Most are asymptomatic at diagnosis, frequency increases with age
Symptoms: acute pancreatitis (Wirsung obstructed by the cyst or mucus), pain, obstructive chronic pancreatitis, jaundice
> symptoms, >malignancy risk!
Cross-sectional imaging often reveals unexpected pancreatic cystic lesions, it is a frequent clinical problem, Should we observe or remove it? What's the diagnosis? Is our patient in danger of malignancy?
Don’t miss this @aegastro @my_ueg #EducAEG #UEGambassador twitter thread
Most are asymptomatic at diagnosis, frequency increases with age
Symptoms: acute pancreatitis (Wirsung obstructed by the cyst or mucus), pain, obstructive chronic pancreatitis, jaundice
> symptoms, >malignancy risk!
Mucinous: intraductal papillary mucinous neop. and mucinous cystic neop.
Nonmucinous: serous cystic neoplasm, solid pseudopapillary neoplasm and cystic neuroendocrine tumours
Endoderm- derived columnar epithelium is characteristic for mucinous lesions
👇
Characterized by papillary proliferation+mucus production. It may involve Wirsung (becomes dilated) and/or branch ducts (cysts connected to the ductal system). It may evolve to pancreatic cancer particularly if Wirsung is involved
Intestinal: main duct, head, 40%->coloid/tubular adenoca
Pancreatobiliary: main duct,head, 68%->tubular adenoca
Oncocytic: rare, nodules,50%-> coloid/tubular adenoca
Gastric: most frequent, branch-type, uncinate, 10%->tubular adenoca
https://t.co/CyvfrBGrXZ
Main duct involvement (60% in resected specimens vs 10 to 30% in resected side branch IPMNs), specially>1cm
Contrast-enhanced mural nodules
Size>3-4cm
Symptoms
Pts at risk of PDAC even in other regions of the gland without involvement
👇👇👇
European guidelines 2018 @Gut_BMJ @chiaro_del @MarcBesselink https://t.co/x8waod12xr
Fukuoka 2017 @pancreatology@SalviaRobi https://t.co/PaEYljt5N9
Characterized by mucinous epithelium and ovarian-type stroma, in body/tail
It is described as macrocystic, septated cyst with small number of cavities, it may have eccentric calcifications, no connection to ductal system
95% women, 5-7th decades
https://t.co/x8waod12xr
@chiaro_del @MarcBesselink @Gut_BMJ
70% women, 5-7th decades, NON-MUCINOUS solitary lesion
Classic SCN is microcystic (multiple small cysts, honeycomb-like) but can be macrocystic or solid. A central scar or calcification can be present
It is a pancreatic NET with a central cystic changes. Solitary lesion, 5-6th decades, frequently with wall contrast enhancement, 10% malignant potential
It seems that these cystic NET are less aggressive than solid NET
They have malignant potential(15%), >risk if >5 cm
Young women=90% (2-3rd decades),body/tail.Solid and cystic solitary masses, calcifications,often with intracystic bleeding.They can spread to the peritoneum or distant organs like the liver
https://t.co/dAuGI0qzLK
https://t.co/x8waod12xr
https://t.co/Ywp7zQF2wE
And Pancreatic cystic neoplasms, several articles from @UpToDate Editors: JR Saltzman S Grover Authors: Asif Khalid, MDKevin McGrath, MD https://t.co/nYN3MKTnl8
More from Health
You gotta think about this one carefully!
Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)
The test is 99% effective in detecting both sick and healthy people.
Your test comes back positive.
Are you really sick? Explain below 👇
The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through
You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.
👇
Here is what we know:
- Out of 10,000 people, 1 is sick
- Out of 100 sick people, 99 test positive
- Out of 100 healthy people, 99 test negative
Assuming 1 million people take the test (including you):
- 100 of them are sick
- 999,900 of them are healthy
👇
Let's now test both groups, starting with the 100 people sick:
▫️ 99 of them will be diagnosed (correctly) as sick (99%)
▫️ 1 of them is going to be diagnosed (incorrectly) as healthy (1%)
👇
Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)
The test is 99% effective in detecting both sick and healthy people.
Your test comes back positive.
Are you really sick? Explain below 👇
The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through
Really doesn\u2019t fit well in a tweet. pic.twitter.com/xN0pAyniFS
— Dr. Lena Sugar \U0001f3f3\ufe0f\u200d\U0001f308\U0001f1ea\U0001f1fa\U0001f1ef\U0001f1f5 (@_jvs) February 18, 2021
You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.
👇
Here is what we know:
- Out of 10,000 people, 1 is sick
- Out of 100 sick people, 99 test positive
- Out of 100 healthy people, 99 test negative
Assuming 1 million people take the test (including you):
- 100 of them are sick
- 999,900 of them are healthy
👇
Let's now test both groups, starting with the 100 people sick:
▫️ 99 of them will be diagnosed (correctly) as sick (99%)
▫️ 1 of them is going to be diagnosed (incorrectly) as healthy (1%)
👇
