1
|
Meij BP, van Stee LL. Transsphenoidal Surgery for Pituitary Tumors. Vet Clin North Am Small Anim Pract 2025; 55:95-118. [PMID: 39227253 DOI: 10.1016/j.cvsm.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Transsphenoidal surgery for the treatment of pituitary masses in cats and dogs has become a more established treatment over the last 2 decades. Although expert centers and surgeons that provide this service remain limited, the patient population presented for pituitary surgery increases with wider availability of advanced imaging, together with more challenging cases. In this review, the current state of hypophysectomy is described with future challenges and opportunities.
Collapse
Affiliation(s)
- Björn P Meij
- Small Animal Surgery, Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 108, Utrecht 3584CM, The Netherlands
| | - Lucinda L van Stee
- Small Animal Surgery, Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 108, Utrecht 3584CM, The Netherlands.
| |
Collapse
|
2
|
Xie Z, Zhuang Y, Liu J. Clipping aneurysms via a fully endoscopic transcranial approach. Sci Rep 2024; 14:32134. [PMID: 39738796 DOI: 10.1038/s41598-024-83958-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2024] [Accepted: 12/18/2024] [Indexed: 01/02/2025] Open
Abstract
Here we presented the initial experience of clipping aneurysms using fully endoscopic techniques and aimed to evaluate the safety and feasibility of fully endoscopic techniques for aneurysms. This was a retrospective single-center study in which patients were scheduled to undergo aneurysm clipping using fully endoscopic techniques. We collected patients' records, radiological neuroimaging, aneurysm-related variables and surgical procedures in detail, as well as postoperative outcomes. All patients were followed up for neurological examinations and computed tomography (CT) as well as computed tomography angiography (CTA) regularly after surgery. We reviewed the radiological and clinical data of 7patients who underwent aneurysm clipping via fully endoscopic techniques at our department from Jan. 2022 to Jul. 2024, including 2 middle cerebral artery aneurysms, 3 cerebral anterior communicating artery aneurysms, 1 anterior cerebral aneurysm and 1 ophthalmic aneurysm. No uncontrolled rupture of aneurysm occurred during operation. Postclipping endoscopic inspection as well as postoperative CTA demonstrated complete occlusion of the aneurysm and preservation of parent, branching, and perforating vessels. None postclipping cerebral infarction caused by branch or perforator compromise were observed after clipping. No mortality was recorded. Follow-up ranged from 1 to 10 months. Six patients (71.4%) showed excellent or good recoveries. The remaining patient recorded improved KPS. With the accumulation of experience and technological progress, the fully endoscopic technique could enable safe and effective clipping of an aneurysm, which provided valuable information for decision-making during surgery and shed a new light on aneurysms clipping.
Collapse
Affiliation(s)
- Zhengxing Xie
- Department of Neurosurgery, The Affiliated Hospital of Jiangsu University, Zhenjiang, China.
- Neuro-Endoscope and Mini-Invasive Treatment Center, The Affiliated Hospital of Jiangsu University, Zhenjiang, China.
| | - Yan Zhuang
- Department of Neurosurgery, The Affiliated Hospital of Jiangsu University, Zhenjiang, China
- Neuro-Endoscope and Mini-Invasive Treatment Center, The Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Jieping Liu
- Department of Neurosurgery, The Affiliated Hospital of Jiangsu University, Zhenjiang, China
- Neuro-Endoscope and Mini-Invasive Treatment Center, The Affiliated Hospital of Jiangsu University, Zhenjiang, China
| |
Collapse
|
3
|
Yao Z, Chen H. Everolimus in pituitary tumor: a review of preclinical and clinical evidence. Front Endocrinol (Lausanne) 2024; 15:1456922. [PMID: 39736867 PMCID: PMC11682973 DOI: 10.3389/fendo.2024.1456922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2024] [Accepted: 11/27/2024] [Indexed: 01/01/2025] Open
Abstract
Although pituitary tumors (PTs) are mostly benign, some PTs are characterized by low surgical resection rates, high recurrence rates, and poor response to conventional treatments and profoundly affect patients' quality of life. Everolimus (EVE) is the only FDA-approved mTOR inhibitor, which can be used for oral treatment. It effectively inhibits tumor cell proliferation and angiogenesis. It has been administered for various neuroendocrine tumors of the digestive tract, lungs, and pancreas. EVE not only suppresses the growth and proliferation of APT cells but also enhances their sensitivity to radiotherapy and chemotherapy. This review introduces the role of the PI3K/AKT/mTOR pathway in the development of APTs, comprehensively explores the current status of preclinical and clinical research of EVE in APTs, and discusses the blood-brain barrier permeability and safety of EVE.
