RESUMO
BACKGROUND AND AIMS: EUS-guided radiofrequency ablation (EUS-RFA) has emerged as an alternative for the local treatment of unresectable pancreatic ductal adenocarcinoma (PDAC). We assessed the feasibility and safety of EUS-RFA in patients with unresectable PDAC. METHODS: This study followed an historic cohort compounded by locally advanced (LA-) and metastatic (m)PDAC-naïve patients who underwent EUS-RFA between October 2019 and March 2022. EUS-RFA was performed with a 19-gauge needle electrode with a 10-mm active tip for energy delivery. Study primary endpoints were feasibility, safety, and clinical follow-up, whereas secondary endpoints were performance status (PS), local control, and overall survival (OS). RESULTS: Twenty-six patients were selected: 15 with locally advanced pancreatic duct adenocarcinoma (LA-PDAC) and 11 with metastatic pancreatic duct adenocarcinoma (mPDAC). Technical success was achieved in all patients with no major adverse events. Six months after EUS-RFA, OS was seen in 11 of 26 patients (42.3%), with significant PS improvement (P = .03). Local control was achieved, with tumor reduction from 39.5 mm to 26 mm (P = .04). A post-treatment hypodense necrotic area was observed at the 6-month follow-up in 11 of 11 patients who were still alive. Metastatic disease was a significant factor for worsening OS (hazard ratio, 5.021; 95% confidence interval, 1.589-15.87; P = .004). CONCLUSIONS: EUS-RFA for the treatment of pancreatic adenocarcinoma is a minimally invasive and safe technique that may have an important role as targeted therapy for local treatment of unresectable cases and as an alternative for poor surgical candidates. Also, RFA may play a role in downstaging cancer with a potential increase in OS in nonmetastatic cases. Large prospective cohorts are required to evaluate this technique in clinical practice.
Assuntos
Carcinoma Ductal Pancreático , Endossonografia , Neoplasias Pancreáticas , Ablação por Radiofrequência , Humanos , Neoplasias Pancreáticas/cirurgia , Neoplasias Pancreáticas/patologia , Neoplasias Pancreáticas/diagnóstico por imagem , Masculino , Feminino , Carcinoma Ductal Pancreático/cirurgia , Carcinoma Ductal Pancreático/patologia , Carcinoma Ductal Pancreático/diagnóstico por imagem , Idoso , Endossonografia/métodos , Pessoa de Meia-Idade , Ablação por Radiofrequência/métodos , Estudos de Coortes , Estudos de Viabilidade , Idoso de 80 Anos ou mais , Ultrassonografia de Intervenção , Estudos Retrospectivos , Resultado do TratamentoRESUMO
BACKGROUND AND AIMS: EUS is a high-skill technique that requires numerous procedures to achieve competence. However, training facilities are limited worldwide. Convolutional neural network (CNN) models have been previously implemented for object detection. We developed 2 EUS-based CNN models for normal anatomic structure recognition during real-time linear- and radial-array EUS evaluations. METHODS: The study was performed from February 2020 to June 2022. Consecutive patient videos of linear- and radial-array EUS videos were recorded. Expert endosonographers identified and labeled 20 normal anatomic structures within the videos for training and validation of the CNN models. Initial CNN models (CNNv1) were developed from 45 videos and the improved models (CNNv2) from an additional 102 videos. CNN model performance was compared with that of 2 expert endosonographers. RESULTS: CNNv1 used 45,034 linear-array EUS frames and 21,063 radial-array EUS frames. CNNv2 used 148,980 linear-array EUS frames and 128,871 radial-array EUS frames. Linear-array CNNv1 and radial-array CNNv1 achieved a 75.65% and 71.36% mean average precision (mAP) with a total loss of .19 and .18, respectively. Linear-array CNNv2 obtained an 88.7% mAP with a .06 total loss, whereas radial-array CNNv2 achieved an 83.5% mAP with a .07 total loss. CNNv2 accurately detected all studied normal anatomic structures with a >98% observed agreement during clinical validation. CONCLUSIONS: The proposed CNN models accurately recognize the normal anatomic structures in prerecorded videos and real-time EUS. Prospective trials are needed to evaluate the impact of these models on the learning curves of EUS trainees.
