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Gastroenterology Jul 2024
Topics: Humans; Adenoma; Colonoscopy; Colonic Polyps; Colorectal Neoplasms; Image Enhancement; Predictive Value of Tests
PubMed: 38224857
DOI: 10.1053/j.gastro.2024.01.014 -
World Neurosurgery Aug 2023Headache is a common symptom in patients with pituitary adenomas. Research on whether resection of pituitary adenomas via the endoscopic endonasal approach (EEA) affects...
BACKGROUND
Headache is a common symptom in patients with pituitary adenomas. Research on whether resection of pituitary adenomas via the endoscopic endonasal approach (EEA) affects headaches is limited, and the pathophysiology of headaches associated with pituitary adenomas remains unclear. This study aimed to determine if resection of pituitary adenomas via the EEA improves headaches and investigate factors that may be associated with headaches in patients with pituitary adenoma.
METHODS
A prospectively collected database of 122 patients undergoing resection of pituitary adenoma via the EEA was analyzed. Patient-reported headache severity was collected prospectively using the Headache Impact Test (HIT-6) at preoperative baseline and 4 postoperative time points (3 weeks, 6 weeks, 3 months, and 6 months).
RESULTS
Adenoma size and subtype, cavernous sinus invasion, and hormonal status were not associated with preoperative headache burden. In patients with preoperative headaches (HIT-6 score >36), significant decreases in HIT-6 score were observed postoperatively at 6 weeks (5.5-point improvement, 95% CI 1.27-9.78, P < 0.01), 3 months (3.6-point improvement, 95% CI 0.01-7.18, P < 0.05), and 6 months (7.5-point improvement, 95% CI 3.43-11.46, P < 0.01). The only factor associated with headache improvement was cavernous sinus invasion (P = 0.003). Adenoma size and subtype and hormonal status were not associated with postoperative headache burden.
CONCLUSIONS
Resection via the EEA is associated with significant improvement in headache-related impact on patient functioning from ≥6 weeks after surgery. Patients with cavernous sinus invasion are more likely to experience improvement in headaches. The mechanism of headaches associated with pituitary adenoma still requires clarification.
Topics: Humans; Pituitary Neoplasms; Adenoma; Endoscopy; Headache; Nose; Treatment Outcome; Retrospective Studies
PubMed: 37277024
DOI: 10.1016/j.wneu.2023.05.082 -
Modern Pathology : An Official Journal... Nov 2023Deep learning systems (DLSs) have been developed for the histopathological assessment of various types of tumors, but none are suitable for differential diagnosis...
Deep learning systems (DLSs) have been developed for the histopathological assessment of various types of tumors, but none are suitable for differential diagnosis between follicular thyroid carcinoma (FTC) and follicular adenoma (FA). Furthermore, whether DLSs can identify the malignant characteristics of thyroid tumors based only on random views of tumor tissue histology has not been evaluated. In this study, we developed DLSs able to differentiate between FTC and FA based on 3 types of convolutional neural network architecture: EfficientNet, VGG16, and ResNet50. The performance of all 3 DLSs was excellent (area under the receiver operating characteristic curve = 0.91 ± 0.04; F1 score = 0.82 ± 0.06). Visual explanations using gradient-weighted class activation mapping suggested that the diagnosis of both FTC and FA was largely dependent on nuclear features. The DLSs were then trained with FTC images and linked information (presence or absence of recurrence within 10 years, vascular invasion, and wide capsular invasion). The ability of the DLSs to diagnose these characteristics was then determined. The results showed that, based on the random views of histology, the DLSs could predict the risk of FTC recurrence, vascular invasion, and wide capsular invasion with a certain level of accuracy (area under the receiver operating characteristic curve = 0.67 ± 0.13, 0.62 ± 0.11, and 0.65 ± 0.09, respectively). Further improvement of our DLSs could lead to the establishment of automated differential diagnosis systems requiring only biopsy specimens.
