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Quiste Pancreático , Neoplasias Pancreáticas , Lesiones Precancerosas , Humanos , Páncreas/patología , Páncreas/diagnóstico por imagen , Quiste Pancreático/diagnóstico , Quiste Pancreático/patología , Neoplasias Pancreáticas/patología , Neoplasias Pancreáticas/prevención & control , Tomografía Computarizada por Rayos X , Lesiones Precancerosas/diagnóstico , Lesiones Precancerosas/patologíaRESUMEN
This study aimed to evaluate the diagnostic efficacy of cell block (CB) and liquid-based cytology (LBC) for endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) in pancreatic tumors. The study included patients who underwent EUS-FNA for pancreatic tumors between January 2015 and February 2021 and whose cytology samples were both processed for LBC and CB. Data of 390 patients (220 men, mean age: 64.2 ± 11.4 years) were retrospectively analyzed. Of the detected lesions (size: 17-120 mm; mean: 39.9 ± 13.9 mm), 220 (56.4%) were located in the head and uncinate process of the pancreas. Lesions in 339 (86.9%) patients were diagnosed as malignant using CB and/or LBC and suspicious for malignancy in 44 (11.3%) patients. In 7 patients with non-diagnostic (6 cases) or negative for malignancy (1 case) EUS-FNA results using both methods, the diagnosis of malignancy was established via ultrasound-guided percutaneous biopsy. Malignancy was detected in 324 (92.4%), 313 (87.9%), and 298 (87.9%) patients using CB, LBC, and both CB and LBC, respectively. Final diagnosis was obtained in 339 (98%) patients by using CB and/or LBC. The combined use of the both methods exhibited significantly superior diagnostic accuracy compared with CB and LBC alone (P < .001). Liquid-based cytology and CB exhibit high diagnostic accuracy for the detection of pancreatic tumors in patients undergoing EUS-FNA. The combined use of both methods showed a significantly higher diagnostic accuracy than LBC and CB alone.
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Biopsia por Aspiración con Aguja Fina Guiada por Ultrasonido Endoscópico , Neoplasias Pancreáticas , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Biopsia por Aspiración con Aguja Fina Guiada por Ultrasonido Endoscópico/métodos , Páncreas/patología , Páncreas/diagnóstico por imagen , Neoplasias Pancreáticas/diagnóstico , Neoplasias Pancreáticas/patología , Estudios Retrospectivos , Sensibilidad y Especificidad , Biopsia Líquida/métodosRESUMEN
BACKGROUND/AIMS: Pancreatic steatosis (PS) is a pathology associated with metabolic syndrome (MS), endocrin and exocrine disfunctions of the pancreas, and fatty liver. The data on the frequency of PS are very limited. We aimed to evaluate the frequency of PS detected by transabdominal ultrasonography (TAU) in gastroenterology clinics located in different geographical regions of Turkey and the factors associated with it. MATERIALS AND METHODS: Volunteers were evaluated by TAU for PS and hepatosteatosis (HS), and its degree. Pancreatic stiffness was evaluated by ultrasonographic shear wave elastography (SWE). All demographic, physical, and biochemical parametres were measured. RESULTS: A total of 1700 volunteers from 14 centers throughout Turkey were included in the study. Mean age was 48.03 ± 20.86 years (56.9% female). Prevalance of PS was detected in 68.9%. In the PS group, age, body mass index (BMI), waist circumference, systolic blood pressure, fasting blood glucose (FBG), lipid levels, insulin resistance, diabetes mellitus, hypertension, MS frequency, and pancreatic SWE score were increasing, and fecal elastase level was decreasing in correlation with the degree of PS. The frequency of HS was 55.5%. Hepatosteatosis [odds ratio (OR): 9.472], increased age (OR: 1.02), and BMI (OR: 1.089) were independent risk factors for the occurrence of PS. Lean-PS rate was 11.8%. The lean-PS group was predominantly female and younger than non-lean PS. Also it has lower blood pressure, FBG, liver enzymes, lipid levels, and HS rates. CONCLUSION: The frequency of PS was found 68.9% in Turkey. Its relationship was determined with age, BMI, HS, MS (and its components), pancreatic stiffness, and fecal elastase level.
