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Archives of Pathology & Laboratory... Mar 2020Histopathologic diagnosis of adenocarcinoma of the prostate is based on light-microscopic examination of hematoxylin-eosin-stained tissue sections. Multiple factors,... (Review)
Review
CONTEXT.—
Histopathologic diagnosis of adenocarcinoma of the prostate is based on light-microscopic examination of hematoxylin-eosin-stained tissue sections. Multiple factors, including preanalytic and analytic elements, affect the ability of the pathologist to accurately diagnose prostatic adenocarcinoma. False-negative diagnosis, that is, failure to diagnose prostatic adenocarcinoma, may have serious clinical consequences. It is important to delineate and understand those factors that may affect and cause histopathologic false-negative diagnoses of prostatic adenocarcinoma.
OBJECTIVES.—
To review common factors involved in histopathologic underdiagnosis of prostatic adenocarcinoma, including the following: (1) tissue processing and sectioning artifacts, (2) minimal adenocarcinoma, (3) deceptively benign appearing variants of acinar adenocarcinoma, (4) single cell adenocarcinoma, and (5) treatment effects.
DATA SOURCES.—
Data sources included published, peer-reviewed literature and personal experiences of the senior author.
CONCLUSIONS.—
Knowledge of the reasons for histopathologic false-negative diagnosis of adenocarcinoma of the prostate is an important component in the diagnostic assessment of prostate tissue sections. Diagnostic awareness of the histomorphologic presentations of small (minimal) adenocarcinoma; deceptively benign appearing variants including atrophic, foamy gland, microcystic, and pseudohyperplastic variants; single cell carcinoma; and treatment effects is critical for establishment of a definitive diagnosis of adenocarcinoma and the prevention of false-negative diagnoses of prostate cancer.
Topics: Adenocarcinoma; Biomarkers, Tumor; Cytodiagnosis; Diagnosis, Differential; False Negative Reactions; Humans; Male; Pancreatic Cyst; Prostatic Neoplasms; Sensitivity and Specificity
PubMed: 31729886
DOI: 10.5858/arpa.2019-0456-RA -
Pathobiology : Journal of... 2022Endoscopic ultrasound-guided ablation (EUS-A) therapy is a minimally invasive procedure for pancreatic-cystic tumors in patients with preoperative comorbidities or in...
BACKGROUND
Endoscopic ultrasound-guided ablation (EUS-A) therapy is a minimally invasive procedure for pancreatic-cystic tumors in patients with preoperative comorbidities or in patients who are not indicated for surgical resection. However, histopathologic characteristics of pancreatic cysts after ablation have not been well-elucidated.
METHODS
Here, we analyzed pathological findings of 12 surgically resected pancreatic cysts after EUS-A with ethanol and/or paclitaxel injection.
RESULTS
Mean patient age was 49.8 ± 13.6 years with a 0.3 male/female ratio. Clinical impression before EUS-A was predominantly mucinous cystic neoplasms. Mean cyst size before and after ablation therapy was similar (3.7 ± 1.0 cm vs. 3.4 ± 1.6 cm; p = 0.139). Median duration from EUS-A to surgical resection was 18 (range, 1-59) months. Mean percentage of the residual neoplastic lining epithelial cells were 23.1 ± 37.0%. Of the resected cysts, 8 cases (67%) showed no/minimal (<5%) residual lining epithelia, while the remaining 4 cases (33%) showed a wide range of residual mucinous epithelia (20-90%). Ovarian-type stroma was noted in 5 cases (42%). Other histologic features included histiocytic aggregation (67%), stromal hyalinization (67%), diffuse egg shell-like calcification along the cystic wall (58%), and fat necrosis (8%).
CONCLUSION
Above all, diffuse egg shell-like calcification along the pancreatic cystic walls with residual lining epithelia and/or ovarian-type stroma were characteristics of pancreatic cysts after EUS-A. Therefore, understanding these histologic features will be helpful for precise pathological diagnosis of pancreatic cystic tumor after EUS-A, even without knowing the patient's history of EUS-A.
Topics: Adult; Endosonography; Ethanol; Female; Humans; Male; Middle Aged; Paclitaxel; Pancreatic Cyst; Pancreatic Neoplasms; Pancreatic Pseudocyst
PubMed: 34515187
DOI: 10.1159/000518050 -
Signal Transduction and Targeted Therapy Oct 2023Pancreatic cystic neoplasms (PCNs) are recognized as precursor lesions of pancreatic cancer, with a marked increase in prevalence. Early detection of malignant PCNs is...
