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Article ; Online: Ingestion of heated tobacco sticks containing a micro-blade by children: the importance of performing a radiograph.

Schicchi, Azzurra / Lonati, Davide / Papotto, Anna / Ippolito, Annamaria / Piana, Sebastiano / Grasso, Santo

2024 Volume 62, Issue 2, Page(s) 129–130

Abstract: Introduction: Some tobacco sticks, such as TEREA™ heat sticks for IQOS ILUMA™, contain a blade. Both the nicotine part of the device and the micro-blade can be ingested by children.: Case summaries: We report two children, an 18-month-old boy and a ... ...

Abstract	Introduction: Some tobacco sticks, such as TEREA™ heat sticks for IQOS ILUMA™, contain a blade. Both the nicotine part of the device and the micro-blade can be ingested by children. Case summaries: We report two children, an 18-month-old boy and a 10-month-old girl, who ingested a heat stick containing a micro-blade. Images: Radiography revealed the micro-blade to be in the child's mouth in the first case and the stomach in the second. Endoscopy was performed on the second child, confirming the presence of the blade in the stomach. Conclusion: We recommend performing a radiograph on all children who ingest tobacco sticks containing a micro-blade. If a metallic object is present, we recommend endoscopic removal to avoid traumatic lesions from the sharp edges.
MeSH term(s)	Female ; Humans ; Infant ; Male ; Eating ; Foreign Bodies/diagnostic imaging ; Hot Temperature ; Radiography ; Tobacco Products/adverse effects
Language	English
Publishing date	2024-03-13
Publishing country	England
Document type	Case Reports ; Journal Article
ZDB-ID	204476-6
ISSN	1556-9519 ; 0009-9309 ; 0731-3810 ; 1556-3650
ISSN (online)	1556-9519
ISSN	0009-9309 ; 0731-3810 ; 1556-3650
DOI	10.1080/15563650.2024.2308018
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Article ; Online: Ultrasound muscle assessment for sarcopenia detection in inflammatory bowel disease: A prospective study.

Mulinacci, Giacomo / Pirola, Lorena / Gandola, Davide / Ippolito, Davide / Viganò, Chiara / Laffusa, Alice / Gallo, Camilla / Invernizzi, Pietro / Danese, Silvio / Massironi, Sara

United European gastroenterology journal

2024

Abstract: Background: Sarcopenia is prevalent in patients with inflammatory bowel disease (IBD) and impacts surgical and therapeutic outcomes; thus, effective diagnostic tools are needed to assess muscle mass and function in this population.: Methods: 153 ... ...

Abstract	Background: Sarcopenia is prevalent in patients with inflammatory bowel disease (IBD) and impacts surgical and therapeutic outcomes; thus, effective diagnostic tools are needed to assess muscle mass and function in this population. Methods: 153 consecutive patients were included, 100 in the training cohort and 53 in the study cohort. Three superficial muscles (rectus femoris = RF, rectus abdominis = RA, and biceps brachii = BB) were selected for the detection of sarcopenia using muscle ultrasound (US). The training cohort consisted of consecutive patients with or without IBD and was used to evaluate the feasibility and inter- and intra-observer variability of the US measurement. The study cohort consisted of only IBD patients and served to test US diagnostic accuracy. In the latter, muscle US, bioelectrical impedance analysis (BIA), and magnetic resonance imaging (MRI) were used to measure muscle parameters. Results: Sarcopenia prevalence in IBD patients was 50%. Muscle US showed excellent inter-rater and intra-rater reliability (ICC >0.95) and a good diagnostic accuracy in detecting sarcopenia compared to BIA with area under the receiver operating characteristic curve (AUROC) values of 80% and 85% for RA and BB thickness, respectively. Moreover, an Ultrasound Muscle Index (USMI) was defined as the sum of the RA, BB, and RF thickness divided by the square of the patient's height, resulting in an AUROC of 81%. Muscle thresholds for sarcopenia were detected, with RA and USMI values correlated with the highest positive (84.3%) and negative (99%) predictive values, respectively. Additionally, the agreement between the US and MRI measurements of RA was excellent (ICC 0.96). Conclusions: The findings of this study emphasize the potential of muscle US as a reliable diagnostic tool for assessing sarcopenia in IBD patients. This research has significant implications for disease management in IBD patients and underscores the need for further investigations to validate these findings in larger cohorts.
Language	English
Publishing date	2024-03-28
Publishing country	England
Document type	Journal Article
ZDB-ID	2728585-6
ISSN	2050-6414 ; 2050-6406
ISSN (online)	2050-6414
ISSN	2050-6406
DOI	10.1002/ueg2.12566
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Article ; Online: Does the Relationship of the Autonomic Symptoms Questionnaire COMPASS 31 with Cardiovascular Autonomic Tests Differ between Type 1 and Type 2 Diabetes Mellitus?