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Diagnóstico por Imagen de Elasticidad , Hígado Graso , Síndrome Metabólico , Enfermedades Pancreáticas , Humanos , Turquía/epidemiología , Femenino , Persona de Mediana Edad , Masculino , Prevalencia , Adulto , Factores de Riesgo , Síndrome Metabólico/epidemiología , Enfermedades Pancreáticas/epidemiología , Hígado Graso/epidemiología , Índice de Masa Corporal , Anciano , Páncreas/diagnóstico por imagen , Elastasa Pancreática/análisis , Circunferencia de la Cintura , Resistencia a la Insulina , Glucemia/análisis , Glucemia/metabolismoRESUMEN
Acinar cystic transformation (ACT) of the pancreas is a rare non-neoplastic cystic lesion. It is difficult to distinguish from more concerning pathology, particularly a side-branch duct intraductal papillary mucinous neoplasm (IPMN). All reported cases of ACT have been clinically benign with no evidence of recurrence or malignant transformation. The Fukuoka guidelines is a classification system designed to help guide the management of IPMNs and mucinous cystic neoplasms. We report a case of ACT that was preoperatively diagnosed as a suspected side-branch IPMN. Through the application of current guidelines, the patient underwent a Whipple's procedure. We highlight the difficulties in obtaining an accurate preoperative diagnosis in cases of ACT and the current radiological and cytological methods available to clinicians.
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Quiste Pancreático , Neoplasias Intraductales Pancreáticas , Humanos , Diagnóstico Diferencial , Páncreas/patología , Páncreas/diagnóstico por imagen , Quiste Pancreático/diagnóstico , Quiste Pancreático/patología , Neoplasias Intraductales Pancreáticas/diagnóstico , Neoplasias Intraductales Pancreáticas/patología , Neoplasias Intraductales Pancreáticas/cirugía , Tomografía Computarizada por Rayos XRESUMEN
BACKGROUND: Diffusion-weighted imaging (DWI) has come up as a newer diagnostic modality for the diagnosis of early functional changes in various organs including the pancreas. DWI has shown the ability of early and accurate diagnosis of inflammatory pathologies, before the appearance of morphological changes on imaging. OBJECTIVES: The objectives of this study were to study the diagnostic accuracy of DWI in the diagnosis of early acute interstitial pancreatitis. MATERIALS AND METHODS: The present retrospective observational study was conducted at the department of radiodiagnosis of a tertiary teaching hospital for 1 year. Fifty patients who underwent magnetic resonance imaging of the pancreas with clinical or laboratory diagnosis of early pancreatitis were included in the study. The diagnostic accuracy of DWI was analyzed on the basis of quantitative (apparent diffusion coefficient [ADC] values) evaluation in the diagnosis of early acute pancreatitis. Threshold values for ADC were derived for differentiation of inflamed versus normal pancreas. Sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV) were obtained by drawing the receiver operating characteristic (ROC) curve. RESULTS: The mean ADC values in the patient group (0.882 × 10 -3 mm 2 /s ± 0.102) were significantly lower than the control group (1.178 × 10 -3 mm 2 /s ± 0.232) with P < 0.001. The ROC curve deciphered a cutoff value of 0.937 × 10 -3 mm 2 /s with a sensitivity of 84%, specificity of 86%, PPV of 85.71%, and NPV of 84.31% for diagnosis of acute pancreatitis using quantitative ADC values. CONCLUSION: DWI can thus be a succinct modality for early diagnosis of pancreatitis with excellent diagnostic accuracy and superlative advantage of lack of contrast and radiation in comparison to computed tomography scan.
Résumé Contexte:L'imagerie pondérée en diffusion (DWI) est apparue comme une nouvelle modalité de diagnostic pour le diagnostic des changements fonctionnels précoces.dans divers organes, dont le pancréas. DWI a montré la capacité de diagnostic précoce et précis des pathologies inflammatoires, avant apparition de modifications morphologiques à l'imagerie.Objectifs:Les objectifs de cette étude étaient d'étudier la précision diagnostique du CFA chez le diagnostic de pancréatite interstitielle aiguë précoce.Matériels et méthodes:La présente étude observationnelle rétrospective a été menée à le service de radiodiagnostic d'un CHU pendant 1 an. Cinquante patients ayant bénéficié d'une imagerie par résonance magnétique du les pancréas présentant un diagnostic clinique ou de laboratoire de pancréatite précoce ont été inclus dans l'étude. La précision diagnostique du DWI a été analysée sur la base d'une évaluation quantitative (valeurs du coefficient de diffusion apparent [ADC]) dans le diagnostic de la pancréatite aiguë précoce. Seuil les valeurs de l'ADC ont été dérivées pour différencier le pancréas enflammé du pancréas normal. Sensibilité, spécificité, valeur prédictive positive (VPP),et des valeurs prédictives négatives (NPV) ont été obtenues en traçant la courbe des caractéristiques de fonctionnement du récepteur (ROC).Résultats:L'ADC moyenles valeurs du groupe de patients (0.882 × 10−3 mm2/s ± 0.102) étaient significativement inférieures à celles du groupe témoin (1.178 × 10−3 mm2/s ± 0.232) avec P < 0.001. La courbe ROC a décrypté une valeur seuil de 0.937 × 10−3 mm2/s avec une sensibilité de 84 %, une spécificité de 86 %, une VPP de 85.71 %, et VPN de 84.31 % pour le diagnostic de pancréatite aiguë à l'aide des valeurs quantitatives de l'ADC.Conclusion:La DWI peut donc être une modalité succincte pour le diagnostic précoce de la pancréatite avec une excellente précision diagnostique et l'avantage exceptionnel de l'absence de contraste et de rayonnement par rapport à la tomodensitométrie.