Topics: Humans; Diagnosis, Differential; Deep Learning; Thyroid Neoplasms; Adenocarcinoma, Follicular; Adenoma
PubMed: 37532181
DOI: 10.1016/j.modpat.2023.100296 -
The Veterinary Record Aug 2023The contrast-enhanced ultrasound (CEUS) features of adrenal lesions are poorly reported in veterinary literature.
BACKGROUND
The contrast-enhanced ultrasound (CEUS) features of adrenal lesions are poorly reported in veterinary literature.
METHODS
Qualitative and quantitative B-mode ultrasound and CEUS features of 186 benign (adenoma) and malignant (adenocarcinoma and pheochromocytoma) adrenal lesions were evaluated.
RESULTS
Adenocarcinomas (n = 72) and pheochromocytomas (n = 32) had mixed echogenicity with B-mode, and a non-homogeneous aspect with a diffused or peripheral enhancement pattern, hypoperfused areas, intralesional microcirculation and non-homogeneous wash-out with CEUS. Adenomas (n = 82) had mixed echogenicity, isoechogenicity or hypoechogenicity with B-mode, and a homogeneous or non-homogeneous aspect with a diffused enhancement pattern, hypoperfused areas, intralesional microcirculation and homogeneous wash-out with CEUS. With CEUS, a non-homogeneous aspect and the presence of hypoperfused areas and intralesional microcirculation can be used to distinguish between malignant (adenocarcinoma and pheochromocytoma) and benign (adenoma) adrenal lesions.
LIMITATIONS
Lesions were characterised only by means of cytology.
CONCLUSIONS
CEUS examination is a valuable tool for distinction between benign and malignant adrenal lesions and can potentially differentiate pheochromocytomas from adenocarcinomas and adenomas. However, cytology and histology are necessary to obtain the final diagnosis.
Topics: Dogs; Animals; Pheochromocytoma; Contrast Media; Adrenal Gland Neoplasms; Adenoma; Adenocarcinoma; Ultrasonography; Diagnosis, Differential; Dog Diseases
PubMed: 37138528
DOI: 10.1002/vetr.2949 -
Medical Decision Making : An... Aug 2023Machine learning (ML)-based emulators improve the calibration of decision-analytical models, but their performance in complex microsimulation models is yet to be...
OBJECTIVES
Machine learning (ML)-based emulators improve the calibration of decision-analytical models, but their performance in complex microsimulation models is yet to be determined.
METHODS
We demonstrated the use of an ML-based emulator with the Colorectal Cancer (CRC)-Adenoma Incidence and Mortality (CRC-AIM) model, which includes 23 unknown natural history input parameters to replicate the CRC epidemiology in the United States. We first generated 15,000 input combinations and ran the CRC-AIM model to evaluate CRC incidence, adenoma size distribution, and the percentage of small adenoma detected by colonoscopy. We then used this data set to train several ML algorithms, including deep neural network (DNN), random forest, and several gradient boosting variants (i.e., XGBoost, LightGBM, CatBoost) and compared their performance. We evaluated 10 million potential input combinations using the selected emulator and examined input combinations that best estimated observed calibration targets. Furthermore, we cross-validated outcomes generated by the CRC-AIM model with those made by CISNET models. The calibrated CRC-AIM model was externally validated using the United Kingdom Flexible Sigmoidoscopy Screening Trial (UKFSST).
RESULTS
The DNN with proper preprocessing outperformed other tested ML algorithms and successfully predicted all 8 outcomes for different input combinations. It took 473 s for the trained DNN to predict outcomes for 10 million inputs, which would have required 190 CPU-years without our DNN. The overall calibration process took 104 CPU-days, which included building the data set, training, selecting, and hyperparameter tuning of the ML algorithms. While 7 input combinations had acceptable fit to the targets, a combination that best fits all outcomes was selected as the best vector. Almost all of the predictions made by the best vector laid within those from the CISNET models, demonstrating CRC-AIM's cross-model validity. Similarly, CRC-AIM accurately predicted the hazard ratios of CRC incidence and mortality as reported by UKFSST, demonstrating its external validity. Examination of the impact of calibration targets suggested that the selection of the calibration target had a substantial impact on model outcomes in terms of life-year gains with screening.
