Evaluating radiological response in pancreatic neuroendocrine tumours treated with sunitinib: comparison of Choi versus RECIST criteria (CRIPNET_ GETNE1504 study)

Solis-Hernández, María Pilar; Valle, A. Fernández del; Carmona-Bayonas, Alberto; Garcia-Carbonero, Rocío; Custodio, Ana; Benavent, Marta; Gordoa, Teresa Alonso; Nuñez-Valdovino, Bárbara; Cánovas, Manuel Sánchez; Matos, Ignacio; Alonso, Vicente; López, Carlos; Viúdez, A.; Izquierdo, M.; Calvo-Temprano, David; Grande, Enrique; Capdevila, Jaume; Jiménez‐Fonseca, Paula

doi:10.1038/s41416-019-0558-7

Cited by 23 publications

(17 citation statements)

References 35 publications

(50 reference statements)

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“…Each item was carefully selected to meet specific criteria: (1) to focus on the radiological findings most relevant for patient man- Subsequently, similar advantages of using modified RECIST criteria (mRECIST) for loco-regional therapy in NENs have been reported, in particular for the assessment of TACE of liver metastases. 5 In addition, it has been suggested that the CHOI criteria, initially developed for the assessment of gastrointestinal stromal tumors treated with Imatinib, may be appropriate for tumor response assessment in NENs treated with either targeted therapies such as sunitinib and everolimus [12][13][14] or peptide receptor radionuclide therapy. 15 Finally, the ADC, measured on diffusion-weighted MRI, has also become a promising quantitative biomarker for prediction and monitoring of the therapeutic response.…”

Section: Discussionmentioning

confidence: 99%

ENETS standardized (synoptic) reporting for radiological imaging in neuroendocrine tumours

Dromain

Vullierme

Hicks

et al. 2021

J Neuroendocrinology

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This expert consensus document represents an initiative by the European Neuroendocrine Tumor Society (ENETS) to provide guidance for synoptic reporting of radiological examinations critical to the diagnosis, grading, staging and treatment of neuroendocrine neoplasms (NENs). Template drafts for initial tumor staging and follow‐up by computed tomography (CT) and magnetic resonance imaging (MRI) were established, based on existing institutional and organisational reporting templates relevant for NEN imaging, and applying the RadLex lexicon of radiological information (Radiological Society of North America), for consistency regarding the radiological terms. During the ENETS Scientific Advisory Board meeting 2018, the template drafts were subject to iterative interdisciplinary discussions among experts in imaging, surgery, gastroenterology, oncology and pathology. Members of the imaging group stated a strong preference for a combination of limited and standardised options by way of drop‐down menus. Separate templates were produced for the initial work‐up and for follow‐up, respectively. To provide a detailed description of the radiological findings of the primary tumor and its local extension and spread, different templates were developed for bronchial, pancreatic and gastrointestinal NENs for CT and MRI, respectively. Each template was structured in 10 sections: clinical details, comparative imaging modality, acquisition technique, primary tumor findings, regional lymph node metastases, distant metastases, TNM classification, reference lesions according to RECIST 1.1, additional findings and conclusion. Two templates were developed for follow‐up, for CT and MRI, respectively, and were specifically focused on assessment of therapy response. These included a qualitative response assessment, such as decrease of vascularisation and presence of necrosis, and a quantitative assessment according to RECIST 1.1 and the modified RECIST (mRECIST) for assessing tumor response following transarterial chemoembolisation.

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Section: Discussionmentioning

confidence: 99%

ENETS standardized (synoptic) reporting for radiological imaging in neuroendocrine tumours

Dromain

Vullierme

Hicks

et al. 2021

J Neuroendocrinology

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“…Up to now, 3D volumetry of liver lesions has only been carried out within the framework of studies [ 51 , 52 ]. Besides the volumetric assessment of tumor burden, the 3D segmentations generated by the model presented in this study could be used for further lesion analysis, such as texture analysis, radiomics or contrast-uptake used in Choi criteria [ 53 , 54 ]. To date, most studies concerning artificial intelligence and liver imaging focus on diffuse liver disease or the classification of liver tumors [ 55 , 56 , 57 ].…”

Section: Discussionmentioning

confidence: 99%

Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI—A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-Making