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Imagen de Difusión por Resonancia Magnética , Pancreatitis , Valor Predictivo de las Pruebas , Sensibilidad y Especificidad , Humanos , Imagen de Difusión por Resonancia Magnética/métodos , Estudios Retrospectivos , Femenino , Masculino , Pancreatitis/diagnóstico por imagen , Pancreatitis/diagnóstico , Persona de Mediana Edad , Adulto , Enfermedad Aguda , Páncreas/diagnóstico por imagen , Páncreas/patología , Curva ROC , Diagnóstico Precoz , AncianoRESUMEN
OBJECTIVE: To assess the capacity of fetal pancreatic size, before standard blood glucose testing for screening and diagnosis, to predict maternal gestational diabetes mellitus (GDM). METHODS: This was a retrospective cohort study of low-risk pregnant women recruited during routine second-trimester fetal anatomical screening at 20-25 weeks' gestation at two ultrasound units in Israel between 2017 and 2020. The predictive performance of fetal pancreatic circumference ≥ 80th and ≥ 90th centiles and glucose challenge test (GCT) was examined for the outcome of GDM. The independent-samples t-test was used to compare mean pancreatic circumference centile between pregnancies with GDM and those without GDM. Diagnostic performance was evaluated with 2 × 2 contingency tables and receiver-operating-characteristics (ROC) curves. RESULTS: Overall, 195 women were selected for statistical analysis. Twenty-four (12.3%) women were diagnosed subsequently with GDM. The mean ± SD fetal pancreatic circumference centile was significantly higher in the GDM group compared with the non-GDM group (82.4 ± 14.6 vs 62.8 ± 27.6; P < 0.001). The pancreatic circumference centile was correlated positively with the estimated fetal weight centile (Pearson's coefficient, 0.243; P = 0.001). The 80th centile cut-off for pancreatic circumference had the highest sensitivity (70.8%) and positive predictive value (23.3%) for future maternal GDM, with the best trade-off between sensitivity and specificity achieved at the 75th centile cut-off (sensitivity, 79%; specificity, 60%). The GCT had better specificity (90.2%) and negative predictive value (97.9%) compared with both cut-offs in pancreatic circumference. The area under the ROC curve was higher for pancreatic circumference compared with GCT (0.71 vs 0.64) and only the former was statistically significant (P = 0.001). CONCLUSIONS: Fetal pancreatic circumference has a higher positive predictive capacity compared with GCT. Measuring pancreatic circumference can identify pregnancies at high risk for maternal GDM, thereby promoting earlier diagnosis and treatment, decreasing the time period during which the fetus is exposed to high maternal glucose levels and improving infant outcome. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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Diabetes Gestacional , Páncreas , Valor Predictivo de las Pruebas , Segundo Trimestre del Embarazo , Ultrasonografía Prenatal , Humanos , Femenino , Embarazo , Diabetes Gestacional/diagnóstico , Diabetes Gestacional/diagnóstico por imagen , Estudios Retrospectivos , Adulto , Páncreas/diagnóstico por imagen , Páncreas/embriología , Israel , Curva ROC , Prueba de Tolerancia a la Glucosa , Tamaño de los Órganos , Sensibilidad y Especificidad , Edad GestacionalRESUMEN
BACKGROUND: Advanced pancreatic adenocarcinoma lacks effective treatment options, and systemic gemcitabine-based chemotherapy offers only marginal survival benefits at the cost of significant toxicities and adverse events. New therapeutic options with better drug availability are warranted. This study aims to evaluate the safety and efficacy of digital subtraction angiography (DSA)-guided pancreatic arterial infusion (PAI) versus intravenous chemotherapy (IVC) using the gemcitabine and oxaliplatin (GEMOX) regimen in unresectable locally advanced or metastatic pancreatic cancer (PC) patients. MATERIALS AND METHODS: This study prospectively enrolled 51 eligible treatment-naive patients with unresectable PC to receive GEMOX treatment via PAI or IVC (1:1 ratio randomization) from December 2015 to December 2019. Cycles were repeated monthly, and each process consisted of two treatments administered bi-weekly. Overall survival (OS), progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR), 1-year survival, 6-month survival, tumor-site subgroup survival, and incidences of adverse events were compared. RESULTS: The median OS of the PAI and IVC groups were 9.93 months and 10.07 months, respectively (p = 0.3049). The median PFS of the PAI and IVC groups were 5.07 months and 4.23 months (p = 0.1088). No significant differences were found in the ORR (11.54% vs. 4%, p = 0.6312), DCR (53.85% vs. 44%, p = 0.482), and 1-year OS rate (44% vs. 20.92%, p = 0.27) in PAI and IVC groups. The 6-month OS rate was significantly higher in the PAI group (100%) than in the IVC group (83.67%) (p = 0.0173). The median OS of patients in PAI group with pancreatic head and neck tumors were significantly higher than those of body and tail tumors (12.867 months vs. 9 months, p = 0.0214). The incidences of hematologic disorders, liver function disorders, and digestive disorders in the IVC group were higher than in the PAI group (p < 0.05). CONCLUSION: GEMOX PAI therapy presented a higher 6-month OS rate and fewer adverse events than IVC in advanced pancreatic adenocarcinoma patients. Those with pancreatic head and neck tumors may yield a superior treatment outcome from PAI treatment. TRIAL REGISTRATION NUMBER: NCT02635971. DATE OF REGISTRATION: 21/12/2015.
