[18F]FDG-PET/CT texture analysis in thyroid incidentalomas: preliminary results

Positron Emission Tomography/Computed Tomography in Thyroid Cancer: An Updated Review

PET/computed tomography (CT) is a valuable hybrid imaging modality for the evaluation of thyroid cancer, potentially impacting management decisions. 18F-fluorodeoxyglucose (FDG) PET/CT has proven utility for recurrence evaluation in differentiated thyroid cancer (DTC) patients having thyroglobulin elevation with negative iodine scintigraphy. Aggressive histologic subtypes such as anaplastic thyroid cancer shower higher FDG uptake. 18F-FDOPA is the preferred PET tracer for medullary thyroid cancer. Fibroblast activation protein inhibitor and arginylglycylaspartic acid -based radiotracers have emerged as promising PET agents for radioiodine refractory DTC patients with the potential for theranostic application.

Application of radiomics and machine learning to thyroid diseases in nuclear medicine: a systematic review

BACKGROUND

In the last years growing evidences on the role of radiomics and machine learning (ML) applied to different nuclear medicine imaging modalities for the assessment of thyroid diseases are starting to emerge. The aim of this systematic review was therefore to analyze the diagnostic performances of these technologies in this setting.

METHODS

A wide literature search of the PubMed/MEDLINE, Scopus and Web of Science databases was made in order to find relevant published articles about the role of radiomics or ML on nuclear medicine imaging for the evaluation of different thyroid diseases.

RESULTS

Seventeen studies were included in the systematic review. Radiomics and ML were applied for assessment of thyroid incidentalomas at 18 F-FDG PET, evaluation of cytologically indeterminate thyroid nodules, assessment of thyroid cancer and classification of thyroid diseases using nuclear medicine techniques.

CONCLUSION

Despite some intrinsic limitations of radiomics and ML may have affect the results of this review, these technologies seem to have a promising role in the assessment of thyroid diseases. Validation of preliminary findings in multicentric studies is needed to translate radiomics and ML approaches in the clinical setting.

Prediction of Malignant Thyroid Nodules Using 18 F-FDG PET/CT-Based Radiomics Features in Thyroid Incidentalomas

OBJECTIVE

The purpose of the current study was to evaluate the diagnostic performances of 18 F-FDG PET/CT-based radiomics features for prediction of malignant thyroid nodules (TNs) in thyroid incidentaloma (TI).

METHODS

PubMed, Cochrane database, and EMBASE database, from the earliest available date of indexing through December 31, 2022, were searched for studies evaluating diagnostic performance of 18 F-FDG PET/CT-based radiomics features for prediction of malignant TNs in TI. We determined the sensitivities and specificities across studies, calculated positive and negative likelihood ratios (LRs; positive and negative LRs), and estimated pooled area under the curve.

RESULTS

Across 5 studies (518 patients), the pooled sensitivity of 18 F-FDG PET/CT was 0.77 (95% confidence interval [CI], 0.67-0.84), and a pooled specificity was 0.67. Likelihood ratio syntheses gave an overall positive LR of 2.3 (95% CI, 1.5-3.6) and negative LR of 0.35 (95% CI, 0.26-0.47). The pooled diagnostic odds ratio was 7 (95% CI, 4-12). The pooled area under the curve of fixed effects was 0.763 (95% CI, 0.736-0.791), and that of random effects was 0.763 (95% CI, 0.721-0.805).

CONCLUSION

18 F-FDG PET/CT-based radiomics features showed a good diagnostic performance for prediction of malignant TNs in TI.

PET/CT May Assist in Avoiding Pointless Thyroidectomy in Indeterminate Thyroid Nodules: A Narrative Review

Indeterminate thyroid nodules (ITN) are commonly encountered among the general population, with a malignancy rate of 10 to 40%. However, many patients may be overtreated with futile surgery for benign ITN. To avoid unnecessary surgery, PET/CT scan is a possible alternative to help differentiate between benign and malignant ITN. In this narrative review, the major results and limitations of the most recent studies on PET/CT efficacy (from PET/CT visual assessment to quantitative PET parameters and recent radiomic features analysis) and on cost-effectiveness (compared to other alternatives (such as surgery)) are presented. PET/CT can reduce futile surgery with visual assessment (around 40%; if ITN ≥ 10 mm). Moreover, PET/CT conventional parameters and radiomic features extracted from PET/CT imaging can be associated together in a predictive model to rule out malignancy in ITN, with a high NPV (96%) when certain criteria are met. Even though promising results were obtained in these recent PET/CT studies, further studies are needed to enable PET/CT to become the definitive diagnostic tool once a thyroid nodule is identified as indeterminate.