Pancreatic cystic neoplasms (PCNs) are recognized as precursor lesions of pancreatic cancer, with a marked increase in prevalence. Early detection of malignant PCNs is crucial for improving prognosis; however, current diagnostic methods are insufficient for accurately identifying malignant PCNs. Here, we utilized mass spectrometry (MS)-based glycosite- and glycoform-specific glycoproteomics, combined with proteomics, to explore potential cyst fluid diagnostic biomarkers for PCN. The glycoproteomic and proteomic landscape of pancreatic cyst fluid samples from PCN patients was comprehensively investigated, and its characteristics during the malignant transformation of PCN were analyzed. Under the criteria of screening specific cyst fluid biomarkers for the diagnosis of PCN, a group of cyst fluid glycoprotein biomarkers was identified. Through parallel reaction monitoring (PRM)-based targeted glycoproteomic analysis, we validated these chosen glycoprotein biomarkers in a second cohort, ultimately confirming N-glycosylated PHKB (Asn-935, H5N2F0S0; Asn-935, H4N4F0S0; Asn-935, H5N4F0S0), CEACAM5 (Asn-197, H5N4F0S0) and ATP6V0A4 (Asn-367, H6N4F0S0) as promising diagnostic biomarkers for distinguishing malignant PCNs. These glycoprotein biomarkers exhibited robust performance, with an area under the curve ranging from 0.771 to 0.948. In conclusion, we successfully established and conducted MS-based glycoproteomic analysis to identify novel cyst fluid glycoprotein biomarkers for PCN. These findings hold significant clinical implications, providing valuable insights for PCN decision-making, and potentially offering therapeutic targets for PCN treatment.
Topics: Humans; Pancreatic Cyst; Cyst Fluid; Proteomics; Pancreatic Neoplasms; Glycoproteins; Neoplasms, Cystic, Mucinous, and Serous
PubMed: 37848412
DOI: 10.1038/s41392-023-01645-8 -
ANZ Journal of Surgery Nov 2020Cystic lesions of the pancreas (PCLs) may be inflammatory or proliferative and making an accurate and timely pre-operative diagnosis remains a significant clinical... (Review)
Review
BACKGROUND
Cystic lesions of the pancreas (PCLs) may be inflammatory or proliferative and making an accurate and timely pre-operative diagnosis remains a significant clinical challenge. This is principally due to the heterogeneity of the pathological processes involved. PCLs constitute an entity with diverse histology and although infrequent, the possible potential for malignant transformation of these lesions and the opportunity for curative surgery mandates that our diagnostic approaches are up to date and evidence based. In addition, improved diagnostic accuracy is crucial to prevent unnecessary surgical procedures with the inevitable associated morbidity.
METHODS
This narrative review examines the current diagnostic benchmarks and identifies novel diagnostic techniques that warrant further consideration, a number of which are beginning to be included in routine clinical practice when these PCLs are being investigated. A computerized search was made of MEDLINE, EMBASE and PubMed using the search words 'diagnostic approaches to pancreatic cystic lesions'. All relevant articles in English language or with an English abstract were retrieved and additionally cross referenced.
CONCLUSION
The increasing accuracy of available imaging techniques together with the wider availability of endoluminal ultrasound and the development of additional novel methods to assess PCLs presents an opportunity to significantly improve the pre-operative diagnosis rate. This is essential to classify the type of PCL and hence guide the management particularly with lesions where there is a likelihood of progression to more serious pathology. We have highlighted the need for a comprehensive and standardized algorithm for the diagnosis and management of PCLs.
Topics: Endoscopic Ultrasound-Guided Fine Needle Aspiration; Humans; Morbidity; Pancreas; Pancreatic Cyst; Pancreatic Neoplasms
PubMed: 32815222
DOI: 10.1111/ans.16251 -
Gastrointestinal Endoscopy Oct 2020
Topics: Biopsy, Needle; Humans; Pancreatic Cyst; Pathologists
PubMed: 32964846
DOI: 10.1016/j.gie.2020.06.020 -
Hepatobiliary & Pancreatic Diseases... Jun 2023Pancreatic cysts are common. However, most studies are based on data collected from individual centers. The present study aimed to evaluate the changes of management...
BACKGROUND
Pancreatic cysts are common. However, most studies are based on data collected from individual centers. The present study aimed to evaluate the changes of management patterns for pancreatic cystic lesions (PCLs) by analyzing large epidemiologic data.
METHODS
Between January 2007 and December 2018, information regarding pancreatic cystic lesions was acquired from the nationwide Health Insurance Review and Assessment Service database in Korea.