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Adenocarcinoma , Angiografía de Substracción Digital , Protocolos de Quimioterapia Combinada Antineoplásica , Desoxicitidina , Neoplasias Pancreáticas , Humanos , Neoplasias Pancreáticas/tratamiento farmacológico , Neoplasias Pancreáticas/patología , Neoplasias Pancreáticas/mortalidad , Masculino , Femenino , Persona de Mediana Edad , Desoxicitidina/análogos & derivados , Desoxicitidina/administración & dosificación , Desoxicitidina/efectos adversos , Anciano , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Protocolos de Quimioterapia Combinada Antineoplásica/efectos adversos , Protocolos de Quimioterapia Combinada Antineoplásica/administración & dosificación , Adenocarcinoma/tratamiento farmacológico , Adenocarcinoma/mortalidad , Adenocarcinoma/patología , Infusiones Intraarteriales , Adulto , Estudios Prospectivos , Oxaliplatino/administración & dosificación , Oxaliplatino/efectos adversos , Gemcitabina , Infusiones Intravenosas , Páncreas/patología , Páncreas/diagnóstico por imagen , Compuestos OrganoplatinosRESUMEN
Pancreatitis caused by a fish bone penetrating the posterior wall of the stomach and entering the pancreas is rare. We herein report a case involving a woman in her late 30s with an approximately 1-month history of recurrent upper abdominal pain. Initial evaluation at another hospital failed to identify the cause but raised suspicion of pancreatic cancer. Computed tomography, magnetic resonance imaging, and a detailed consultation led us to suspect that the patient's pain had been caused by inadvertent ingestion of a fish bone. We used three-dimensional visualization technology to determine the location of the fish bone and informed the patient of the lesion and surgical plan through a simulated surgical demonstration. During surgery, we applied augmented reality navigation technology to remove the fish bone by a minimally invasive approach. The patient was discharged on postoperative day 3. She was followed up by telephone 24 hours after discharge. Outpatient follow-up was performed 1 week after discharge and on day 30. The patient recovered well and developed no complications. This case shows that digital medical technology can be applied in patients undergoing surgical removal of a pancreatic foreign body. Such technology assists with preoperative evaluation, patient education, and intraoperative trauma reduction.
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Cuerpos Extraños , Procedimientos Quirúrgicos Mínimamente Invasivos , Páncreas , Humanos , Femenino , Páncreas/cirugía , Páncreas/diagnóstico por imagen , Adulto , Cuerpos Extraños/cirugía , Cuerpos Extraños/diagnóstico por imagen , Procedimientos Quirúrgicos Mínimamente Invasivos/métodos , Tomografía Computarizada por Rayos X , Imagenología Tridimensional , Imagen por Resonancia MagnéticaRESUMEN
PURPOSE OF REVIEW: Radiographic imaging of the pancreas has drawn recent interest as pancreas volume may serve as a biomarker in identifying the likelihood of diabetes development, subtyping diabetes, and identifying prognostic indicators of poor ultimate outcomes. In this review, the role of pancreas imaging is discussed in various forms of diabetes including type 1 diabetes (T1D), type 2 diabetes (T2D), and diabetes of the exocrine pancreas, particularly diabetes following acute or chronic pancreatitis. RECENT FINDINGS: Recent literature of quantitative pancreatic imaging correlating with various forms of diabetes was reviewed. Imaging-derived pancreas volumes are lower in individuals with diabetes, in particular those with T1D. Additionally, morphologic changes, enhancement characteristics, fat content, and MRI signal changes have been observed in different diabetes subtypes. These characteristics, as well as potential confounding variables, are reviewed. Additionally, future areas of research in MRI, CT radiomics, and pancreatitis-related imaging predictors of diabetes are discussed. SUMMARY: Increased understanding of pancreas imaging features which predict diabetes and gauge prognosis has the potential to identify at-risk individuals and will become increasingly important in diabetes care. This article reviews the current knowledge of common pancreas imaging features as well as future directions of ongoing research in diabetes imaging.