Role of PET/Computed Tomography in Elderly Thyroid Cancer: Tumor Biology and Clinical Management

PET/computed tomography (CT) studies can be potentially useful in elderly thyroid carcinoma patients for exploring the disease biology, especially in metastatic setting and thereby directing appropriate therapeutic management on case-to-case basis, adopting nuclear theranostics, and disease prognostication. With the availability of multiple PET radiopharmaceuticals, it would be worthwhile to evolve and optimally use FDG and the other non-fluorodeoxyglucose and investigational PET/CT tracers as per the clinical situation and need and thereby define their utilities in a given case scenario. In this regard, (I) differentiated thyroid carcinoma (DTC) including radioiodine refractory disease, poorly differentiated thyroid cancer (PDTC) and TENIS, (II) medullary thyroid carcinoma (MTC), (III) anaplastic carcinoma and (IV) Primary thyroid lymphoma (PTL) should be viewed and dealt separately.

Radiomics in Oncological PET Imaging: A Systematic Review—Part 1, Supradiaphragmatic Cancers

Radiomics is an upcoming field in nuclear oncology, both promising and technically challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia and assess its quality, we performed a literature search in the PubMed database up to 18 February 2022. Inclusion criteria were: studies based on human data; at least one specified tumor type; supradiaphragmatic malignancy; performing radiomics on PET imaging. Exclusion criteria were: studies only based on phantom or animal data; technical articles without a clinically oriented question; fewer than 30 patients in the training cohort. A review database containing PMID, year of publication, cancer type, and quality criteria (number of patients, retrospective or prospective nature, independent validation cohort) was constructed. A total of 220 studies met the inclusion criteria. Among them, 119 (54.1%) studies included more than 100 patients, 21 studies (9.5%) were based on prospectively acquired data, and 91 (41.4%) used an independent validation set. Most studies focused on prognostic and treatment response objectives. Because the textural parameters and methods employed are very different from one article to another, it is complicated to aggregate and compare articles. New contributions and radiomics guidelines tend to help improving quality of the reported studies over the years.

Radiomics Analysis of [18F]FDG PET/CT Thyroid Incidentalomas: How Can It Improve Patients’ Clinical Management? A Systematic Review from the Literature

Background: We performed a systematic review of the literature to provide an overview of the application of PET-based radiomics of [18F]FDG-avid thyroid incidentalomas and to discuss the additional value of PET volumetric parameters and radiomic features over clinical data. Methods: The most relevant databases were explored using an algorithm constructed based on a combination of terms related to our subject and English-language articles published until October 2021 were considered. Among the 247 identified articles, 19 studies were screened for eligibility and 11 met the criteria, with 4 studies including radiomics analyses. Results: We summarized the available literature based on a study of PET volumetric parameters and radiomics. Ten articles provided accurate details about volumetric parameters and their prospective value in tumour assessment. We included the data provided by these articles in a sub-analysis, but could not obtain statistically relevant results. Four publications analyzed the diagnostic potential of radiomics and the possibility of creating precise predictive models, their corresponding quality score being assessed. Conclusions: The use of PET volumetric parameters and radiomics analysis in patients with [18F]FDG-avid thyroid incidentalomas outlines a great prospect in diagnosis and stratification of patients with malignant nodules and may represent a way of limiting the need for unnecessary invasive procedures; however, further studies need to be performed for a standardization of the method.

Quantitative classification and radiomics of [18F]FDG-PET/CT in indeterminate thyroid nodules

PURPOSE

To evaluate whether quantitative [¹⁸F]FDG-PET/CT assessment, including radiomic analysis of [¹⁸F]FDG-positive thyroid nodules, improved the preoperative differentiation of indeterminate thyroid nodules of non-Hürthle cell and Hürthle cell cytology.