RESULTS
The final number of patients with pancreatic cysts was 165 277 among the total claims for reimbursement of 855 983 associated with PCLs over 12 years. The total number of claims were increased from 19 453 in 2007 to 155 842 in 2018 and the prevalence increased from 0.04% to 0.23%. For 12 years, 2874 (1.7%) had pancreatic cancer and 8212 (5.0%) underwent surgery, and 36 had surgery for twice (total 8248 pancreatectomy). After ruling out claims from the first 3 years of washout period, the incidence increased from 9891 to 24 651 and the crude incidence rate of PCLs expanded from 19.96 per 100 000 to 47.77 per 100 000. Compared to specific neoplasm codes (D136 or D377), the use of pancreatic cyst code (K862) has been remarkably increased and the most common since 2010. The annual number of pancreatectomies increased from 518 to 861 between 2007 and 2012, and decreased to 596 until 2018. The percentage of pancreatic cancer in patients who received pancreatectomy increased from 5.6% in 2007 to 11.7% in 2018.
CONCLUSIONS
The incidence of PCLs is rapidly increasing. Among PCLs, indeterminate cyst is increasing outstandingly. A trend of decreasing in the number of resections and increasing cancer rates among resected cysts may be attributed to the updated international guidelines.
Topics: Humans; Incidence; Retrospective Studies; Pancreatic Cyst; Pancreatic Neoplasms
PubMed: 35715339
DOI: 10.1016/j.hbpd.2022.06.002 -
PloS One 2023Although main pancreatic duct dilatation and pancreatic cysts are risk factors for developing pancreatic cancer, limited data exist regarding these findings in relatives...
Although main pancreatic duct dilatation and pancreatic cysts are risk factors for developing pancreatic cancer, limited data exist regarding these findings in relatives and spouses of pancreatic cancer patients. The frequency of these findings was examined using long-term follow-up data and transabdominal ultrasonography focusing on the pancreas. We prospectively enrolled 184 relatives and spouses of pancreatic cancer patients and performed special pancreatic ultrasonography to detect main pancreatic duct dilatation and pancreatic cysts. First-degree relatives (148 participants) of patients with pancreatic cancer were significantly younger than the spouses (36 participants; 41 vs. 65 years old). The frequency of ultrasonographic findings was significantly different between the relative (8.8%) and spouse (33.3%) groups. Main pancreatic duct dilatation and pancreatic cysts were observed in seven (4.7%) and seven (4.7%) participants in the relative group, and in nine (25.0%) and five (13.9%) participants in the spouse group, respectively. On multivariate analysis, age was an independent risk factor for the ultrasonographic findings. The frequency of ultrasonographic findings was significantly higher in spouses than in first-degree relatives of patients with pancreatic cancer and was strongly influenced by the age gap between the groups. Main pancreatic duct dilatation was frequently observed, especially in the spouse group.
Topics: Humans; Aged; Spouses; Dilatation; Pancreatic Ducts; Pancreatic Neoplasms; Pancreatic Cyst; Gastrointestinal Diseases; Dilatation, Pathologic
PubMed: 36630426
DOI: 10.1371/journal.pone.0280403 -
Gastroenterology Mar 2022To successfully implement imaging-based pancreatic cancer (PC) surveillance, understanding the timeline and morphologic features of neoplastic progression is key. We...
BACKGROUND & AIMS
To successfully implement imaging-based pancreatic cancer (PC) surveillance, understanding the timeline and morphologic features of neoplastic progression is key. We aimed to investigate the progression to neoplasia from serial prediagnostic pancreatic imaging tests in high-risk individuals and identify factors associated with successful early detection.
METHODS
We retrospectively examined the development of pancreatic abnormalities in high-risk individuals who were diagnosed with PC or underwent pancreatic surgery, or both, in 16 international surveillance programs.
RESULTS
Of 2552 high-risk individuals under surveillance, 28 (1%) developed neoplastic progression to PC or high-grade dysplasia during a median follow-up of 29 months after baseline (interquartile range [IQR], 40 months). Of these, 13 of 28 (46%) presented with a new lesion (median size, 15 mm; range 7-57 mm), a median of 11 months (IQR, 8; range 3-17 months) after a prior examination, by which time 10 of 13 (77%) had progressed beyond the pancreas. The remaining 15 of 28 (54%) had neoplastic progression in a previously detected lesion (12 originally cystic, 2 indeterminate, 1 solid), and 11 (73%) had PC progressed beyond the pancreas. The 12 patients with cysts had been monitored for 21 months (IQR, 15 months) and had a median growth of 5 mm/y (IQR, 8 mm/y). Successful early detection (as high-grade dysplasia or PC confined to the pancreas) was associated with resection of cystic lesions (vs solid or indeterminate lesions (odds ratio, 5.388; 95% confidence interval, 1.525-19.029) and small lesions (odds ratio, 0.890/mm; 95% confidence interval 0.812-0.976/mm).