Collapse
Affiliation(s)
- Zihong Yao
- The Second Clinical Medical College of Lanzhou University, Lanzhou, Gansu, China
- Department of Endocrinology and Metabolism, Lanzhou University Second Hospital, Lanzhou, Gansu, China
| | - Hui Chen
- Department of Endocrinology and Metabolism, Lanzhou University Second Hospital, Lanzhou, Gansu, China
| |
Collapse
|
4
|
Liang X, Li Z, Xing M, Gao W, Liu P. Surgical effect of the medial wall resection of the cavernous sinus for functional pituitary adenomas. Front Surg 2024; 11:1439909. [PMID: 39713808 PMCID: PMC11659198 DOI: 10.3389/fsurg.2024.1439909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Accepted: 11/25/2024] [Indexed: 12/24/2024] Open
Abstract
Background The surgical treatment of pituitary adenomas (PAs) is aimed at achieving maximal tumor resection, relieving the compression, and correcting the disorders of pituitary hormones. Parasellar dural invasion is a primary factor in the failure of the surgery. By comparing the two operations of tumor excision combined with resection of the medial wall of the cavernous sinus (MW) and simple tumor excision, we further confirmed the clinical effectiveness and safety of the resection technique of the MW. Methods 41 patients with functional pituitary adenoma (FPA) were divided into two groups according to the operation. The experimental group consisted of 20 patients who underwent tumor excision combined with resection of the MW via endonasal transsphenoidal approach and 21 patients who underwent simple pituitary tumor excision as the control group. Both groups were followed up for 12 months and matched for age, sex, BMI, tumor type, Knosp grade, maximum tumor diameter, hypertension, diabetes, and coronary disease. Perioperative-related indicators, biochemical remission rates, tumor recurrence rates, and complications were assessed. Results A total of 21 medial walls were removed in 20 patients, 15 (71%) specimens had pathologically confirmed tumor invasion. Biochemical remission rates and average operative duration in the experimental group were more than in the control group (P < 0.05). The remaining perioperative indicators, complications, and tumor recurrence rates had no statistically significant difference (P > 0.05). Conclusion The technique of the MW removal via endonasal transsphenoidal approach for FPAs is safe and effective, with a high biochemical remission. The average operative duration for MW removal may be longer than that for simple tumor excision.
Collapse
Affiliation(s)
| | | | | | | | - Pengfei Liu
- Department of Neurosurgery, Binzhou Medical University Hospital, Binzhou, Shandong, China
| |
Collapse
|
5
|
Das A, Sidiqi B, Mennillo L, Mao Z, Brudfors M, Xochicale M, Khan DZ, Newall N, Hanrahan JG, Clarkson MJ, Stoyanov D, Marcus HJ, Bano S. Automated surgical skill assessment in endoscopic pituitary surgery using real-time instrument tracking on a high-fidelity bench-top phantom. Healthc Technol Lett 2024; 11:336-344. [PMID: 39720762 PMCID: PMC11665785 DOI: 10.1049/htl2.12101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2024] [Accepted: 11/11/2024] [Indexed: 12/26/2024] Open
Abstract
Improved surgical skill is generally associated with improved patient outcomes, although assessment is subjective, labour intensive, and requires domain-specific expertise. Automated data-driven metrics can alleviate these difficulties, as demonstrated by existing machine learning instrument tracking models. However, these models are tested on limited datasets of laparoscopic surgery, with a focus on isolated tasks and robotic surgery. Here, a new public dataset is introduced: the nasal phase of simulated endoscopic pituitary surgery. Simulated surgery allows for a realistic yet repeatable environment, meaning the insights gained from automated assessment can be used by novice surgeons to hone their skills on the simulator before moving to real surgery. Pituitary Real-time INstrument Tracking Network (PRINTNet) has been created as a baseline model for this automated assessment. Consisting of DeepLabV3 for classification and segmentation, StrongSORT for tracking, and the NVIDIA Holoscan for real-time performance, PRINTNet achieved 71.9% multiple object tracking precision running at 22 frames per second. Using this tracking output, a multilayer perceptron achieved 87% accuracy in predicting surgical skill level (novice or expert), with the 'ratio of total procedure time to instrument visible time' correlated with higher surgical skill. The new publicly available dataset can be found at https://doi.org/10.5522/04/26511049.