METHODS

Prospectively included patients with a Bethesda III or IV thyroid nodule underwent [¹⁸F]FDG-PET/CT imaging. Receiver operating characteristic (ROC) curve analysis was performed for standardised uptake values (SUV) and SUV-ratios, including assessment of SUV cut-offs at which a malignant/borderline neoplasm was reliably ruled out (≥ 95% sensitivity). [¹⁸F]FDG-positive scans were included in radiomic analysis. After segmentation at 50% of SUV_peak, 107 radiomic features were extracted from [¹⁸F]FDG-PET and low-dose CT images. Elastic net regression classifiers were trained in a 20-times repeated random split. Dimensionality reduction was incorporated into the splits. Predictive performance of radiomics was presented as mean area under the ROC curve (AUC) across the test sets.

RESULTS

Of 123 included patients, 84 (68%) index nodules were visually [¹⁸F]FDG-positive. The malignant/borderline rate was 27% (33/123). SUV-metrices showed AUCs ranging from 0.705 (95% CI, 0.601-0.810) to 0.729 (0.633-0.824), 0.708 (0.580-0.835) to 0.757 (0.650-0.864), and 0.533 (0.320-0.747) to 0.700 (0.502-0.898) in all (n = 123), non-Hürthle (n = 94), and Hürthle cell (n = 29) nodules, respectively. At SUV_max, SUV_peak, SUV_max-ratio, and SUV_peak-ratio cut-offs of 2.1 g/mL, 1.6 g/mL, 1.2, and 0.9, respectively, sensitivity of [¹⁸F]FDG-PET/CT was 95.8% (95% CI, 78.9-99.9%) in non-Hürthle cell nodules. In Hürthle cell nodules, cut-offs of 5.2 g/mL, 4.7 g/mL, 3.4, and 2.8, respectively, resulted in 100% sensitivity (95% CI, 66.4-100%). Radiomic analysis of 84 (68%) [¹⁸F]FDG-positive nodules showed a mean test set AUC of 0.445 (95% CI, 0.290-0.600) for the PET model.

CONCLUSION

Quantitative [¹⁸F]FDG-PET/CT assessment ruled out malignancy in indeterminate thyroid nodules. Distinctive, higher SUV cut-offs should be applied in Hürthle cell nodules to optimize rule-out ability. Radiomic analysis did not contribute to the additional differentiation of [¹⁸F]FDG-positive nodules.

TRIAL REGISTRATION NUMBER

This trial is registered with ClinicalTrials.gov: NCT02208544 (5 August 2014), https://clinicaltrials.gov/ct2/show/NCT02208544 .

Comparison between Two Different Scanners for the Evaluation of the Role of 18F-FDG PET/CT Semiquantitative Parameters and Radiomics Features in the Prediction of Final Diagnosis of Thyroid Incidentalomas

The aim of this study was to compare two different tomographs for the evaluation of the role of semiquantitative PET/CT parameters and radiomics features (RF) in the prediction of thyroid incidentalomas (TIs) at ¹⁸F-FDG imaging. A total of 221 patients with the presence of TIs were retrospectively included. After volumetric segmentation of each TI, semiquantitative parameters and RF were extracted. All of the features were tested for significant differences between the two PET scanners. The performances of all of the features in predicting the nature of TIs were analyzed by testing three classes of final logistic regression predictive models, one for each tomograph and one with both scanners together. Some RF resulted significantly different between the two scanners. PET/CT semiquantitative parameters were not able to predict the final diagnosis of TIs while GLCM-related RF (in particular GLCM entropy_log2 e GLCM entropy_log10) together with some GLRLM-related and GLZLM-related features presented the best predictive performances. In particular, GLCM entropy_log2, GLCM entropy_log10, GLZLM SZHGE, GLRLM HGRE and GLRLM HGZE resulted the RF with best performances. Our study enabled the selection of some RF able to predict the final nature of TIs discovered at ¹⁸F-FDG PET/CT imaging. Classic semiquantitative and volumetric PET/CT parameters did not reveal these abilities. Furthermore, a good overlap in the extraction of RF between the two scanners was underlined.

Characterization of focal hypermetabolic thyroid incidentaloma: An analysis with F-18 fluorodeoxyglucose positron emission tomography/computed tomography parameters

BACKGROUND

Incidentally found thyroid tumor (thyroid incidentaloma, TI) on F-18 fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET-CT) is reported in 2.5%-5% of patients being investigated for non-thyroid purposes. Up to 50% of these cases have been diagnosed to be malignant by cytological/histological results. Ultrasonography (US) and fine-needle aspiration cytology are recommended for thyroid nodules with high FDG uptake (hypermetabolism) that are 1 cm or greater in size. It is important to accurately determine whether a suspicious hypermetabolic TI is malignant or benign.