Assuntos
Endossonografia , Redes Neurais de Computação , Humanos , Endossonografia/métodos , Estudos Prospectivos , Gravação de VideoteipeRESUMO
BACKGROUND: We aimed to develop a convolutional neural network (CNN) model for detecting neoplastic lesions during real-time digital single-operator cholangioscopy (DSOC) and to clinically validate the model through comparisons with DSOC expert and nonexpert endoscopists. METHODS: In this two-stage study, we first developed and validated CNN1. Then, we performed a multicenter diagnostic trial to compare four DSOC experts and nonexperts against an improved model (CNN2). Lesions were classified into neoplastic and non-neoplastic in accordance with Carlos Robles-Medranda (CRM) and Mendoza disaggregated criteria. The final diagnosis of neoplasia was based on histopathology and 12-month follow-up outcomes. RESULTS: In stage I, CNN2 achieved a mean average precision of 0.88, an intersection over the union value of 83.24â%, and a total loss of 0.0975. For clinical validation, a total of 170 videos from newly included patients were analyzed with the CNN2. Half of cases (50â%) had neoplastic lesions. This model achieved significant accuracy values for neoplastic diagnosis, with a 90.5â% sensitivity, 68.2â% specificity, and 74.0â% and 87.8â% positive and negative predictive values, respectively. The CNN2 model outperformed nonexpert #2 (area under the receiver operating characteristic curve [AUC]-CRM 0.657 vs. AUC-CNN2 0.794, Pâ<â0.05; AUC-Mendoza 0.582 vs. AUC-CNN2 0.794, Pâ<â0.05), nonexpert #4 (AUC-CRM 0.683 vs. AUC-CNN2 0.791, Pâ<â0.05), and expert #4 (AUC-CRM 0.755 vs. AUC-CNN2 0.848, Pâ<â0.05; AUC-Mendoza 0.753 vs. AUC-CNN2 0.848, Pâ<â0.05). CONCLUSIONS: The proposed CNN model distinguished neoplastic bile duct lesions with good accuracy and outperformed two nonexpert and one expert endoscopist.
Assuntos
Inteligência Artificial , Neoplasias , Humanos , Redes Neurais de Computação , Curva ROC , Valor Preditivo dos TestesRESUMO
BACKGROUND: Chronic esophageal conditions (CEC) are associated with significant disease-related burden, disability, and costs. Health-related quality of life (HRQOL) constructs are intended to capture the physical, mental, social, and emotional aspects of a patient's life and how health status impacts these domains. The Northwestern Esophageal Quality of Life (NEQOL) can be used among esophageal diseases while maintaining sensitivity to specific conditions. We aimed to translate, cross-cultural adapt, and validate the NEQOL into Spanish. METHODS: After language and cross-cultural adaptation, the NEQOL was applied to an outpatient clinic-based population in a single tertiary center. We analyzed the internal consistency, construct, criterion validity, and test-retest reliability of the questionnaire. The criterion validity was tested against the SF-12 questionnaire. KEY RESULTS: After completing the translation process, no item was considered problematic. A total of 385 patients were included in the validation study. The internal consistency (Cronbach's alpha) for the total NEQOL-S score was 0.89. The NEQOL-S questionnaire showed moderate test-retest reliability (ICC = 0.828; 95% CI 0.755-0.881; p < 0.001). Criterion validity showed good coherence when correlated with the SF-12 survey (R2 = 0.538; 95% CI 0.491-0.585, p < 0.001). CONCLUSIONS AND INFERENCES: The translated and cross-culturally adapted NEQOL-S showed good psychometric properties that allow its use in Spanish-speaking patients suffering from CEC.
Assuntos
Idioma , Qualidade de Vida , Humanos , Reprodutibilidade dos Testes , Inquéritos e Questionários , Traduções , Comparação TransculturalRESUMO
BACKGROUND: Endoscopic ultrasound (EUS) can detect small lesions throughout the digestive tract; however, it remains challenging to accurately identify malignancies with this approach. EUS elastography measures tissue hardness, by which malignant and nonmalignant pancreatic masses (PMs) and lymph nodes (LNs) can be differentiated. However, there is currently little information regarding the strain ratio (SR) cutoff in Hispanic populations. AIM: To determine the diagnostic accuracy of EUS elastography for PMs and LNs with an SR cutoff value in Hispanics. METHODS: A retrospective study of patients who underwent EUS elastography for PMs between December 2013 and December 2014. A qualitative (analysis of color maps) and quantitative (SR) analysis of PMs and their associated LNs was performed. The accuracy of EUS elastography in identifying malignant PMs and LNs and cutoff value for SR were analyzed. A PM and/or its associated LNs were considered malignant based on histopathological findings from fine-needle aspiration biopsy samples. RESULTS: A sample of 121 patients was included, 45.4% of whom were female. 69 (57.0%) PMs were histologically malignant, with a median SR of 50.4 vs 33.0 for malignant vs nonmalignant masses (P < 0.001). EUS evaluation identified associated LNs in 43/121 patients (35.5%), in whom 22/43 (51.2%) patients had histologically confirmed malignant diagnosis, with a median SR of 30 vs 40 for malignant vs nonmalignant LNs (P = 0.7182). In detecting malignancy in PMs, an SR cutoff value of > 21.5 yielded a sensitivity of 94.2%, while a cutoff value of > 121 yielded a specificity of 96.2.2%. There were significant differences in the Giovannini scores, a previously established elastic score system, between the patients grouped by their final histology results (P < 0.001). For LNs, SR cutoff values of > 14.0 and > 155 yielded a sensitivity of 90.9% and a specificity of 95.2%, respectively, in detecting malignancy. CONCLUSION: EUS elastography is a helpful technique for the diagnosis of solid PMs and their associated LNs. The proposed SR cutoff values have a high sensitivity and specificity for the detection of malignancy.