Pancreatic Incidentalomas: A Management Algorithm for Identifying Ectopic Spleens.


Journal

The Journal of surgical research
ISSN: 1095-8673
Titre abrégé: J Surg Res
Pays: United States
ID NLM: 0376340

Informations de publication

Date de publication:
04 2019
Historique:
received: 12 07 2018
revised: 01 10 2018
accepted: 19 11 2018
pubmed: 30 1 2019
medline: 17 1 2020
entrez: 30 1 2019
Statut: ppublish

Résumé

Identification of incidental pancreatic lesions is increasing because of advancements in imaging. Diagnosis remains a challenge for clinicians, with intrapancreatic accessory spleens (IPAS) posing a unique dilemma. IPAS are frequently resected because of inability to exclude alternate diagnoses, subjecting patients to unnecessary risk. The purpose of this study was to examine our institutional experience with IPAS and develop a multidisciplinary algorithm to improve preoperative diagnosis. Patients who underwent a distal pancreatectomy at a single institution from 2005 to 2018 were identified from a prospectively maintained database. Examination of final pathology for a diagnosis of IPAS yielded the final cohort. Demographics, preoperative workup, and operative course were reviewed and analyzed. A diagnostic algorithm was composed based on the consensus of a panel of expert pancreatic surgeons, a radiologist, and a pathologist. Ten patients of 303 patients who underwent a distal pancreatectomy were identified with a final pathology of IPAS. The average age was 54 y, 80% were white, and 60% were male. Lesions ranged in size from 7 mm to 5.1 cm in largest diameter (mean 2.2 cm). Lesions were described as round, well-marginated, and enhancing masses within the pancreatic tail. Preoperative workup was variable in terms of imaging and laboratory testing. Diagnostic workups were examined and combined with multidisciplinary input to create a diagnostic algorithm. Incidental pancreatic lesions like IPAS remain a diagnostic challenge for clinicians. Employing a diagnostic algorithm as proposed may aid in the distinction of malignant and premalignant pathology and prevent unwarranted pancreatic resections.

Sections du résumé

BACKGROUND
Identification of incidental pancreatic lesions is increasing because of advancements in imaging. Diagnosis remains a challenge for clinicians, with intrapancreatic accessory spleens (IPAS) posing a unique dilemma. IPAS are frequently resected because of inability to exclude alternate diagnoses, subjecting patients to unnecessary risk. The purpose of this study was to examine our institutional experience with IPAS and develop a multidisciplinary algorithm to improve preoperative diagnosis.
MATERIALS AND METHODS
Patients who underwent a distal pancreatectomy at a single institution from 2005 to 2018 were identified from a prospectively maintained database. Examination of final pathology for a diagnosis of IPAS yielded the final cohort. Demographics, preoperative workup, and operative course were reviewed and analyzed. A diagnostic algorithm was composed based on the consensus of a panel of expert pancreatic surgeons, a radiologist, and a pathologist.
RESULTS
Ten patients of 303 patients who underwent a distal pancreatectomy were identified with a final pathology of IPAS. The average age was 54 y, 80% were white, and 60% were male. Lesions ranged in size from 7 mm to 5.1 cm in largest diameter (mean 2.2 cm). Lesions were described as round, well-marginated, and enhancing masses within the pancreatic tail. Preoperative workup was variable in terms of imaging and laboratory testing. Diagnostic workups were examined and combined with multidisciplinary input to create a diagnostic algorithm.
CONCLUSIONS
Incidental pancreatic lesions like IPAS remain a diagnostic challenge for clinicians. Employing a diagnostic algorithm as proposed may aid in the distinction of malignant and premalignant pathology and prevent unwarranted pancreatic resections.

Identifiants

pubmed: 30694749
pii: S0022-4804(18)30823-0
doi: 10.1016/j.jss.2018.11.032
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

144-152

Subventions

Organisme : NHLBI NIH HHS
ID : T32 HL092332
Pays : United States

Informations de copyright

Copyright © 2018 Elsevier Inc. All rights reserved.

Auteurs

Katherine A Baugh (KA)

Elkins Pancreas Center, Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.

Nicole Villafane (N)

Elkins Pancreas Center, Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.

Carlos Farinas (C)

Department of Radiology, Baylor College of Medicine, Houston, Texas.

Sadhna Dhingra (S)

Department of Pathology, Baylor College of Medicine, Houston, Texas.

Eric J Silberfein (EJ)

Elkins Pancreas Center, Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.

Nader N Massarweh (NN)

Elkins Pancreas Center, Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.

H Tran Cao (HT)

Elkins Pancreas Center, Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.

William E Fisher (WE)

Elkins Pancreas Center, Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.

George Van Buren (G)

Elkins Pancreas Center, Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas. Electronic address: George.vanburen@bcm.edu.

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