AIM

To distinguish malignant hypermetabolic TIs from benign disease by analyzing F-18 FDG PET-CT parameters and to identify a cut-off value.

METHODS

Totally, 12761 images of patients who underwent F-18 FDG PET-CT for non-thyroid purposes at our hospital between January 2016 and December 2020 were retrospectively reviewed, and 339 patients [185 men (mean age: 68 ± 11.2) and 154 women (mean age: 63 ± 15.0)] were found to have abnormal, either focal or diffuse, thyroid FDG uptake. After a thorough review of their medical records, US, and cytological/histological reports, 46 eligible patients with focal hypermetabolic TI were included in this study. The TIs were categorized as malignant and benign according to the cytological/histological reports, and four PET parameters [standardized uptake value (SUV)_max, SUV_peak, SUV_mean, and metabolic tumor volume (MTV)] were measured on FDG PET-CT. Total lesion glycolysis (TLG) was calculated by multiplying the SUV_mean by MTV. Both parametric and non-parametric methods were used to compare the five parameters between malignant and benign lesions. Receiver operating characteristic (ROC) curve analysis was performed to identify a cut-off value.

RESULTS

Each of the 46 patients [12 men (26.1%; mean age: 62 ± 13.1 years) and 34 women (73.9%; mean age: 60 ± 12.0 years)] with focal hypermetabolic TIs had one focal hypermetabolic TI. Among them, 26 (56.5%) were malignant and 20 (43.5%) were benign. SUV_max, SUV_peak, SUV_mean, and TLG were all higher in malignant lesions than benign ones, but the difference was statistically significant (P = 0.012) only for SUV_max. There was a positive linear correlation (r = 0.339) between SUV_max and the diagnosis of malignancy. ROC curve analysis for SUV_max revealed an area under the curve of 0.702 (P < 0.05, 95% confidence interval: 0.550-0.855) and SUV_max cut-off of 8.5 with a sensitivity of 0.615 and a specificity of 0.789.

CONCLUSION

More than half of focal hypermetabolic TIs on F-18 FDG PET-CT were revealed as malignant lesions, and SUV_max was the best parameter for discriminating between malignant and benign disease. Unexpected focal hypermetabolic TIs with the SUV_max above the cut-off value of 8.5 may have a greater than 70% chance of malignancy; therefore, further active assessment is required.

Radiomics analysis improves 18FDG PET/CT-based risk stratification of cytologically indeterminate thyroid nodules

PURPOSE

As ~25% of cytologically indeterminate thyroid nodules harbour malignancy, diagnostic lobectomy is still performed in many cases. ¹⁸FDG PET/CT rules out malignancy in visually negative nodules; however, none of the currently available interpretation criteria differentiates malignant from benign ¹⁸FDG-avid nodules. We evaluated the ability of PET metrics and radiomics features (RFs) to predict final diagnosis of ¹⁸FDG-avid cytologically indeterminate thyroid nodules.

METHODS

Seventy-eight patients were retrospectively included. After volumetric segmentation of each thyroid lesion, 4 PET metrics and 107 RFs were extracted. A logistic regression was performed including thyroid stimulating hormone, PET metrics, and RFs to assess their predictive performance. A linear combination of the resulting parameters generated a radiomics score (RS) that was matched with cytology classes (Bethesda III and IV) and compared with final diagnosis.

RESULTS

Two RFs (shape_Sphericity and glcm_Autocorrelation) differentiated malignant from benign lesions. A predictive model integrating RS and cytology classes effectively stratified the risk of malignancy. The prevalence of thyroid cancer increased from 5 to 37% and 79% in accordance with the number (score 0, 1 or 2, respectively) of positive biomarkers.

CONCLUSIONS

Our multiparametric model may be useful for reducing the number of diagnostic lobectomies with advantages in terms of costs and quality of life for patients.

Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms

Endocrine neoplasms remain a great threat to human health. It is extremely important to make a clear diagnosis and timely treatment of endocrine tumors. Machine learning includes radiomics, which has long been utilized in clinical cancer research. Radiomics refers to the extraction of valuable information by analyzing a large amount of standard data with high-throughput medical images mainly including computed tomography, positron emission tomography, magnetic resonance imaging, and ultrasound. With the quantitative imaging analysis and model building, radiomics can reflect specific underlying characteristics of a disease that otherwise could not be evaluated visually. More and more promising results of radiomics in oncological practice have been seen in recent years. Radiomics may have the potential to supplement traditional imaging analysis and assist in providing precision medicine for patients. Radiomics had developed rapidly in endocrine neoplasms practice in the past decade. In this review, we would introduce the general workflow of radiomics and summarize the applications and developments of radiomics in endocrine neoplasms in recent years. The limitations of current radiomic research studies and future development directions would also be discussed.