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Diabetes Mellitus Tipo 1 , Diabetes Mellitus Tipo 2 , Imagen por Resonancia Magnética , Páncreas , Humanos , Imagen por Resonancia Magnética/métodos , Páncreas/diagnóstico por imagen , Páncreas/patología , Diabetes Mellitus Tipo 1/complicaciones , Diabetes Mellitus Tipo 2/complicaciones , Pronóstico , Tomografía Computarizada por Rayos X , Pancreatitis/diagnóstico por imagen , Pancreatitis/etiología , Pancreatitis/terapiaRESUMEN
AIMS: To investigate the utilization of an end-to-end multimodal convolutional model in the rapid and accurate diagnosis of pancreatic diseases using abdominal CT images. MATERIALS AND METHODS: In this study, a novel lightweight label-free end-to-end multimodal network (eeMulNet) model was proposed for the rapid and precise diagnosis of abnormal pancreas. The eeMulNet consists of two steps: pancreatic region localization and multimodal CT diagnosis integrating textual and image data. A research dataset comprising 715 CT scans with various types of pancreas diseases and 228 CT scans from a control group was collected. The training set and independent test set for the multimodal classification network were randomly divided in an 8:2 ratio (755 for training and 188 for testing). RESULTS: The eeMulNet model demonstrated outstanding performance on an independent test set of 188 CT scans (Normal: 45, Abnormal: 143), with an area under the curve (AUC) of 1.0, accuracy of 100%, and sensitivity of 100%. The average testing duration per patient was 41.04 seconds, while the classification network took only 0.04 seconds. CONCLUSIONS: The proposed eeMulNet model offers a promising approach for the diagnosis of pancreatic diseases. It can support the identification of suspicious cases during daily radiology work and enhance the accuracy of pancreatic disease diagnosis. The codes and models of eeMulNet are publicly available at Rudeguy1/eeMulNet (github.com).
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Páncreas , Enfermedades Pancreáticas , Tomografía Computarizada por Rayos X , Humanos , Tomografía Computarizada por Rayos X/métodos , Enfermedades Pancreáticas/diagnóstico por imagen , Femenino , Páncreas/diagnóstico por imagen , Masculino , Imagenología Tridimensional/métodos , Persona de Mediana Edad , Adulto , Anciano , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Sensibilidad y Especificidad , Diagnóstico DiferencialRESUMEN
OBJECTIVES: We aim to assess the early use of contrast-enhanced computed tomography (CECT) of patients with severe acute pancreatitis (SAP) using the computed tomography severity index (CTSI) in prognosis prediction. The CTSI combines quantification of pancreatic and extrapancreatic inflammation with the extent of pancreatic necrosis. METHODS: Post-hoc retrospective analysis of a large, multicentric database (44 institutions) of SAP patients in Japan. The area under the curve (AUC) of the CTSI for predicting mortality and the odds ratio (OR) of the extent of pancreatic inflammation and necrosis were calculated using multivariable analysis. RESULTS: In total, 1097 patients were included. The AUC of the CTSI for mortality was 0.65 (95 % confidence interval [CI:] [0.59-0.70]; p < 0.001). In multivariable analysis, necrosis 30-50 % and >50 % in low-enhanced pancreatic parenchyma (LEPP) was independently associated with a significant increase in mortality, with OR 2.04 and 95 % CI 1.01-4.12 (P < 0.05) and OR 3.88 and 95 % CI 2.04-7.40 (P < 0.001), respectively. However, the extent of pancreatic inflammation was not associated with mortality, regardless of severity. CONCLUSIONS: The degree of necrosis in LEPP assessed using early CECT of SAP was a better predictor of mortality than the extent of pancreatic inflammation.
