Multiparametric Evaluation in Differentiating Glioma Recurrence from Treatment-Induced Necrosis Using Simultaneous<sup>18</sup>F-FDG-PET/MRI: A Single-Institution Retrospective Study

Jena, Amarnath; Taneja, Sangeeta; Jha, Abhishek; Damesha, N.K.; Negi, Pradeep; Jadhav, Ganesh K; Verma, Sapna; Sogani, Shanti Kumar

doi:10.3174/ajnr.a5124

Cited by 47 publications

(52 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To improve the diagnostic efficiency, the synergetic effect of multiparametric PET and MRI parameters was highlighted in previous studies. This indicates that the integrated 18 F-FET or 18 F-FDG PET/MRI analysis could assist in the management of glioma patients by timely and conclusive recognition of true tumor recurrence [9,10,31]. Being embedded in clinical practice, radiomics could provide a comprehensive quantification of imaging information.…”

Section: Discussionmentioning

confidence: 99%

Individualized discrimination of tumor recurrence from radiation necrosis in glioma patients using an integrated radiomics-based model

Wang

Zhen

Zhao

et al. 2019

Eur J Nucl Med Mol Imaging

View full text Add to dashboard Cite

Purpose To develop and validate an integrated model for discriminating tumor recurrence from radiation necrosis in glioma patients. Methods Data from 160 pathologically confirmed glioma patients were analyzed. The diagnostic model was developed in a primary cohort (n = 112). Textural features were extracted from postoperative 18 F-fluorodeoxyglucose (18 F-FDG) positron emission tomography (PET), 11 C-methionine (11 C-MET) PET, and magnetic resonance images. The least absolute shrinkage and selection operator regression model was used for feature selection and radiomics signature building. Multivariable logistic regression analysis was used to develop a model for predicting tumor recurrence. The radiomics signature, quantitative PET parameters, and clinical risk factors were incorporated in the model. The clinical value of the model was then assessed in an independent validation cohort using the remaining 48 glioma patients. Results The integrated model consisting of 15 selected features was significantly associated with postoperative tumor recurrence (p < 0.001 for both primary and validation cohorts). Predictors contained in the individualized diagnosis model included the radiomics signature, the mean of tumor-background ratio (TBR) of 18 F-FDG, maximum of TBR of 11 C-MET PET, and patient age. The integrated model demonstrated good discrimination, with an area under the curve (AUC) of 0.988, with a 95% confidence interval (CI) of 0.975-1.000. Application in the validation cohort showed good differentiation (AUC of 0.914 and 95% CI of 0.881-0.945). Decision curve analysis showed that the integrated diagnosis model was clinically useful. Conclusions Our developed model could be used to assist the postoperative individualized diagnosis of tumor recurrence in patients with gliomas.

show abstract

Section: Discussionmentioning

confidence: 99%

Individualized discrimination of tumor recurrence from radiation necrosis in glioma patients using an integrated radiomics-based model

Wang

Zhen

Zhao

et al. 2019

Eur J Nucl Med Mol Imaging

View full text Add to dashboard Cite

show abstract

“…A high incidence of treatment-related changes has been noted in patients who undergo post-operative radiotherapy or combined chemoradiotherapy with temozolomide. Moreover, routinely available CT and MRI techniques do not allow a reliable distinction between glioma recurrence and treatment-related changes [1,14]. Moreover, the presence of a new contrast-enhanced lesion during follow-up imaging typically indicates a mixture of necrotic tissue and progressive tumor growth; this adds to the overall complexity of lesion characterization [3].…”

Section: Discussionmentioning

confidence: 99%

Dual-energy spectral CT quantitative parameters for the differentiation of Glioma recurrence from treatment-related changes: a preliminary study

Zhou

et al. 2020

BMC Med Imaging

View full text Add to dashboard Cite

Background: Differentiating glioma recurrence from treatment-related changes can be challenging on conventional imaging. We evaluated the efficacy of quantitative parameters measured by dual-energy spectral computed tomographic (CT) for this differentiation. Methods: Twenty-eight patients were examined by dual-energy spectral CT. The effective and normalized atomic number (Z eff and Z eff-N, respectively); spectral Hounsfield unit curve (λ HU) slope; and iodine and normalized iodine concentration (IC and IC N , respectively) in the post-treatment enhanced areas were calculated. Pathological results or clinicoradiologic follow-up of ≥2 months were used for final diagnosis. Nonparametric and t-tests were used to compare quantitative parameters between glioma recurrence and treatment-related changes. Sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively), and accuracy were calculated using receiver operating characteristic (ROC) curves. Predictive probabilities were used to generate ROC curves to determine the diagnostic value. Results: Examination of pre-contrast λ HU , Z eff , Z eff-N , IC, IC N , and venous phase IC N showed no significant differences in quantitative parameters (P > 0.05). Venous phase λ HU , Z eff , Z eff-N , and IC in glioma recurrence were higher than in treatment-related changes (P < 0.001). The optimal venous phase threshold was 1.

