FDG uptake in malignant lesions or inflammatory lesions from two (18)F-FDG PET/CT images. Four different PET parameters were used to compare between the two studies: SUVmax, SUVmean, average activity over 30 % of the isocontour (isocontour, Bq/mL), and isocontour-mediastinal activity (Bq/mL). Additionally, we classified the patients into two groups: the responder or non-responder group according to the presence of PIO effect on skeletal muscle. Furthermore, PET parameters of malignant lesions were analyzed based on the type of malignancy and were compared with those of inflammatory lesions.

RESULTS

All four PET parameters of malignant lesions in the responder group showed increasing patterns after the use of PIO. In the subgroup analysis, the similar pattern was observed in gastrointestinal cancer. In hepatobiliary and pancreatic cancer, SUVmean and isocontour showed statistically significant increase in the presence of PIO. On the other hand, in the non-responder group, all four PET parameters showed decreasing patterns in both malignant and inflammatory lesions after the use of PIO. There was no statistically significant difference in PET parameters of malignant lesions in the non-responder group.

CONCLUSIONS

In this study, we found that PIO had the potential to increase (18)F-FDG uptake of malignant lesions in the patients who showed PIO effect on skeletal muscle. Contrary to our preclinical studies, clinical results had limitations to evaluate malignant lesions in non-responder group. Further larger-scale studies are necessary to elucidate the potential role of PIO on (18)F-FDG uptake in malignant or inflammatory lesions.

TRIAL REGISTRATION

The test for safety and effectiveness of the new efficacy of Pioglitazone to diagnose the malignant tumor and inflammation in F-18 FDG positron emission tomography (PET) study, 12029.

Prognostic value of volumetric parameters of (18)F-FDG PET in non-small-cell lung cancer: a meta-analysis

PURPOSE

We conducted a comprehensive systematic review of the literature on volumetric parameters from (18)F-FDG PET and a meta-analysis of the prognostic value of metabolic tumour volume (MTV) and total lesion glycolysis (TLG) in patients with lung cancer.

METHODS

A systematic search of MEDLINE and EMBASE was performed using the keywords "positron emission tomography (PET)", "lung cancer", and "volume". Inclusion criteria were: (18)F-FDG PET used as an initial imaging tool; studies limited to non-small-cell lung cancer (NSCLC); volume measurement of lung cancer; patients who had not undergone surgery, chemotherapy, or radiotherapy before the PET scan; and studies that reported survival data. Event-free survival and overall survival were evaluated as outcomes. The impact of MTV and TLG on survival was measured in terms of the hazard ratio (HR) effect size. Data from each study were analysed using Review Manager 5.2.

RESULTS

Thirteen eligible studies including 1,581 patients were analysed. Patients with high MTV showed a worse prognosis with an HR of 2.71 (95% CI 1.82 - 4.02, p < 0.00001) for adverse events and an HR of 2.31 (95% CI 1.54 - 3.47, p < 0.00001) for death. Patients with high TLG also showed a worse prognosis with an HR of 2.35 (95% CI 1.91 - 2.89, p < 0.00001) for adverse events and an HR of 2.43 (95% CI 1.89 - 3.11, p < 0.00001) for death. The prognostic value of MTV and TLG remained significant in a subgroup analysis according to TNM stage as well as the methods for defining cut-off values and tumour delineation.

CONCLUSION

Volumetric parameters from (18)F-FDG PET are significant prognostic factors for outcome in patients with NSCLC. Patients with a high MTV or TLG are at higher risk of adverse events and death. MTV and TLG were significant prognostic factors in patients with TNM stage I/II and stage III/IV NSCLC.

Autoclustering of Non-small Cell Lung Carcinoma Subtypes on (18)F-FDG PET Using Texture Analysis: A Preliminary Result

PURPOSE

Texture analysis on (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) scan is a relatively new imaging analysis tool to evaluate metabolic heterogeneity. We analyzed the difference in textural characteristics between non-small cell lung carcinoma (NSCLC) subtypes, namely adenocarcinoma (ADC) and squamous cell carcinoma (SqCC).

METHODS

Diagnostic (18)F-FDG PET/computed tomography (CT) scans of 30y patients (median age, 67; range, 42-88) with NSCLC (17 ADC and 13 SqCC) were retrospectively analyzed. Regions of interest were manually determined on selected transverse image containing the highest SUV value in tumors. Texture parameters were extracted by histogram-based algorithms, absolute gradient-based algorithms, run-length matrix-based algorithms, co-occurrence matrix-based algorithms, and autoregressive model-based algorithms. Twenty-four out of hundreds of texture features were selected by three algorithms: Fisher coefficient, minimization of both classification error probability and average correlation, and mutual information. Automated clustering of tumors was based on the most discriminating feature calculated by linear discriminant analysis (LDA). Each tumor subtype was determined by histopathologic examination after biopsy and surgery.

RESULTS

Fifteen texture features had significant different values between ADC and SqCC. LDA with 24 automate-selected texture features accurately clustered between ADC and SqCC with 0.90 linear separability. There was no high correlation between SUVmax and texture parameters (|r| ≤ 0.62).

CONCLUSION

Each subtype of NSCLC tumor has different metabolic heterogeneity. The results of this study support the potential of textural parameters on FDG PET as an imaging biomarker.