CONCLUSIONS
Emulators such as a DNN that is meticulously selected and trained can substantially reduce the computational burden of calibrating complex microsimulation models.
HIGHLIGHTS
Calibrating a microsimulation model, a process to find unobservable parameters so that the model fits observed data, is computationally complex.We used a deep neural network model, a popular machine learning algorithm, to calibrate the Colorectal Cancer Adenoma Incidence and Mortality (CRC-AIM) model.We demonstrated that our approach provides an efficient and accurate method to significantly speed up calibration in microsimulation models.The calibration process successfully provided cross-model validation of CRC-AIM against 3 established CISNET models and also externally validated against a randomized controlled trial.
Topics: Humans; Incidence; Calibration; Colorectal Neoplasms; Neural Networks, Computer; Adenoma
PubMed: 37434445
DOI: 10.1177/0272989X231184175 -
Frontiers in Endocrinology 2024Prolactinomas (PRLomas) constitute approximately half of all pituitary adenomas and approximately one-fifth of them are diagnosed in males. The clinical presentation of... (Review)
Review
Prolactinomas (PRLomas) constitute approximately half of all pituitary adenomas and approximately one-fifth of them are diagnosed in males. The clinical presentation of PRLomas results from direct prolactin (PRL) action, duration and severity of hyperprolactinemia, and tumor mass effect. Male PRLomas, compared to females, tend to be larger and more invasive, are associated with higher PRL concentration at diagnosis, present higher proliferative potential, are more frequently resistant to standard pharmacotherapy, and thus may require multimodal approach, including surgical resection, radiotherapy, and alternative medical agents. Therefore, the management of PRLomas in men is challenging in many cases. Additionally, hyperprolactinemia is associated with a significant negative impact on men's health, including sexual function and fertility potential, bone health, cardiovascular and metabolic complications, leading to decreased quality of life. In this review, we highlight the differences in pathogenesis, clinical presentation and treatment of PRLomas concerning the male sex.
Topics: Female; Male; Humans; Prolactinoma; Hyperprolactinemia; Quality of Life; Pituitary Neoplasms; Adenoma
PubMed: 38370355
DOI: 10.3389/fendo.2024.1338345 -
BMJ Open Gastroenterology Jan 2024Colorectal cancer (CRC) has a significant role in cancer-related mortality. Colonoscopy, combined with adenoma removal, has proven effective in reducing CRC incidence.... (Randomized Controlled Trial)
Randomized Controlled Trial
OBJECTIVE
Colorectal cancer (CRC) has a significant role in cancer-related mortality. Colonoscopy, combined with adenoma removal, has proven effective in reducing CRC incidence. However, suboptimal colonoscopy quality often leads to missed polyps. The impact of artificial intelligence (AI) on adenoma and polyp detection rate (ADR, PDR) is yet to be established.
DESIGN
We conducted a randomised controlled trial at Sahlgrenska University Hospital in Sweden. Patients underwent colonoscopy with or without the assistance of AI (AI-C or conventional colonoscopy (CC)). Examinations were performed with two different AI systems, that is, Fujifilm CADEye and Medtronic GI Genius. The primary outcome was ADR.
RESULTS
Among 286 patients, 240 underwent analysis (average age: 66 years). The ADR was 42% for all patients, and no significant difference emerged between AI-C and CC groups (41% vs 43%). The overall PDR was 61%, with a trend towards higher PDR in the AI-C group. Subgroup analysis revealed higher detection rates for sessile serrated lesions (SSL) with AI assistance (AI-C 22%, CC 11%, p=0.004). No difference was noticed in the detection of polyps or adenomas per colonoscopy. Examinations were most often performed by experienced endoscopists, 78% (n=86 AI-C, 100 CC).
CONCLUSION
Amidst the ongoing AI integration, ADR did not improve with AI. Particularly noteworthy is the enhanced detection rates for SSL by AI assistance, especially since they pose a risk for postcolonoscopy CRC. The integration of AI into standard colonoscopy practice warrants further investigation and the development of improved software might be necessary before enforcing its mandatory implementation.