Characteristics of malignant thyroid lesions on [18F] fluorodeoxyglucose (FDG)-Positron emission tomography (PET)/Computed tomography (CT)

Objectives

To determine the imaging variables that can best differentiate malignant from benign thyroid lesions incidentally found on F-18 FDG PET/CT scans.

Methods

All F-18 FDG PET/CT studies starting from 2011 to end of 2016 were reviewed for incidental thyroid lesions or metabolic abnormalities. Only patients who were found to have FNAB or histopathology were included. Patients with known thyroid malignancy were excluded. Patients were analyzed for age, sex, SUVmax, non-enhanced CT tissue density in mean Hounsfield units (HU), uptake pattern (focal or diffuse) and gland morphology (MNG or diffuse). A control group of 15 patients with normal thyroid glands were used to assess the tissue density in HU for normal thyroid tissue. Sensitivity, specificity, PPV, NPV and accuracy to detect malignancy were calculated. Pearson Chi-square test was used to compare categorical variables while unpaired T-test and one way ANOVA test were used to compare means of continuous variables. ROC analysis was used to assess the best cut off points for SUVmax and HU. Regression analysis was used to detect the independent predictors for malignant lesions.

Results

Biopsy was unsatisfactory or indeterminate in 4/48 patients (8%). Only 44 patients (mean age 55.2 ± 14.7; 30 females (68 %)) with unequivocal FNAB or histopathology were included for further analysis. MNG was noted in 17/44 patients (38.6 %). Thyroid malignancy was found in 16/44 (36.4 %), benign thyroid lesions in 28/44 (63.6 %). Thyroid malignancies were 12 papillary, 1 follicular, 1 Hurthle cell neoplasm and 2 lymphoma. Benign lesions were 23 benign follicular or colloid nodules and 5 autoimmune thyroiditis. Focal FDG uptake pattern was more frequently associated with malignant lesions compared to benign lesions (75 % vs. 43 %; p = 0.039). The mean SUVmax and tissue density (HU) were both higher in malignant than benign lesions (8.8 ± 8.3 vs. 3.6 ± 1.9, p = 0.024) and (48.9 ± 12.7 vs. 32.9 ± 17.5, p = 0.003) respectively. The mean HU in the control group with normal thyroid tissue was 90 ± 7.4 significantly higher than in both the benign and malignant lesions (p < 0.001). ROC analysis revealed SUVmax cutoff of >4.7 and HU cutoff of >42 to best differentiate malignant from benign lesions. The sensitivity, specificity, PPV, NPV and accuracy to detect malignancy for SUVmax>4.7 were 68.8 %, 78.6 %, 64.8 %, 81.5 & 75.0 % (p = 0.002), for HU > 42 were 81.3.0 %, 75.0 %, 65.0 %, 87.5 & 77.3 % (p = 0.0003) and for both parameters combined were 87.5 %, 60.7 %, 56.0 %, 89.5 % and accuracy of 70.5 % (p = 0.002) respectively. Only HU > 42 and SUVmax>4.7 were independent predictors for malignancy with odd ratios 8.98 and 4.93 respectively.

Conclusion

A higher tissue density (HU > 42) and SUVmax>4.7 as well as tendency for focal uptake pattern are the most significant characteristics associated with malignant thyroid lesions occasionally detected on PET/CT.

A Systematic Review of PET Textural Analysis and Radiomics in Cancer

Background: Although many works have supported the utility of PET radiomics, several authors have raised concerns over the robustness and replicability of the results. This study aimed to perform a systematic review on the topic of PET radiomics and the used methodologies. Methods: PubMed was searched up to 15 October 2020. Original research articles based on human data specifying at least one tumor type and PET image were included, excluding those that apply only first-order statistics and those including fewer than 20 patients. Each publication, cancer type, objective and several methodological parameters (number of patients and features, validation approach, among other things) were extracted. Results: A total of 290 studies were included. Lung (28%) and head and neck (24%) were the most studied cancers. The most common objective was prognosis/treatment response (46%), followed by diagnosis/staging (21%), tumor characterization (18%) and technical evaluations (15%). The average number of patients included was 114 (median = 71; range 20–1419), and the average number of high-order features calculated per study was 31 (median = 26, range 1–286). Conclusions: PET radiomics is a promising field, but the number of patients in most publications is insufficient, and very few papers perform in-depth validations. The role of standardization initiatives will be crucial in the upcoming years.

