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Nagayama R, Ueki T, Shimizu Y, Hijioka S, Nakamura M, Kitano M, Hara K, Masamune A, Kin T, Hanada K, Koshita S, Yamada R, Takenaka M, Itoi T, Yanagisawa A, Otuka T, Hirono S, Kanno A, Ideno N, Kuwahara T, Shimizu A, Kamata K, Asai Y, Takeyama Y. Is preoperative pancreatic juice cytology useful for determining therapeutic strategies for patients with intraductal papillary mucinous neoplasm of the pancreas? J Hepatobiliary Pancreat Sci 2024; 31:183-192. [PMID: 38084510 DOI: 10.1002/jhbp.1394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Revised: 10/04/2023] [Accepted: 10/11/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND We compared the results of preoperative pancreatic juice cytology (PJC) and final pathological diagnosis after resection in patients who underwent resection of intraductal papillary mucinous neoplasm (IPMN) of the pancreas to determine whether preoperative PJC can help determine therapeutic strategies. METHODS Of 1130 patients who underwent surgical resection IPMN at 11 Japanese tertiary institutions, the study included 852 patients who underwent preoperative PJC guided by endoscopic retrograde cholangiopancreatography (ERCP). RESULTS The accuracy of preoperative PJC for differentiation between cancerous and noncancerous lesions were 55% for IPMN overall; 59% for the branch duct type; 49% for the main pancreatic duct type; 53% for the mixed type, respectively. On classifying IPMN according to the diameters of the mural nodule (MN) and main pancreatic duct (MPD), the corresponding values for diagnostic performance were 40% for type 1 (MN ≥5 mm and MPD ≥ 10 mm); 46% for type 2 (MN ≥5 mm and MPD < 10 mm); 61% for type 3 (MN < 5 mm and MPD ≥ 10 mm); 72% for type 4 (MN < 5 mm and MPD < 10 mm), respectively. CONCLUSIONS PJC in IPMN is not a recommended examination because of its low overall sensitivity and no significant difference in diagnostic performance by type, location, or subclassification. Although the sensitivity is low, the positive predictive value is high, so we suggest that pancreatic juice cytology be performed only in cases where the patient is not sure about surgery.
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Affiliation(s)
- Rintaro Nagayama
- Department of Gastroenterology, Fukuoka University Chikushi Hospital, Fukuoka, Japan
| | - Toshiharu Ueki
- Department of Gastroenterology, Fukuoka University Chikushi Hospital, Fukuoka, Japan
| | - Yasuhiro Shimizu
- Department of Gastroenterological Surgery, Aichi Cancer Center Hospital, Aichi, Japan
| | - Susumu Hijioka
- Department of Hepatobiliary and Pancreatic Oncology, National Cancer Center, Tokyo, Japan
| | - Masafumi Nakamura
- Department of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Masayuki Kitano
- Second Department of Internal Medicine, Wakayama Medical University School of Medicine, Wakayama, Japan
| | - Kazuo Hara
- Department of Gastroenterology, Aichi Cancer Center Hospital, Aichi, Japan
| | - Atsushi Masamune
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Miyagi, Japan
| | - Toshifumi Kin
- Center for Gastroenterology, Teine-Keijinkai Hospital, Hokkaido, Japan
| | - Keiji Hanada
- Department of Gastroenterology, JA Onomichi General Hospital, Hiroshima, Japan
| | - Shinsuke Koshita
- Department of Gastroenterology, Sendai City Medical Center Sendai Open Hospital, Miyagi, Japan
| | - Reiko Yamada
- Department of Gastroenterology and Hepatology, Mie University Graduate School of Medicine, Mie, Japan
| | - Mamoru Takenaka
- Department of Gastroenterology and Hepatology, Kindai University Faculty of Medicine, Osaka-sayama, Japan
| | - Takao Itoi
- Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan
| | - Akio Yanagisawa
- Department of Pathology and Laboratory Medicine, Kyoto First Red Cross Hospital, Kyoto, Japan
| | - Takao Otuka
- Department of Digestive Surgery, Breast and Thyroid Surgery, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Seiko Hirono
- Department of Hepato-Biliary-Pancreatic Surgery, Hyogo College of Medicine, Hyogo, Japan