TRIAL REGISTRATION NUMBER
NCT05178095.
Topics: Humans; Aged; Artificial Intelligence; Prospective Studies; Early Detection of Cancer; Colonoscopy; Adenoma
PubMed: 38290758
DOI: 10.1136/bmjgast-2023-001247 -
The Lancet. Oncology Mar 2024The faecal immunochemical test (FIT) is widely employed for colorectal cancer screening. However, its sensitivity for advanced precursor lesions remains suboptimal. The...
BACKGROUND
The faecal immunochemical test (FIT) is widely employed for colorectal cancer screening. However, its sensitivity for advanced precursor lesions remains suboptimal. The multitarget FIT (mtFIT), measuring haemoglobin, calprotectin, and serpin family F member 2, has demonstrated enhanced sensitivity for advanced neoplasia, especially advanced adenomas, at equal specificity to FIT. This study aimed to prospectively validate and investigate the clinical utlitity of mtFIT versus FIT in a setting of population-based colorectal cancer screening.
METHODS
Individuals aged 55-75 years and who were eligible for the Dutch national FIT-based colorectal cancer screening programme were invited to submit both a FIT and mtFIT sample collected from the same bowel movement. Positive FIT (47 μg/g haemoglobin cutoff) or mtFIT (based on decision-tree algorithm) led to a colonoscopy referral. The primary outcome was the relative detection rate of mtFIT versus FIT for all advanced neoplasia. Secondary outcomes were the relative detection rates of colorectal cancer, advanced adenoma, and advanced serrated polyps individually and the long-term effect of mtFIT-based versus FIT-based programmatic screening on colorectal cancer incidence, mortality, and cost, determined with microsimulation modelling. The study has been registered in ClinicalTrials.gov, NCT05314309, and is complete.
FINDINGS
Between March 25 and Dec 7, 2022, 35 786 individuals were invited to participate in the study, of whom 15 283 (42·7%) consented, and 13 187 (86·3%) of 15 283 provided both mtFIT and FIT samples with valid results. Of the 13 187 participants, 6637 (50·3%) were male and 6550 (49·7%) were female. mtFIT showed a 9·11% (95% CI 8·62-9·61) positivity rate and 2·27% (95% CI 2·02-2·54) detection rate for advanced neoplasia, compared with a positivity rate of 4·08% (3·75-4·43) and a detection rate of 1·21% (1·03-1·41) for FIT. Detection rates of mtFIT versus FIT were 0·20% (95% CI 0·13-0·29) versus 0·17% (0·11-0·27) for colorectal cancer; 1·64% (1·43-1·87) versus 0·86% (0·72-1·04) for advanced adenoma, and 0·43% (0·33-0·56) versus 0·17% (0·11-0·26) for advanced serrated polyps. Modelling demonstrated that mtFIT-based screening could reduce colorectal cancer incidence by 21% and associated mortality by 18% compared with the current Dutch colorectal cancer screening programme, at feasible costs. Furthermore, at equal positivity rates, mtFIT outperformed FIT in terms of diagnostic yield. At an equally low positivity rate, mtFIT-based screening was predicted to further decrease colorectal cancer incidence by 5% and associated mortality by 4% compared with FIT-based screening.
INTERPRETATION
The higher detection rate of mtFIT for advanced adenoma compared with FIT holds the potential to translate into additional and clinically meaningful long-term colorectal cancer incidence and associated mortality reductions in programmatic colorectal cancer screening.
FUNDING
Stand Up to Cancer, Dutch Cancer Society, Dutch Digestive Foundation, and Health~Holland.
Topics: Humans; Early Detection of Cancer; Defecation; Colorectal Neoplasms; Adenoma; Hemoglobins
PubMed: 38346438
DOI: 10.1016/S1470-2045(23)00651-4 -
Population Health Management Aug 2023The Centers for Medicare & Medicaid Services (CMS) recommend covering blood-based tests meeting proposed minimum performance thresholds for colorectal cancer (CRC)...