CONCLUSIONS
In nearly half of high-risk individuals developing high-grade dysplasia or PC, no prior lesions are detected by imaging, yet they present at an advanced stage. Progression can occur before the next scheduled annual examination. More sensitive diagnostic tools or a different management strategy for rapidly growing cysts are needed.
Topics: Adult; Aged; Aged, 80 and over; Disease Progression; Early Detection of Cancer; Endosonography; Female; Follow-Up Studies; Humans; Magnetic Resonance Imaging; Male; Middle Aged; Neoplasm Metastasis; Pancreas; Pancreatic Cyst; Pancreatic Neoplasms; Precancerous Conditions; Retrospective Studies; Risk Factors; Time Factors; Tomography, X-Ray Computed; Tumor Burden; Watchful Waiting
PubMed: 34678218
DOI: 10.1053/j.gastro.2021.10.014 -
International Journal of Computer... Oct 2022Pancreatic cancer is one of the most lethal neoplasms among common cancers worldwide, and PCLs are well-known precursors of this type of cancer. Artificial intelligence... (Review)
Review
PURPOSE
Pancreatic cancer is one of the most lethal neoplasms among common cancers worldwide, and PCLs are well-known precursors of this type of cancer. Artificial intelligence (AI) could help to improve and speed up the detection and classification of pancreatic lesions. The aim of this review is to summarize the articles addressing the diagnostic yield of artificial intelligence applied to medical imaging (computed tomography [CT] and/or magnetic resonance [MR]) for the detection of pancreatic cancer and pancreatic cystic lesions.
METHODS
We performed a comprehensive literature search using PubMed, EMBASE, and Scopus (from January 2010 to April 2021) to identify full articles evaluating the diagnostic accuracy of AI-based methods processing CT or MR images to detect pancreatic ductal adenocarcinoma (PDAC) or pancreatic cystic lesions (PCLs).
RESULTS
We found 20 studies meeting our inclusion criteria. Most of the AI-based systems used were convolutional neural networks. Ten studies addressed the use of AI to detect PDAC, eight studies aimed to detect and classify PCLs, and 4 aimed to predict the presence of high-grade dysplasia or cancer.
CONCLUSION
AI techniques have shown to be a promising tool which is expected to be helpful for most radiologists' tasks. However, methodologic concerns must be addressed, and prospective clinical studies should be carried out before implementation in clinical practice.
Topics: Artificial Intelligence; Humans; Pancreatic Cyst; Pancreatic Neoplasms; Prospective Studies; Tomography, X-Ray Computed
PubMed: 35951286
DOI: 10.1007/s11548-022-02706-z -
Journal of X-ray Science and Technology 2023Automatic segmentation of the pancreas and its tumor region is a prerequisite for computer-aided diagnosis.
BACKGROUND
Automatic segmentation of the pancreas and its tumor region is a prerequisite for computer-aided diagnosis.
OBJECTIVE
In this study, we focus on the segmentation of pancreatic cysts in abdominal computed tomography (CT) scan, which is challenging and has the clinical auxiliary diagnostic significance due to the variability of location and shape of pancreatic cysts.
METHODS
We propose a convolutional neural network architecture for segmentation of pancreatic cysts, which is called pyramid attention and pooling on convolutional neural network (PAPNet). In PAPNet, we propose a new atrous pyramid attention module to extract high-level features at different scales, and a spatial pyramid pooling module to fuse contextual spatial information, which effectively improves the segmentation performance.
RESULTS
The model was trained and tested using 1,346 CT slice images obtained from 107 patients with the pathologically confirmed pancreatic cancer. The mean dice similarity coefficient (DSC) and mean Jaccard index (JI) achieved using the 5-fold cross-validation method are 84.53% and 75.81%, respectively.
CONCLUSIONS
The experimental results demonstrate that the proposed new method in this study enables to achieve effective results of pancreatic cyst segmentation.
Topics: Humans; Image Processing, Computer-Assisted; Neural Networks, Computer; Pancreatic Cyst; Abdomen; Diagnosis, Computer-Assisted
PubMed: 37038804
DOI: 10.3233/XST-230011