| | - Atsushi Kanno
- Department of Medicine, Division of Gastroenterology, Jichi Medical University, Tochigi, Japan
| | - Noboru Ideno
- Department of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takamichi Kuwahara
- Department of Gastroenterology, Aichi Cancer Center Hospital, Aichi, Japan
| | - Akinori Shimizu
- Department of Gastroenterology, JA Onomichi General Hospital, Hiroshima, Japan
| | - Ken Kamata
- Department of Gastroenterology and Hepatology, Kindai University Faculty of Medicine, Osaka-sayama, Japan
| | - Yasutsugu Asai
- Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan
| | - Yoshifumi Takeyama
- Department of Surgery, Kinki University School of Medicine, Osaka-sayama, Japan
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Yagi N, Suzuki S, Hirota N, Arita T, Otuka T, Yamashita T. Prediction of persistent form of atrial fibrillation using left atrial morphology on preprocedural computed tomography: application of radiomics. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Radiomics is a comprehensive analysis methodology of medical image and involves the extraction of numerous features from standard imaging. Its usefulness has been reported mainly in the field of cancer for diagnosis and prediction of prognosis. In the territory of cardiac imaging, several reports have investigated the utility of radiomics for classifying the risk of prognosis in coronary artery disease, and few practical applications have been reported for patients with atrial fibrillation (AF) who underwent catheter ablation (CA).
Purpose
The objective of this study was to evaluate the utility of radiomics analysis applying to the preprocedural cardiac computerized tomography (CT) in AF patients.
Methods
We analyzed 525 consecutive three-dimensional CT in patients with AF who underwent CA. After marking the region of interest on left atrium (LA) (including the root of pulmonary veins) semiautomatically, 107 radiomics feature values were obtained by Python program. We calculated the amount of representative statistics for each radiomics feature for prediction of persistent AF (PeAF) (Wald statistic in logistic regression analysis) and LA diameter (LAD) (coefficient correlation), respectively. To compare the distribution of the two statistics, the relative importance (calculated as the ratio of statistic to the maximum statistics among 107 radiomics features [%]) was calculated for each statistic. Further, we compared the area under the curve (AUC) in receiver operation characteristic (ROC) curve analysis for predicting PeAF between radiomics features (multivariate model) and LAD (single parameter).
Results
In 525 study patients (age 63±10 years old and male 80%), 253 (48%) were PeAF and remaining were paroxysmal AF (PAF). LAD was 43±6 mm and 38±6 mm in patients with PeAF and PAF, respectively. The relative importance of the two statistics (Wald statistic for PeAF and coefficient correlation for LAD) of 107 radiomics features are displayed in Figure 1, which shows similar distribution of two statistics. It means the close relationship between LA morphology and the form of PeAF in AF patients and the radiomics features possibly well explain the relationship. In Figure 2, the predictive capability for PeAF was compared between radiomics feature values and LAD, where the AUC was 0.85 (95% confidence interval [CI], 0.82–0.88) and 0.73 (95% CI, 0.69–0.78) for radiomics feature values and LAD, respectively (Delong test, P<0.001).
Conclusion
We applied the radiomics features for the evaluation of LA morphology. The predictive capability for PeAF in the prediction model with the radiomics feature values was much better than that with LAD alone. Since radiomics feature analysis yields a huge number of numerical values representing the LA morphology in a reproducible manner, it would provide a new direction to construct a good prediction model using machine learning including artificial intelligence out of a routine cardiac CT scan.
Funding Acknowledgement
Type of funding sources: None.