show abstract

“…A high incidence of treatment-related changes has been noted in patients who undergo post-operative radiotherapy or combined chemoradiotherapy with temozolomide. Moreover, routinely available CT and MRI techniques do not allow a reliable distinction between glioma recurrence and treatment-related changes [1,14]. Further, a new contrast-enhancing lesion observed on follow up imaging is often a mixture of necrotic tissue and growing tumor, which this adds to the complexity of lesion characterization [3].…”

Section: Discussionmentioning

confidence: 99%

Dual-energy Spectral CT Quantitative Parameters for the Differentiation of Glioma Recurrence from Treatment-Related Changes: A Preliminary Study

Zhou

et al. 2019

Preprint

View full text Add to dashboard Cite

Background: Differentiating glioma recurrence from treatment-related changes can be challenging on conventional imaging. We evaluated the use of dual-energy spectral computed tomographic (CT) quantitative parameters for this differentiation. Methods: Twenty-eight patients were examined by dual-energy spectral imaging CT. The slope of the spectral Hounsfield unit curve (λHU), effective atomic number (Zeff), normalized effective atomic number (Zeff-N), iodine concentration (IC), and normalized iodine concentration (ICN) in the post-treatment enhanced areas were calculated. Pathological results or clinicoradiologic follow-up of ≥2 months were used for final diagnosis. Nonparametric and t-tests were used to compare quantitative parameters between glioma recurrence and treatment-related changes. Positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated; sensitivity and specificity were calculated using receiver operating characteristic (ROC) curves. ROC curves were generated using predictive probabilities to evaluate the diagnostic value. Results: There were no significant differences in quantitative parameters based on examination of pre-contrast λHU, Zeff, Zeff-N, IC, ICN and venous phase ICN (P>0.05). Venous phase λHU, Zeff, Zeff-N, and IC in glioma recurrence were higher than in treatment-related changes (P<0.001). The optimal venous phase threshold was 1.03, 7.75, 1.04, and 2.85 mg/cm3, achieving 66.7%, 91.7%, 83.3%, and 91.7% sensitivity; 100.0%, 77.8%, 88.9%, and 77.8% specificity; 100.0%, 73.3%, 83.3%, and 73.3% PPV; 81.8%, 93.3%, 88.9%, and 93.3% NPV; and 86.7%, 83.3%, 86.7%, and 83.3% accuracy, respectively. The areas under the curve (AUC) were 0.912, 0.912, 0.931, and 0.910 in glioma recurrence and treatment-related changes, respectively. Conclusions: Dual-energy spectral CT imaging may provide quantitative values to aid in differentiation of glioma recurrence from treatment-related changes.

show abstract

Multiparametric Evaluation in Differentiating Glioma Recurrence from Treatment-Induced Necrosis Using Simultaneous¹⁸F-FDG-PET/MRI: A Single-Institution Retrospective Study

Abstract: Simultaneous PET/MR imaging with FDG offers correlative and synergistic multiparametric assessment of glioma recurrence with increased accuracy and clinical utility.

Cited by 47 publications

References 29 publications

Individualized discrimination of tumor recurrence from radiation necrosis in glioma patients using an integrated radiomics-based model

Individualized discrimination of tumor recurrence from radiation necrosis in glioma patients using an integrated radiomics-based model

Dual-energy spectral CT quantitative parameters for the differentiation of Glioma recurrence from treatment-related changes: a preliminary study

Dual-energy Spectral CT Quantitative Parameters for the Differentiation of Glioma Recurrence from Treatment-Related Changes: A Preliminary Study

Contact Info

Product

Resources

About

Multiparametric Evaluation in Differentiating Glioma Recurrence from Treatment-Induced Necrosis Using Simultaneous18F-FDG-PET/MRI: A Single-Institution Retrospective Study

Abstract: Simultaneous PET/MR imaging with FDG offers correlative and synergistic multiparametric assessment of glioma recurrence with increased accuracy and clinical utility.

Cited by 47 publications

References 29 publications

Individualized discrimination of tumor recurrence from radiation necrosis in glioma patients using an integrated radiomics-based model

Individualized discrimination of tumor recurrence from radiation necrosis in glioma patients using an integrated radiomics-based model

Dual-energy spectral CT quantitative parameters for the differentiation of Glioma recurrence from treatment-related changes: a preliminary study

Dual-energy Spectral CT Quantitative Parameters for the Differentiation of Glioma Recurrence from Treatment-Related Changes: A Preliminary Study

Contact Info

Product

Resources

About

Multiparametric Evaluation in Differentiating Glioma Recurrence from Treatment-Induced Necrosis Using Simultaneous¹⁸F-FDG-PET/MRI: A Single-Institution Retrospective Study