Focal Thyroid Incidentalomas on 18F-FDG PET/CT: A Systematic Review and Meta-Analysis on Prevalence, Risk of Malignancy and Inconclusive Fine Needle Aspiration

BACKGROUND

The rising demand for ¹⁸F-fluorodeoxyglucose positron emission tomography with computed tomography (¹⁸F-FDG PET/CT) has led to an increase of thyroid incidentalomas. Current guidelines are restricted in giving options to tailor diagnostics and to suit the individual patient.

OBJECTIVES

We aimed at exploring the extent of potential overdiagnostics by performing a systematic review and meta-analysis of the literature on the prevalence, the risk of malignancy (ROM) and the risk of inconclusive FNAC (ROIF) of focal thyroid incidentalomas (FTI) on ¹⁸F-FDG PET/CT.

DATA SOURCES

A literature search in MEDLINE, Embase and Web of Science was performed to identify relevant studies.

STUDY SELECTION

Studies providing information on the prevalence and/or ROM of FTI on ¹⁸F-FDG PET/CT in patients with no prior history of thyroid disease were selected by two authors independently. Sixty-one studies met the inclusion criteria.

DATA ANALYSIS

A random effects meta-analysis on prevalence, ROM and ROIF with 95% confidence intervals (CIs) was performed. Heterogeneity and publication bias were tested. Risk of bias was assessed using the quality assessment of diagnostic accuracy studies (QUADAS-2) tool.

DATA SYNTHESIS

Fifty studies were suitable for prevalence analysis. In total, 12,943 FTI were identified in 640,616 patients. The pooled prevalence was 2.22% (95% CI = 1.90% - 2.54%, I² = 99%). 5151 FTI had cyto- or histopathology results available. The pooled ROM was 30.8% (95% CI = 28.1% - 33.4%, I² = 57%). 1308 (83%) of malignant nodules were papillary thyroid carcinoma (PTC). The pooled ROIF was 20.8% (95% CI = 13.7% - 27.9%, I² = 92%).

LIMITATIONS

The main limitations were the low to moderate methodological quality of the studies and the moderate to high heterogeneity of the results.

CONCLUSION

FTI are a common finding on ¹⁸F-FDG PET/CTs. Nodules are malignant in approximately one third of the cases, with the majority being PTC. Cytology results are non-diagnostic or indeterminate in one fifth of FNACs. These findings reveal the potential risk of overdiagnostics of FTI and emphasize that the workup of FTI should be performed within the context of the patient's disease and that guidelines should adopt this patient tailored approach.

Radiomics Analysis of [18F]-Fluorodeoxyglucose-Avid Thyroid Incidentalomas Improves Risk Stratification and Selection for Clinical Assessment

Background: [¹⁸F]-Fluorodeoxyglucose (FDG)-avid thyroid lesions incidentally detected on positron emission tomography/computed tomography (PET/CT) scans represent a tumor lesion in about 30% of cases. The present study evaluated the ability of PET metrics and radiomics features to predict final diagnosis of [¹⁸F]FDG thyroid incidentalomas (TIs). Methods: A total of 104 patients with 107 TIs were retrospectively studied; 30 nodules (28%) were diagnosed as malignant. After volumetric segmentation of each thyroid lesion, metabolic tumor volume (MTV), total lesion glycolysis (TLG), standardized uptake values (SUVs), and metabolic heterogeneity were estimated, and 107 radiomics features were extracted following a standard protocol. Results: MTV, TLG, SUVmax, SUVmean, and SUVpeak among functional PET parameters, and gray-level co-occurrence matrix (GLCM)_InverseDifferenceMoment, shape_Sphericity, GLCM_SumSquares, firstorder_Maximum2DDiameterSlice, firstorder_Energy, and GLCM_Contrast among nonredundant radiomics features, showed significantly different values between malignant and benign TIs (Mann-Whitney U-test, p < 0.01 for all). Univariate logistic regression revealed that these parameters demonstrated good ability to predict final diagnosis of TIs (p < 0.02 for all). Shape_Sphericity was the best predictor classifying 82% of TIs correctly (p < 0.0001). Only TLG, SUVmax, and shape_Sphericity retained significance (p < 0.0001) by multivariate analysis. Malignant lesion prevalence increased from 7% to 100% in accordance with the number (score, 0-3) of the three positive parameters present (χ² trend, p < 0.0001). A score of 0 excludes malignant TIs with a negative predictive value of 93%, while a score of 3 predicted malignancy with a positive predictive value of 100%. Conclusions: PET metrics and radiomics analysis can improve identification of [¹⁸F]FDG-avid TIs at high risk of malignancy. A model based on TLG, SUVmax, and shape_Sphericity may allow prediction of a final diagnosis, providing useful information for the management of TIs.