D'Ippolito, Ilenia / Menduni, Marika / D'Amato, Cinzia / Andreadi, Aikaterini / Lauro, Davide / Spallone, Vincenza

Diabetes & metabolism journal

2024

Abstract: Background: The aim was to investigate if autonomic symptoms questionnaire Composite Autonomic Symptom Score (COMPASS) 31 has different association with cardiovascular autonomic neuropathy (CAN) and diagnostic performance between type 1 diabetes ... ...

Abstract	Background: The aim was to investigate if autonomic symptoms questionnaire Composite Autonomic Symptom Score (COMPASS) 31 has different association with cardiovascular autonomic neuropathy (CAN) and diagnostic performance between type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Methods: Seventy-nine participants with T1DM and 140 with T2DM completed COMPASS 31 before cardiovascular reflex tests (CARTs) for CAN, and assessment of symptoms, signs, vibration, and thermal perception thresholds for diabetic polyneuropathy (DPN) diagnosis. Results: COMPASS 31 total weighted score (TWS) was similar in the two groups, but significantly associated with confirmed CAN only in T1DM (P=0.0056) and not T2DM group (P=0.1768) and correlated with CARTs score more strongly in T1DM (rho=0.356, P=0.0016) than in T2DM group (rho=0.084, P=0.3218) (P=0.016). Only in T1DM and not T2DM group, the area under the receiver operating characteristic curve (AUC) reached a fair diagnostic accuracy (>0.7) for confirmed CAN (0.73±0.07 vs. 0.61±0.08) and DPN (0.75±0.06 vs. 0.68±0.05), although without a significant difference. COMPASS 31 TWS (cut-off 16.44) reached acceptable diagnostic performance in T1DM, with sensitivity for confirmed CAN 81.2% and sensitivity and specificity for DPN 76.3% and 78%, compared to T2DM group (all <70%). AUC for DPN of orthostatic intolerance domain was higher in T1DM compared to T2DM group (0.73±0.05 vs. 0.58±0.04, P=0.027). Conclusion: COMPASS 31 is more weakly related to CAN in T2DM than in T1DM, with a fair diagnostic accuracy for confirmed CAN only in T1DM. This difference supports a multifactorial origin of symptoms and should be considered when using COMPASS 31.
Language	English
Publishing date	2024-02-26
Publishing country	Korea (South)
Document type	Journal Article
ZDB-ID	2602402-0
ISSN	2233-6087 ; 2233-6087
ISSN (online)	2233-6087
ISSN	2233-6087
DOI	10.4093/dmj.2023.0301
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Article ; Online: The Global Reading Room: Imaging Surveillance for Primary Sclerosing Cholangitis.

Grigoriadis, Aristeidis / Ippolito, Davide / Itani, Malak / Tan, Cher Heng / Venkatesh, Sudhakar K

AJR. American journal of roentgenology

2023 Volume 222, Issue 2, Page(s) e2329661

MeSH term(s)	Humans ; Cholangitis, Sclerosing/diagnostic imaging ; Diagnostic Imaging ; Colorectal Neoplasms
Language	English
Publishing date	2023-05-31
Publishing country	United States
Document type	Journal Article
ZDB-ID	82076-3
ISSN	1546-3141 ; 0361-803X ; 0092-5381
ISSN (online)	1546-3141
ISSN	0361-803X ; 0092-5381
DOI	10.2214/AJR.23.29661
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Article ; Online: Feasibility of Low-Dose and Low-Contrast Media Volume Approach in Computed Tomography Cardiovascular Imaging Reconstructed with Model-Based Algorithm.

Ippolito, Davide / Porta, Marco / Maino, Cesare / Riva, Luca / Ragusi, Maria / Giandola, Teresa / Franco, Paolo Niccolò / Cangiotti, Cecilia / Gandola, Davide / De Vito, Andrea / Talei Franzesi, Cammillo / Corso, Rocco

Tomography (Ann Arbor, Mich.)

2024 Volume 10, Issue 2, Page(s) 286–298

Abstract: ... ...

Abstract	Aim
MeSH term(s)	Humans ; Contrast Media ; Feasibility Studies ; Radiation Dosage ; Tomography, X-Ray Computed/methods ; Algorithms
Chemical Substances	Contrast Media
Language	English
Publishing date	2024-02-16
Publishing country	Switzerland
Document type	Journal Article
ISSN	2379-139X
ISSN (online)	2379-139X
DOI	10.3390/tomography10020023
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Article: Cross-sectional imaging after pancreatic surgery: The dialogue between the radiologist and the surgeon.