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Medios de Contraste , Necrosis , Páncreas , Pancreatitis , Tomografía Computarizada por Rayos X , Humanos , Femenino , Masculino , Persona de Mediana Edad , Anciano , Pancreatitis/diagnóstico por imagen , Pancreatitis/patología , Pancreatitis/mortalidad , Estudios Retrospectivos , Páncreas/diagnóstico por imagen , Páncreas/patología , Estudios de Cohortes , Pronóstico , Adulto , Índice de Severidad de la Enfermedad , Inflamación/diagnóstico por imagen , Japón/epidemiología , Pancreatitis Aguda Necrotizante/diagnóstico por imagen , Pancreatitis Aguda Necrotizante/mortalidad , Pancreatitis Aguda Necrotizante/patologíaRESUMEN
OBJECTIVES: to predict liver injury in acute pancreatitis (AP) patients by establishing a radiomics model based on contrast-enhanced computed tomography (CECT). METHODS: a total of 1223 radiomic features were extracted from late arterial-phase pancreatic CECT images of 209 AP patients (146 in the training cohort and 63 in the test cohort), and the optimal radiomic features retained after dimensionality reduction by least absolute shrinkage and selection operator (LASSO) were used to construct a radiomic model through logistic regression analysis. In addition, clinical features were collected to develop a clinical model, and a joint model was established by combining the best radiomic features and clinical features to evaluate the practicality and application value of the radiomic models, clinical model and combined model. RESULTS: four potential features were selected from the pancreatic parenchyma to construct the radiomic model, and the area under the receiver operating characteristic curve (AUC) of the radiomic model was significantly greater than that of the clinical model for both the training cohort (0.993 vs. 0.653, p = 0.000) and test cohort (0.910 vs. 0.574, p = 0.000). The joint model had a greater AUC than the radiomics model for both the training cohort (0.997 vs. 0.993, p = 0.357) and test cohort (0.925 vs. 0.910, p = 0.302). CONCLUSIONS: the radiomic model based on CECT has good performance in predicting liver injury in AP patients and can guide clinical decision-making and improve the prognosis of patients with AP.
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Medios de Contraste , Pancreatitis , Tomografía Computarizada por Rayos X , Humanos , Pancreatitis/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Femenino , Masculino , Persona de Mediana Edad , Adulto , Anciano , Enfermedad Aguda , Curva ROC , Estudios Retrospectivos , Hígado/diagnóstico por imagen , Hígado/lesiones , Páncreas/diagnóstico por imagen , Páncreas/lesiones , RadiómicaRESUMEN
Solid pseudopapillary neoplasm of the pancreas (SPNP) is a rare entity. In this study, we present a woman in her 20's who presented for evaluation of two separate pancreatic masses. On imaging and biopsy, the tail lesion was thought to be a neuroendocrine tumour and the body lesion was thought to be a metastatic lymph node. The patient was brought to the operating room and underwent a distal pancreatectomy and splenectomy. The patient had an uneventful postoperative course and was discharged home on postoperative day 4. Pathology confirmed both masses were consistent with the diagnosis of well-differentiated SPNP with no signs of malignancy including lymphovascular or perineural invasion, or lymph node involvement.
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Pancreatectomía , Neoplasias Pancreáticas , Esplenectomía , Humanos , Neoplasias Pancreáticas/cirugía , Neoplasias Pancreáticas/patología , Neoplasias Pancreáticas/diagnóstico por imagen , Neoplasias Pancreáticas/diagnóstico , Femenino , Pancreatectomía/métodos , Carcinoma Papilar/cirugía , Carcinoma Papilar/patología , Carcinoma Papilar/diagnóstico por imagen , Carcinoma Papilar/diagnóstico , Adulto Joven , Diagnóstico Diferencial , Páncreas/patología , Páncreas/diagnóstico por imagen , Tomografía Computarizada por Rayos XRESUMEN
PURPOSE: For reliable DCE MRI parameter estimation, k-space undersampling is essential to meet resolution, coverage, and signal-to-noise requirements. Pseudo-spiral (PS) sampling achieves this by sampling k-space on a Cartesian grid following a spiral trajectory. The goal was to optimize PS k-space sampling patterns for abdomin al DCE MRI. METHODS: The optimal PS k-space sampling pattern was determined using an anthropomorphic digital phantom. Contrast agent inflow was simulated in the liver, spleen, pancreas, and pancreatic ductal adenocarcinoma (PDAC). A total of 704 variable sampling and reconstruction approaches were created using three algorithms using different parametrizations to control sampling density, halfscan and compressed sensing regularization. The sampling patterns were evaluated based on image quality scores and the accuracy and precision of the DCE pharmacokinetic parameters. The best and worst strategies were assessed in vivo in five healthy volunteers without contrast agent administration. The best strategy was tested in a DCE scan of a PDAC patient. RESULTS: The best PS reconstruction was found to be PS-diffuse based, with quadratic distribution of readouts on a spiral, without random shuffling, halfscan factor of 0.8, and total variation regularization of 0.05 in the spatial and temporal domains. The best scoring strategy showed sharper images with less prominent artifacts in healthy volunteers compared to the worst strategy. Our suggested DCE sampling strategy also showed high quality DCE images in the PDAC patient. CONCLUSION: Using an anthropomorphic digital phantom, we identified an optimal PS sampling strategy for abdominal DCE MRI, and demonstrated feasibility in a PDAC patient.