The Centers for Medicare & Medicaid Services (CMS) recommend covering blood-based tests meeting proposed minimum performance thresholds for colorectal cancer (CRC) screening. Outcomes were compared between currently available stool-based screening tests and a hypothetical blood-based test meeting CMS minimum thresholds. Using the Colorectal Cancer and Adenoma Incidence and Mortality Microsimulation Model (CRC-AIM), outcomes were simulated for average-risk individuals screened between ages 45 and 75 years with triennial multitarget stool DNA (mt-sDNA), annual fecal immunochemical test (FIT), and annual fecal occult blood test (FOBT). Per CMS guidance, blood-based CRC screening was modeled triennially, with 74% CRC sensitivity and 90% specificity. Although not specified by CMS, adenoma sensitivity was set between 10% and 20%. Published adenoma and CRC sensitivity and specificity were used for stool-based tests. Adherence was set at (1) 100%, (2) 30%-70%, in 10% increments, and (3) real-world rates for stool-based tests (mt-sDNA = 65.6%; FIT = 42.6%; FOBT = 34.4%). Assuming perfect adherence, a blood-based test produced ≥19 lower life-years gained (LYG) than stool-based strategies. At the best-case scenario for blood-based tests (100% adherence and 20% adenoma sensitivity), mt-sDNA at real-world adherence achieved more LYG (287.2 vs. 297.1, respectively) with 14% fewer colonoscopies. At 100% blood-based test adherence and real-world mt-sDNA and FIT adherence, the blood-based test would require advanced adenoma sensitivity of 30% to reach the LYG of mt-sDNA (297.1) and ∼15% sensitivity to reach the LYG of FIT (258.9). This model suggests that blood-based tests with CMS minimally acceptable CRC sensitivity and low advanced adenoma sensitivity will frequently yield inferior outcomes to stool-based testing across a wide range of adherence assumptions.
Topics: Aged; Humans; United States; Early Detection of Cancer; Medicare; Sensitivity and Specificity; Mass Screening; Colorectal Neoplasms; Adenoma
PubMed: 37466476
DOI: 10.1089/pop.2023.0037 -
Cancer Epidemiology, Biomarkers &... Aug 2023To systematically appraise and synthesize available epidemiologic evidence on the associations of environmental and genetic factors with the risk of sporadic early-onset... (Meta-Analysis)
Meta-Analysis
BACKGROUND
To systematically appraise and synthesize available epidemiologic evidence on the associations of environmental and genetic factors with the risk of sporadic early-onset colorectal cancer (EOCRC) and early-onset advanced colorectal adenoma (EOCRA).
METHODS
Multiple databases were comprehensively searched to identify eligible observational studies. Genotype data from UK Biobank were incorporated to examine their associations with EOCRC in a nested case-control design. Meta-analyses of environmental risk factors were performed, and the strength of evidence was graded based on predefined criteria. Meta-analyses of genetic associations were conducted using the allelic, recessive, and dominant models, respectively.
RESULTS
A total of 61 studies were included, reporting 120 environmental factors and 62 genetic variants. We found 12 risk factors (current overweight, overweight in adolescence, high waist circumference, smoking, alcohol, sugary beverages intake, sedentary behavior, red meat intake, family history of colorectal cancer, hypertension, hyperlipidemia, and metabolic syndrome) and three protective factors (vitamin D, folate, and calcium intake) for EOCRC or EOCRA. No significant associations between the examined genetic variants and EOCRC risk were observed.
CONCLUSIONS
Recent data indicate that the changing patterns of traditional colorectal cancer risk factors may explain the rising incidence of EOCRC. However, research on novel risk factors for EOCRC is limited; therefore, we cannot rule out the possibility of EOCRC having different risk factors than late-onset colorectal cancer (LOCRC).
IMPACT
The potential for the identified risk factors to enhance the identification of at-risk groups for personalized EOCRC screening and prevention and for the prediction of EOCRC risk should be comprehensively addressed by future studies.
Topics: Adolescent; Humans; Adenoma; Colorectal Neoplasms; Overweight; Risk Factors; Smoking; Observational Studies as Topic
PubMed: 37220872
DOI: 10.1158/1055-9965.EPI-22-1316