Maino, Cesare / Cereda, Marco / Franco, Paolo Niccolò / Boraschi, Piero / Cannella, Roberto / Gianotti, Luca Vittorio / Zamboni, Giulia / Vernuccio, Federica / Ippolito, Davide

European journal of radiology open

2024 Volume 12, Page(s) 100544

Abstract: Pancreatic surgery is nowadays considered one of the most complex surgical approaches and not unscathed from complications. After the surgical procedure, cross-sectional imaging is considered the non-invasive reference standard to detect early and late ... ...

Abstract	Pancreatic surgery is nowadays considered one of the most complex surgical approaches and not unscathed from complications. After the surgical procedure, cross-sectional imaging is considered the non-invasive reference standard to detect early and late compilations, and consequently to address patients to the best management possible. Contras-enhanced computed tomography (CECT) should be considered the most important and useful imaging technique to evaluate the surgical site. Thanks to its speed, contrast, and spatial resolution, it can help reach the final diagnosis with high accuracy. On the other hand, magnetic resonance imaging (MRI) should be considered as a second-line imaging approach, especially for the evaluation of biliary findings and late complications. In both cases, the radiologist should be aware of protocols and what to look at, to create a robust dialogue with the surgeon and outline a fitted treatment for each patient.
Language	English
Publishing date	2024-01-19
Publishing country	England
Document type	Journal Article
ZDB-ID	2810314-2
ISSN	2352-0477
ISSN	2352-0477
DOI	10.1016/j.ejro.2023.100544
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Article: Artificial Intelligence Applied to Chest X-ray: A Reliable Tool to Assess the Differential Diagnosis of Lung Pneumonia in the Emergency Department.

Ippolito, Davide / Maino, Cesare / Gandola, Davide / Franco, Paolo Niccolò / Miron, Radu / Barbu, Vlad / Bologna, Marco / Corso, Rocco / Breaban, Mihaela Elena

Diseases (Basel, Switzerland)

2023 Volume 11, Issue 4

Abstract: Background: Considering the large number of patients with pulmonary symptoms admitted to the emergency department daily, it is essential to diagnose them correctly. It is necessary to quickly solve the differential diagnosis between COVID-19 and typical ...

Abstract	Background: Considering the large number of patients with pulmonary symptoms admitted to the emergency department daily, it is essential to diagnose them correctly. It is necessary to quickly solve the differential diagnosis between COVID-19 and typical bacterial pneumonia to address them with the best management possible. In this setting, an artificial intelligence (AI) system can help radiologists detect pneumonia more quickly. Methods: We aimed to test the diagnostic performance of an AI system in detecting COVID-19 pneumonia and typical bacterial pneumonia in patients who underwent a chest X-ray (CXR) and were admitted to the emergency department. The final dataset was composed of three sub-datasets: the first included all patients positive for COVID-19 pneumonia (n = 1140, namely "COVID-19+"), the second one included all patients with typical bacterial pneumonia (n = 500, "pneumonia+"), and the third one was composed of healthy subjects (n = 1000). Two radiologists were blinded to demographic, clinical, and laboratory data. The developed AI system was used to evaluate all CXRs randomly and was asked to classify them into three classes. Cohen's κ was used for interrater reliability analysis. The AI system's diagnostic accuracy was evaluated using a confusion matrix, and 95%CIs were reported as appropriate. Results: The interrater reliability analysis between the most experienced radiologist and the AI system reported an almost perfect agreement for COVID-19+ (κ = 0.822) and pneumonia+ (κ = 0.913). We found 96% sensitivity (95% CIs = 94.9-96.9) and 79.8% specificity (76.4-82.9) for the radiologist and 94.7% sensitivity (93.4-95.8) and 80.2% specificity (76.9-83.2) for the AI system in the detection of COVID-19+. Moreover, we found 97.9% sensitivity (98-99.3) and 88% specificity (83.5-91.7) for the radiologist and 97.5% sensitivity (96.5-98.3) and 83.9% specificity (79-87.9) for the AI system in the detection of pneumonia+ patients. Finally, the AI system reached an accuracy of 93.8%, with a misclassification rate of 6.2% and weighted-F1 of 93.8% in detecting COVID+, pneumonia+, and healthy subjects. Conclusions: The AI system demonstrated excellent diagnostic performance in identifying COVID-19 and typical bacterial pneumonia in CXRs acquired in the emergency setting.
Language	English
Publishing date	2023-11-20
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2720869-2
ISSN	2079-9721
ISSN	2079-9721
DOI	10.3390/diseases11040171
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Article: Developments in diagnosis and management of post-liver transplantation biliary complications: the radiologist's perspective.