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Abdomen , Algoritmos , Medios de Contraste , Procesamiento de Imagen Asistido por Computador , Imagen por Resonancia Magnética , Neoplasias Pancreáticas , Fantasmas de Imagen , Humanos , Imagen por Resonancia Magnética/métodos , Medios de Contraste/química , Abdomen/diagnóstico por imagen , Procesamiento de Imagen Asistido por Computador/métodos , Neoplasias Pancreáticas/diagnóstico por imagen , Páncreas/diagnóstico por imagen , Hígado/diagnóstico por imagen , Relación Señal-Ruido , Carcinoma Ductal Pancreático/diagnóstico por imagen , Adulto , Masculino , Bazo/diagnóstico por imagen , Voluntarios Sanos , Femenino , Interpretación de Imagen Asistida por Computador/métodos , Reproducibilidad de los ResultadosRESUMEN
Importance: Diagnosing solid lesions in the pancreas via endoscopic ultrasonographic (EUS) images is challenging. Artificial intelligence (AI) has the potential to help with such diagnosis, but existing AI models focus solely on a single modality. Objective: To advance the clinical diagnosis of solid lesions in the pancreas through developing a multimodal AI model integrating both clinical information and EUS images. Design, Setting, and Participants: In this randomized crossover trial conducted from January 1 to June 30, 2023, from 4 centers across China, 12 endoscopists of varying levels of expertise were randomly assigned to diagnose solid lesions in the pancreas with or without AI assistance. Endoscopic ultrasonographic images and clinical information of 439 patients from 1 institution who had solid lesions in the pancreas between January 1, 2014, and December 31, 2022, were collected to train and validate the joint-AI model, while 189 patients from 3 external institutions were used to evaluate the robustness and generalizability of the model. Intervention: Conventional or AI-assisted diagnosis of solid lesions in the pancreas. Main Outcomes and Measures: In the retrospective dataset, the performance of the joint-AI model was evaluated internally and externally. In the prospective dataset, diagnostic performance of the endoscopists with or without the AI assistance was compared. Results: The retrospective dataset included 628 patients (400 men [63.7%]; mean [SD] age, 57.7 [27.4] years) who underwent EUS procedures. A total of 130 patients (81 men [62.3%]; mean [SD] age, 58.4 [11.7] years) were prospectively recruited for the crossover trial. The area under the curve of the joint-AI model ranged from 0.996 (95% CI, 0.993-0.998) in the internal test dataset to 0.955 (95% CI, 0.940-0.968), 0.924 (95% CI, 0.888-0.955), and 0.976 (95% CI, 0.942-0.995) in the 3 external test datasets, respectively. The diagnostic accuracy of novice endoscopists was significantly enhanced with AI assistance (0.69 [95% CI, 0.61-0.76] vs 0.90 [95% CI, 0.83-0.94]; P < .001), and the supplementary interpretability information alleviated the skepticism of the experienced endoscopists. Conclusions and Relevance: In this randomized crossover trial of diagnosing solid lesions in the pancreas with or without AI assistance, the joint-AI model demonstrated positive human-AI interaction, which suggested its potential to facilitate a clinical diagnosis. Nevertheless, future randomized clinical trials are warranted. Trial Registration: ClinicalTrials.gov Identifier: NCT05476978.
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Inteligencia Artificial , Estudios Cruzados , Humanos , Masculino , Femenino , Persona de Mediana Edad , Anciano , Endosonografía/métodos , Neoplasias Pancreáticas/diagnóstico , Neoplasias Pancreáticas/diagnóstico por imagen , Adulto , Páncreas/diagnóstico por imagen , China , Estudios RetrospectivosRESUMEN
Pancreatic cancer is a highly lethal disease with a poor prognosis. Its early diagnosis and accurate treatment mainly rely on medical imaging, so accurate medical image analysis is especially vital for pancreatic cancer patients. However, medical image analysis of pancreatic cancer is facing challenges due to ambiguous symptoms, high misdiagnosis rates, and significant financial costs. Artificial intelligence (AI) offers a promising solution by relieving medical personnel's workload, improving clinical decision-making, and reducing patient costs. This study focuses on AI applications such as segmentation, classification, object detection, and prognosis prediction across five types of medical imaging: CT, MRI, EUS, PET, and pathological images, as well as integrating these imaging modalities to boost diagnostic accuracy and treatment efficiency. In addition, this study discusses current hot topics and future directions aimed at overcoming the challenges in AI-enabled automated pancreatic cancer diagnosis algorithms.