Fehrenbach

Xin

Hartenstein

et al. 2021

Cancers

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Background: Rapid quantification of liver metastasis for diagnosis and follow-up is an unmet medical need in patients with secondary liver malignancies. We present a 3D-quantification model of neuroendocrine liver metastases (NELM) using gadoxetic-acid (Gd-EOB)-enhanced MRI as a useful tool for multidisciplinary cancer conferences (MCC). Methods: Manual 3D-segmentations of NELM and livers (149 patients in 278 Gd-EOB MRI scans) were used to train a neural network (U-Net architecture). Clinical usefulness was evaluated in another 33 patients who were discussed in our MCC and received a Gd-EOB MRI both at baseline and follow-up examination (n = 66) over 12 months. Model measurements (NELM volume; hepatic tumor load (HTL)) with corresponding absolute (ΔabsNELM; ΔabsHTL) and relative changes (ΔrelNELM; ΔrelHTL) between baseline and follow-up were compared to MCC decisions (therapy success/failure). Results: Internal validation of the model’s accuracy showed a high overlap for NELM and livers (Matthew’s correlation coefficient (φ): 0.76/0.95, respectively) with higher φ in larger NELM volume (φ = 0.80 vs. 0.71; p = 0.003). External validation confirmed the high accuracy for NELM (φ = 0.86) and livers (φ = 0.96). MCC decisions were significantly differentiated by all response variables (ΔabsNELM; ΔabsHTL; ΔrelNELM; ΔrelHTL) (p < 0.001). ΔrelNELM and ΔrelHTL showed optimal discrimination between therapy success or failure (AUC: 1.000; p < 0.001). Conclusion: The model shows high accuracy in 3D-quantification of NELM and HTL in Gd-EOB-MRI. The model’s measurements correlated well with MCC’s evaluation of therapeutic response.

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“…In interpreting the results, it is also important to note that the endpoint currently considered clinically relevant (i.e., PFS) depends on radiological progression according to morphological criteria (RECIST). This entails certain limitations in NENs, as functional differences are not factored in [18]. For its part, PFS is deemed an acceptable surrogate endpoint for OS in RCTs of NENs [53].…”

Section: Discussionmentioning

confidence: 99%

“…Patients initiated therapy between 2002 and 2017. The design, characteristics, and quality criteria of this registry have been previously reported [5,6,[16][17][18]. Data from a total of 4,068 available cases were screened for eligibility, and additional quality controls were implemented for this analysis (double-checking of data, monitoring of discrepancies, and unjustified missing data).…”

Section: Patientsmentioning

confidence: 99%

External Validity of Somatostatin Analogs Trials in Advanced Neuroendocrine Neoplasms: The GETNE-TRASGU Study

et al. 2021

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Introduction: Somatostatin analogues (SSA) prolong progression-free survival (PFS) in patients with well-differentiated gastroenteropancreatic neuroendocrine tumors (GEP-NETs). However, the eligibility criteria in randomized clinical trials (RCTs) have been restricted, which contrasts with the vast heterogeneity found in NETs. Methods: We identified patients with well-differentiated (Ki67% ≤20%), metastatic GEP-NETs treated in first-line with SSA monotherapy from the Spanish R-GETNE registry. The therapeutic effect was evaluated using a Bayesian Cox model. The objective was to compare survival-based outcomes from real world clinical practice versus RCTs. Results: The dataset contained 535 patients with a median age of 62 years (range: 26-89). The median Ki67% was 4 (range: 0-20). The most common primary tumor sites were: midgut, 46%; pancreas, 34%; unknown primary, 10%; and colorectal, 10%. Half of the patients received octreotide LAR (n=266) and half, lanreotide autogel (n=269). The median PFS was 28.0 months (95% CI, 22.1-32.0) for octreotide vs 30.1 months (95% CI, 23.1-38.0) for lanreotide. The overall hazard ratio for lanreotide vs octreotide was 0.90 (95% credible interval, 0.71-1.12). The probability of effect sizes >30% with lanreotide vs octreotide was 2% and 6% for midgut and foregut NENs, respectively. Conclusion: Our study evaluated the external validity of RCTs examining SSAs in the real world, as well as the main effect-modifying factors (progression status, symptoms, tumor site, specific metastases, and analytical data).. Our results indicate that both octreotide LAR and lanreotide autogel had a similar effect on PFS. Consequently, both represent valid alternatives in patients with well-differentiated, metastatic GEP-NENs.

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Evaluating radiological response in pancreatic neuroendocrine tumours treated with sunitinib: comparison of Choi versus RECIST criteria (CRIPNET_ GETNE1504 study)

Cited by 23 publications

References 35 publications

ENETS standardized (synoptic) reporting for radiological imaging in neuroendocrine tumours

ENETS standardized (synoptic) reporting for radiological imaging in neuroendocrine tumours

Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI—A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-Making

External Validity of Somatostatin Analogs Trials in Advanced Neuroendocrine Neoplasms: The GETNE-TRASGU Study

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