CT texture analysis of mediastinal lymphadenopathy: Combining with US-based elastographic parameter and discrimination between sarcoidosis and lymph node metastasis from small cell lung cancer

Objectives

To investigate the potential of computed tomography (CT)-based texture analysis and elastographic data provided by endobronchial ultrasonography (EBUS) for differentiating the mediastinal lymphadenopathy by sarcoidosis and small cell lung cancer (SCLC) metastasis.

Methods

Sixteen patients with sarcoidosis and 14 with SCLC were enrolled. On CT images showing the largest mediastinal lymph node, a fixed region of interest was drawn on the node, and texture features were automatically measured. Among the 30 patients, 19 (12 sarcoidosis and 7 SCLC) underwent endobronchial ultrasound transbronchial needle aspiration, and the fat-to-lesion strain ratio (FLR) was recorded. Texture features and FLRs were compared between the 2 patient groups. Logistic regression analysis was performed to evaluate the diagnostic accuracy of these measurements.

Results

Of the 31 texture features, the differences between 11 texture features of CT ROIs in the patients with sarcoidosis versus patients with SCLC were significant. Among them, the grey-level run length matrix with high gray-level run emphasis (GLRLM-HGRE) showed the greatest difference (P<0.01). Differences between FLRs were significant (P<0.05). Logistic regression analysis together with receiver operating characteristic curve analysis demonstrated that the FLR combined with the GLRLM-HGRE showed a high diagnostic accuracy (100% sensitivity, 92% specificity, 0.988 area under the curve) for discriminating between sarcoidosis and SCLC.

Conclusion

Texture analysis, particularly combined with the FLR, is useful for discriminating between mediastinal lymphadenopathy caused by sarcoidosis from that caused by metastasis from SCLC.

Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)

Background:

Texture analysis (TA) can quantify intra-tumor heterogeneity using standard medical images. The present study aimed to assess the application of positron emission tomography (PET) TA in the differential diagnosis of gastric cancer and gastric lymphoma.

Methods:

The pre-treatment PET images of 79 patients (45 gastric cancer, 34 gastric lymphoma) between January 2013 and February 2018 were retrospectively reviewed. Standard uptake values (SUVs), first-order texture features, and second-order texture features of the grey-level co-occurrence matrix (GLCM) were analyzed. The differences in features among different groups were analyzed by the two-way Mann-Whitney test, and receiver operating characteristic (ROC) analysis was used to estimate the diagnostic efficacy.

Results:

Inertia_GLCM was significantly lower in gastric cancer than that in gastric lymphoma (4975.61 vs. 11,425.30, z = −3.238, P = 0.001), and it was found to be the most discriminating texture feature in differentiating gastric lymphoma and gastric cancer. The area under the curve (AUC) of inertia_GLCM was higher than the AUCs of SUVmax and SUVmean (0.714 vs. 0.649 and 0.666, respectively). SUVmax and SUVmean were significantly lower in low-grade gastric lymphoma than those in high grade gastric lymphoma (3.30 vs. 11.80, 2.40 vs. 7.50, z = −2.792 and −3.007, P = 0.005 and 0.003, respectively). SUVs and first-order grey-level intensity features were not significantly different between low-grade gastric lymphoma and gastric cancer. Entropy_GLCM12 was significantly lower in low-grade gastric lymphoma than that in gastric cancer (6.95 vs. 9.14, z = −2.542, P = 0.011) and had an AUC of 0.770 in the ROC analysis of differentiating low-grade gastric lymphoma and gastric cancer.