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Algoritmos , Inteligencia Artificial , Neoplasias Pancreáticas , Humanos , Neoplasias Pancreáticas/diagnóstico por imagen , Neoplasias Pancreáticas/diagnóstico , Neoplasias Pancreáticas/patología , Páncreas/diagnóstico por imagen , Páncreas/patología , Procesamiento de Imagen Asistido por Computador/métodos , Interpretación de Imagen Asistida por Computador/métodos , Tomografía Computarizada por Rayos X/métodos , Imagen por Resonancia Magnética/métodosRESUMEN
BACKGROUND: Pancreatic cysts in autosomal dominant polycystic kidney disease (ADPKD) correlate with PKD2 mutations, which have a different phenotype than PKD1 mutations. However, pancreatic cysts are commonly overlooked by radiologists. Here, we automate the detection of pancreatic cysts on abdominal MRI in ADPKD. METHODS: Eight nnU-Net-based segmentation models with 2D or 3D configuration and various loss functions were trained on positive-only or positive-and-negative datasets, comprising axial and coronal T2-weighted MR images from 254 scans on 146 ADPKD patients with pancreatic cysts labeled independently by two radiologists. Model performance was evaluated on test subjects unseen in training, comprising 40 internal, 40 external, and 23 test-retest reproducibility ADPKD patients. RESULTS: Two radiologists agreed on 52% of cysts labeled on training data, and 33%/25% on internal/external test datasets. The 2D model with a loss of combined dice similarity coefficient and cross-entropy trained with the dataset with both positive and negative cases produced an optimal dice score of 0.7 ± 0.5/0.8 ± 0.4 at the voxel level on internal/external validation and was thus used as the best-performing model. In the test-retest, the optimal model showed superior reproducibility (83% agreement between scan A and B) in segmenting pancreatic cysts compared to six expert observers (77% agreement). In the internal/external validation, the optimal model showed high specificity of 94%/100% but limited sensitivity of 20%/24%. CONCLUSIONS: Labeling pancreatic cysts on T2 images of the abdomen in patients with ADPKD is challenging, deep learning can help the automated detection of pancreatic cysts, and further image quality improvement is warranted.
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Aprendizaje Profundo , Imagen por Resonancia Magnética , Quiste Pancreático , Riñón Poliquístico Autosómico Dominante , Humanos , Riñón Poliquístico Autosómico Dominante/diagnóstico por imagen , Riñón Poliquístico Autosómico Dominante/complicaciones , Riñón Poliquístico Autosómico Dominante/patología , Quiste Pancreático/diagnóstico por imagen , Quiste Pancreático/patología , Imagen por Resonancia Magnética/métodos , Femenino , Masculino , Persona de Mediana Edad , Adulto , Reproducibilidad de los Resultados , Páncreas/diagnóstico por imagen , Páncreas/patología , Interpretación de Imagen Asistida por Computador/métodos , AncianoAsunto(s)
Neoplasias Pancreáticas , Humanos , Neoplasias Pancreáticas/patología , Neoplasias Pancreáticas/cirugía , Neoplasias Pancreáticas/diagnóstico , Neoplasias Pancreáticas/diagnóstico por imagen , Femenino , Carcinoma Papilar/patología , Carcinoma Papilar/cirugía , Carcinoma Papilar/diagnóstico por imagen , Carcinoma Papilar/diagnóstico , Pancreatectomía/métodos , Adulto , Páncreas/patología , Páncreas/diagnóstico por imagenRESUMEN
BACKGROUND: There are no guidelines in the literature for the use of a computed tomography (CT) protocol in the initial phase of acute pancreatitis (AP). PURPOSE: To evaluate the contribution of single portal venous phase CT compared to triple-phase CT protocol, performed in the initial phase of AP for severity assessment. MATERIAL AND METHODS: In this retrospective study, a total of 175 patients with acute pancreatitis who underwent initial triple-phase CT protocol (non-contrast, arterial phase, and portal venous phase) between D3 and D7 after the onset of symptoms were included. Analysis of AP severity and complications was independently assessed by two readers using three validated CT severity scores (CTSI, mCTSI, EPIC). All scores were applied to the triple-phase CT protocol and compared to the single portal venous phase. Inter-observer analyses were also performed. RESULTS: No significant difference whatever the severity score was observed after analysis of the single portal venous phase compared with the triple-phase CT protocol (interstitial edematous pancreatitis: CTSI: 2 vs. 2, mCTSI: 2 vs. 2, EPIC: 1 vs. 1; necrotizing pancreatitis: CTSI: 6 vs. 6, mCTSI: 8 vs. 8, EPIC: 5 vs. 5). Inter-observer agreement was excellent (ICC = 0.96-0.99), whatever the severity score. CONCLUSION: A triple-phase CT protocol performed at the initial phase of AP was no better than a single portal venous for assessing the severity of complications and could lead to a 63% reduction in irradiation.