Duodenal neuroendocrine neoplasms on enhanced CT : establishing a diagnostic model with duodenal gastrointestinal stromal tumors in the non-ampullary area and analyzing the value of predicting prognosis
© 2023. The Author(s)..
OBJECTIVE: To identify CT features and establish a diagnostic model for distinguishing non-ampullary duodenal neuroendocrine neoplasms (dNENs) from non-ampullary duodenal gastrointestinal stromal tumors (dGISTs) and to analyze overall survival outcomes of all dNENs patients.
MATERIALS AND METHODS: This retrospective study included 98 patients with pathologically confirmed dNENs (n = 44) and dGISTs (n = 54). Clinical data and CT characteristics were collected. Univariate analyses and binary logistic regression analyses were performed to identify independent factors and establish a diagnostic model between non-ampullary dNENs (n = 22) and dGISTs (n = 54). The ROC curve was created to determine diagnostic ability. Cox proportional hazards models were created and Kaplan-Meier survival analyses were performed for survival analysis of dNENs (n = 44).
RESULTS: Three CT features were identified as independent predictors of non-ampullary dNENs, including intraluminal growth pattern (OR 0.450; 95% CI 0.206-0.983), absence of intratumoral vessels (OR 0.207; 95% CI 0.053-0.807) and unenhanced lesion > 40.76 HU (OR 5.720; 95% CI 1.575-20.774). The AUC was 0.866 (95% CI 0.765-0.968), with a sensitivity of 90.91% (95% CI 70.8-98.9%), specificity of 77.78% (95% CI 64.4-88.0%), and total accuracy rate of 81.58%. Lymph node metastases (HR: 21.60), obstructive biliary and/or pancreatic duct dilation (HR: 5.82) and portal lesion enhancement ≤ 99.79 HU (HR: 3.02) were independent prognostic factors related to poor outcomes.
CONCLUSION: We established a diagnostic model to differentiate non-ampullary dNENs from dGISTs. Besides, we found that imaging features on enhanced CT can predict OS of patients with dNENs.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:149 |
|---|---|
| Enthalten in: |
Journal of cancer research and clinical oncology - 149(2023), 16 vom: 25. Nov., Seite 15143-15157 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Feng, Na [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Computed tomography |
|---|
| Anmerkungen: |
Date Completed 27.10.2023 Date Revised 29.10.2023 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1007/s00432-023-05295-9 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM361323271 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM361323271 | ||
| 003 | DE-627 | ||
| 005 | 20231226084910.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s00432-023-05295-9 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1204.xml |
| 035 | |a (DE-627)NLM361323271 | ||
| 035 | |a (NLM)37634206 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Feng, Na |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Duodenal neuroendocrine neoplasms on enhanced CT |b establishing a diagnostic model with duodenal gastrointestinal stromal tumors in the non-ampullary area and analyzing the value of predicting prognosis |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 27.10.2023 | ||
| 500 | |a Date Revised 29.10.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2023. The Author(s). | ||
| 520 | |a OBJECTIVE: To identify CT features and establish a diagnostic model for distinguishing non-ampullary duodenal neuroendocrine neoplasms (dNENs) from non-ampullary duodenal gastrointestinal stromal tumors (dGISTs) and to analyze overall survival outcomes of all dNENs patients | ||
| 520 | |a MATERIALS AND METHODS: This retrospective study included 98 patients with pathologically confirmed dNENs (n = 44) and dGISTs (n = 54). Clinical data and CT characteristics were collected. Univariate analyses and binary logistic regression analyses were performed to identify independent factors and establish a diagnostic model between non-ampullary dNENs (n = 22) and dGISTs (n = 54). The ROC curve was created to determine diagnostic ability. Cox proportional hazards models were created and Kaplan-Meier survival analyses were performed for survival analysis of dNENs (n = 44) | ||
| 520 | |a RESULTS: Three CT features were identified as independent predictors of non-ampullary dNENs, including intraluminal growth pattern (OR 0.450; 95% CI 0.206-0.983), absence of intratumoral vessels (OR 0.207; 95% CI 0.053-0.807) and unenhanced lesion > 40.76 HU (OR 5.720; 95% CI 1.575-20.774). The AUC was 0.866 (95% CI 0.765-0.968), with a sensitivity of 90.91% (95% CI 70.8-98.9%), specificity of 77.78% (95% CI 64.4-88.0%), and total accuracy rate of 81.58%. Lymph node metastases (HR: 21.60), obstructive biliary and/or pancreatic duct dilation (HR: 5.82) and portal lesion enhancement ≤ 99.79 HU (HR: 3.02) were independent prognostic factors related to poor outcomes | ||
| 520 | |a CONCLUSION: We established a diagnostic model to differentiate non-ampullary dNENs from dGISTs. Besides, we found that imaging features on enhanced CT can predict OS of patients with dNENs | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Computed tomography | |
| 650 | 4 | |a Duodenum | |
| 650 | 4 | |a Gastrointestinal stromal tumors | |
| 650 | 4 | |a Neuroendocrine tumors | |
| 650 | 4 | |a Survival analysis | |
| 700 | 1 | |a Chen, Hai-Yan |e verfasserin |4 aut | |
| 700 | 1 | |a Lu, Yuan-Fei |e verfasserin |4 aut | |
| 700 | 1 | |a Pan, Yao |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Jie-Ni |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Xin-Bin |e verfasserin |4 aut | |
| 700 | 1 | |a Deng, Xue-Ying |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Ri-Sheng |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of cancer research and clinical oncology |d 1981 |g 149(2023), 16 vom: 25. Nov., Seite 15143-15157 |w (DE-627)NLM000394610 |x 1432-1335 |7 nnns |
| 773 | 1 | 8 | |g volume:149 |g year:2023 |g number:16 |g day:25 |g month:11 |g pages:15143-15157 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1007/s00432-023-05295-9 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 149 |j 2023 |e 16 |b 25 |c 11 |h 15143-15157 | ||