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Affiliation(s)
- N Yagi
- Cardiovascular Institute , Tokyo , Japan
| | - S Suzuki
- Cardiovascular Institute , Tokyo , Japan
| | - N Hirota
- Cardiovascular Institute , Tokyo , Japan
| | - T Arita
- Cardiovascular Institute , Tokyo , Japan
| | - T Otuka
- Cardiovascular Institute , Tokyo , Japan
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Andrieu S, Barberger-Gateau P, Raffaitin C, Berr C, Tzourio C, Dartigues JF, Gin H, Fitten LJ, Ortiz F, Fairbanks L, Bartzokis G, Lu P, Ringman J, Heyn PC, Locher JL, Salvà A, Andrieu S, Fernández E, Vellas B, van de Rest O, Geleijnse JM, Kok FJ, van Staveren WA, Beekman ATF, Hoefnagels WHL, de Groot CPGM, Angevaren M, Aufdemkampe G, Verhaar HJJ, Aleman A, Vannees L, Arkin S, Florez H, Gerstein H, Sheridan P, Bosch J, Goldberg R, Kaspar KM, Drawert SM, Marcus RL, Kidde J, Dibble L, Addison O, LaStayo PC, Scarmeas N, Stern Y, Schupf N, Luchsinger JA, Sharkey JR, Laditka JN, Laditka SB, Liu R, Hochhalter A, Robare JF, Türner N, Judge M, Foster TC, Erdos B, Cudykier I, Scarpace PJ, Weiss LA, Bergstrom J, Kritz-Silverstein D, Barrett-Connor E, Yurko-Mauro K, Nelson E, Quinn J, Sattler FR, Castaneda-Sceppa C, Binder EF, Schroeder ET, Wang Y, Bhasin S, Kawakubo M, Stewart Y, Hahn C, Colletti P, Roubenoff R, Yarasheski KE, Azen SP, Aoki Y, Yamamoto T, Otuka T, Blanc-Bisson C, Bourdel-Marchasson I, Bocock MA, Keller HH, Bowman G, Baxter J, Oken B, Frei B, Traber M, Leonard S, Kaye J, Shannon J, Quinn J, Carlsson M, Gustafson Y, Eriksson S, Littbrand H, Håglin L, Danthiir V, Wilson C, Nettelbeck T, Burns N, Wittert G, Noakes M, Clifton P, DiMaria-Ghalili RA, Grieger JA, Nowson CA, Wattanapenpaiboon NT, Holstein J, Robinson C, Hartmann C, Rueb S, Heffel L, Dintaman S, Reynolds J, Fleming L, Crull M, Goldey J, Serper LL, Hubbard R, Westengard J, Horning M, Ishige Y, Aoki Y, Keller HH, Keller HH, LaStayo PC, Marcus RL, Smith S, Kidde J, Dibble L, Butler C, Hill M, LaStayo PC, Marcus RL, Dibble L, Kidde J, Peters C, Meier W, Laughlin GA, Kritz-Silverstein D, von Muhlen D, Barrett-Connor E, Olariu L, Petcu M, Tulcan C, Pup M, Otilingam P, Gate M, Pasinetti GM, Ray B, Chauhan NB, Bailey JA, Lahiri DK, Shatenstein B, Kergoat MJ, Reid I, Chicoine ME, Vaz L, Stewart R, Sabbah W, Tsakos G, D’Aiuto F, Watt RG, Sturman M, Kelly J, Fleischman D, Leurgans S, Bennett D, Morris MC, Suominen MH, Muurinen S, Soini H, Pitkälä KH, Yamamoto T, Fujinoki C, Aoki Y. 3rd IANA (International Academy on Nutrition and Aging) Meeting Nutrition, Exercise & Alzheimer and Clinical Trials on Sarcopenia August 1–2, 2008 Hyatt Regency Tamaya Resort 1300 Tuyuna Trail Santa Ana Pueblo, NM USA. J Nutr Health Aging 2008. [DOI: 10.1007/bf02982702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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