Marra, Paolo / Bonaffini, Pietro Andrea / Ippolito, Davide / Sironi, Sandro

Hepatobiliary surgery and nutrition

2021 Volume 11, Issue 3, Page(s) 457–461

Language	English
Publishing date	2021-01-29
Publishing country	China (Republic : 1949- )
Document type	Editorial ; Comment
ZDB-ID	2812398-0
ISSN	2304-389X ; 2304-3881
ISSN (online)	2304-389X
ISSN	2304-3881
DOI	10.21037/hbsn-22-141
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Article ; Online: Artificial Intelligence Applied to Chest X-ray

Davide Ippolito / Cesare Maino / Davide Gandola / Paolo Niccolò Franco / Radu Miron / Vlad Barbu / Marco Bologna / Rocco Corso / Mihaela Elena Breaban

Diseases, Vol 11, Iss 4, p

A Reliable Tool to Assess the Differential Diagnosis of Lung Pneumonia in the Emergency Department

2023 Volume 171

Abstract	Background: Considering the large number of patients with pulmonary symptoms admitted to the emergency department daily, it is essential to diagnose them correctly. It is necessary to quickly solve the differential diagnosis between COVID-19 and typical bacterial pneumonia to address them with the best management possible. In this setting, an artificial intelligence (AI) system can help radiologists detect pneumonia more quickly. Methods: We aimed to test the diagnostic performance of an AI system in detecting COVID-19 pneumonia and typical bacterial pneumonia in patients who underwent a chest X-ray (CXR) and were admitted to the emergency department. The final dataset was composed of three sub-datasets: the first included all patients positive for COVID-19 pneumonia (n = 1140, namely “COVID-19+”), the second one included all patients with typical bacterial pneumonia (n = 500, “pneumonia+”), and the third one was composed of healthy subjects (n = 1000). Two radiologists were blinded to demographic, clinical, and laboratory data. The developed AI system was used to evaluate all CXRs randomly and was asked to classify them into three classes. Cohen’s κ was used for interrater reliability analysis. The AI system’s diagnostic accuracy was evaluated using a confusion matrix, and 95%CIs were reported as appropriate. Results: The interrater reliability analysis between the most experienced radiologist and the AI system reported an almost perfect agreement for COVID-19+ (κ = 0.822) and pneumonia+ (κ = 0.913). We found 96% sensitivity (95% CIs = 94.9–96.9) and 79.8% specificity (76.4–82.9) for the radiologist and 94.7% sensitivity (93.4–95.8) and 80.2% specificity (76.9–83.2) for the AI system in the detection of COVID-19+. Moreover, we found 97.9% sensitivity (98–99.3) and 88% specificity (83.5–91.7) for the radiologist and 97.5% sensitivity (96.5–98.3) and 83.9% specificity (79–87.9) for the AI system in the detection of pneumonia+ patients. Finally, the AI system reached an accuracy of 93.8%, with a misclassification ...
Keywords	artificial intelligence ; chest X-ray ; SARS-CoV-2 ; COVID-19 ; Medicine ; R
Subject code	610
Language	English
Publishing date	2023-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Cross-sectional imaging after pancreatic surgery

Cesare Maino / Marco Cereda / Paolo Niccolò Franco / Piero Boraschi / Roberto Cannella / Luca Vittorio Gianotti / Giulia Zamboni / Federica Vernuccio / Davide Ippolito

European Journal of Radiology Open, Vol 12, Iss , Pp 100544- (2024)

The dialogue between the radiologist and the surgeon

2024

Abstract	Pancreatic surgery is nowadays considered one of the most complex surgical approaches and not unscathed from complications. After the surgical procedure, cross-sectional imaging is considered the non-invasive reference standard to detect early and late compilations, and consequently to address patients to the best management possible. Contras-enhanced computed tomography (CECT) should be considered the most important and useful imaging technique to evaluate the surgical site. Thanks to its speed, contrast, and spatial resolution, it can help reach the final diagnosis with high accuracy. On the other hand, magnetic resonance imaging (MRI) should be considered as a second-line imaging approach, especially for the evaluation of biliary findings and late complications. In both cases, the radiologist should be aware of protocols and what to look at, to create a robust dialogue with the surgeon and outline a fitted treatment for each patient.
Keywords	Pancreas ; Pancreatectomy ; Pancreaticojejunostomy ; Pancreaticoduodenectomy ; Postoperative complications ; Medical physics. Medical radiology. Nuclear medicine ; R895-920
Subject code	616
Language	English
Publishing date	2024-06-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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