Conclusions:

Inertia_GLCM and entropy_GLCM were the most discriminating features in differentiating gastric lymphoma from gastric cancer and low-grade gastric lymphoma from gastric cancer, respectively. PET TA can improve the differential diagnosis of gastric neoplasms, especially in tumors with similar degrees of fluorodeoxyglucose uptake.

Evidence-Based Data About Prevalence and Risk of Malignancy of Thyroid Incidentalomas Detected by Different PET Radiopharmaceuticals

Background:

To date, several meta-analyses and systematic reviews have reported data about the prevalence and risk of malignancy of thyroid incidentalomas detected by different PET radiopharmaceuticals.

Objective:

This article aims to summarize the published evidence-based data about the prevalence and risk of malignancy of thyroid incidentalomas detected by different PET radiopharmaceuticals.

Methods:

A comprehensive computer literature search of systematic reviews and meta-analyses published up to July 2019 in PubMed/MEDLINE and Cochrane library databases regarding the prevalence and risk of malignancy of thyroid incidentalomas detected by different PET radiopharmaceuticals was carried out.

Results:

We have summarized the data about prevalence and risk of malignancy of thyroid incidentalomas detected by different PET radiopharmaceuticals (fluorine-18 fluorodeoxyglucose, radiolabelled choline and prostate-specific membrane antigen) taking into account 8 evidence-based articles.

Conclusion:

Evidence-based data demonstrated that thyroid incidentalomas detected by different PET radiopharmaceuticals are not infrequent and their risk of malignancy is not negligible, in particular if focal pattern is evident at PET, thus requiring further clinical and instrumental evaluation.

Evaluating Focal 18F-FDG Uptake in Thyroid Gland with Radiomics

Purpose

The aim of this study was to evaluate the ability of ¹⁸F-FDG PET/CT texture analysis to predict the exact pathological outcome of thyroid incidentalomas.

Methods

¹⁸F-FDG PET/CT images between March 2010 and September 2018 were retrospectively reviewed in patients with focal ¹⁸F-FDG uptake in the thyroid gland and who underwent fine needle aspiration biopsy from this area. The focal uptake in the thyroid gland was drawn in 3D with 40% SUVmax threshold. Features were extracted from volume of interest (VOI) using the LIFEx package. The features obtained were compared in benign and malignant groups, and statistically significant variables were evaluated by receiver operating curve (ROC) analysis. The correlation between the variables with area under curve (AUC) value over 0.7 was examined; variables with correlation coefficient less than 0.6 were evaluated with machine learning algorithms.

Results

Sixty patients (70% train set, 30% test set) were included in the study. In univariate analysis, a statistically significant difference was observed in 6 conventional parameters, 5 first-, and 16 second-order features between benign and malignant groups in train set (p < 0.05). The feature with the highest benign-malignant discriminating power was GLRLM_RLNU (AUC:0.827). AUC value of SUVmax was calculated as 0.758. GLRLM_RLNU and SUVmax were evaluated to build a model to predict the exact pathology outcome. Random forest algorithm showed the best accuracy and AUC (78.6% and 0.849, respectively).

Conclusion

In the differentiation of benign-malignant thyroid incidentalomas, GLRLM_RLNU and SUVmax combination may be more useful than SUVmax to predict the outcome.

Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma

PURPOSE

To appraise the ability of a radiomics signature to predict clinical outcome after stereotactic body radiation therapy (SBRT) for pancreas carcinoma.

METHODS

A cohort of 100 patients was included in this retrospective, single institution analysis. Radiomics texture features were extracted from computed tomography (CT) images obtained for the clinical target volume. The cohort of patients was randomly divided into two separate groups for the training (60 patients) and validation (40 patients). Cox regression models were built to predict overall survival and local control. The significant predictors at univariate analysis were included in a multivariate model. The quality of the models was appraised by means of area under the curve and concordance index.

RESULTS

A clinical-radiomic signature associated with Overall Survival (OS) was found significant in both training and validation sets (p = 0.01 and 0.05 and concordance index 0.73 and 0.75 respectively). Similarly, a signature was found for Local Control (LC) with p = 0.007 and 0.004 and concordance index 0.69 and 0.75. In the low risk group, the median OS and LC in the validation group were 14.4 and 28.6 months while in the high-risk group were 9.0 and 17.5 months respectively.

CONCLUSION

A CT based radiomic signature was identified which correlate with OS and LC after SBRT and allowed to identify low and high-risk groups of patients.