Collapse
Affiliation(s)
- Adrito Das
- UCL Hawkes InstituteUniversity College LondonLondonUK
| | - Bilal Sidiqi
- UCL Hawkes InstituteUniversity College LondonLondonUK
| | | | - Zhehua Mao
- UCL Hawkes InstituteUniversity College LondonLondonUK
| | | | - Miguel Xochicale
- UCL Hawkes InstituteUniversity College LondonLondonUK
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Danyal Z. Khan
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of NeurosurgeryNational Hospital for Neurology and NeurosurgeryLondonUK
| | - Nicola Newall
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of NeurosurgeryNational Hospital for Neurology and NeurosurgeryLondonUK
| | - John G. Hanrahan
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of NeurosurgeryNational Hospital for Neurology and NeurosurgeryLondonUK
| | - Matthew J. Clarkson
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | | | - Hani J. Marcus
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of NeurosurgeryNational Hospital for Neurology and NeurosurgeryLondonUK
| | - Sophia Bano
- UCL Hawkes InstituteUniversity College LondonLondonUK
| |
Collapse
|
6
|
Wijekoon A, Das A, Herrera RR, Khan DZ, Hanrahan J, Carter E, Luoma V, Stoyanov D, Marcus HJ, Bano S. PitRSDNet: Predicting intra-operative remaining surgery duration in endoscopic pituitary surgery. Healthc Technol Lett 2024; 11:318-326. [PMID: 39720757 PMCID: PMC11665798 DOI: 10.1049/htl2.12099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2024] [Accepted: 11/11/2024] [Indexed: 12/26/2024] Open
Abstract
Accurate intra-operative Remaining Surgery Duration (RSD) predictions allow for anaesthetists to more accurately decide when to administer anaesthetic agents and drugs, as well as to notify hospital staff to send in the next patient. Therefore, RSD plays an important role in improved patient care and minimising surgical theatre costs via efficient scheduling. In endoscopic pituitary surgery, it is uniquely challenging due to variable workflow sequences with a selection of optional steps contributing to high variability in surgery duration. This article presents PitRSDNet for predicting RSD during pituitary surgery, a spatio-temporal neural network model that learns from historical data focusing on workflow sequences. PitRSDNet integrates workflow knowledge into RSD prediction in two forms: (1) multi-task learning for concurrently predicting step and RSD; and (2) incorporating prior steps as context in temporal learning and inference. PitRSDNet is trained and evaluated on a new endoscopic pituitary surgery dataset with 88 videos to show competitive performance improvements over previous statistical and machine learning methods. The findings also highlight how PitRSDNet improves RSD precision on outlier cases utilising the knowledge of prior steps.
Collapse
Affiliation(s)
- Anjana Wijekoon
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of Computer ScienceUniversity College LondonLondonUK
| | - Adrito Das
- UCL Hawkes InstituteUniversity College LondonLondonUK
| | | | - Danyal Z. Khan
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of NeurosurgeryNational Hospital for Neurology and NeurosurgeryLondonUK
| | - John Hanrahan
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of NeurosurgeryNational Hospital for Neurology and NeurosurgeryLondonUK
| | - Eleanor Carter
- Department of NeurosurgeryNational Hospital for Neurology and NeurosurgeryLondonUK
| | - Valpuri Luoma
- Department of NeurosurgeryNational Hospital for Neurology and NeurosurgeryLondonUK
| | - Danail Stoyanov
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of Computer ScienceUniversity College LondonLondonUK
| | - Hani J. Marcus
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of NeurosurgeryNational Hospital for Neurology and NeurosurgeryLondonUK
| | - Sophia Bano
- UCL Hawkes InstituteUniversity College LondonLondonUK
- Department of Computer ScienceUniversity College LondonLondonUK
| |
Collapse
|
7
|
Khan DZ, Valetopoulou A, Das A, Hanrahan JG, Williams SC, Bano S, Borg A, Dorward NL, Barbarisi S, Culshaw L, Kerr K, Luengo I, Stoyanov D, Marcus HJ. Artificial intelligence assisted operative anatomy recognition in endoscopic pituitary surgery. NPJ Digit Med 2024; 7:314. [PMID: 39521895 PMCID: PMC11550325 DOI: 10.1038/s41746-024-01273-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Accepted: 09/26/2024] [Indexed: 11/16/2024] Open
Abstract
Pituitary tumours are surrounded by critical neurovascular structures and identification of these intra-operatively can be challenging. We have previously developed an AI model capable of sellar anatomy segmentation. This study aims to apply this model, and explore the impact of AI-assistance on clinician anatomy recognition. Participants were tasked with labelling the sella on six images, initially without assistance, then augmented by AI. Mean DICE scores and the proportion of annotations encompassing the centroid of the sella were calculated. Six medical students, six junior trainees, six intermediate trainees and six experts were recruited. There was an overall improvement in sella recognition from a DICE of score 70.7% without AI assistance to 77.5% with AI assistance (+6.7; p < 0.001). Medical students used and benefitted from AI assistance the most, improving from a DICE score of 66.2% to 78.9% (+12.8; p = 0.02). This technology has the potential to augment surgical education and eventually be used as an intra-operative decision support tool.
Collapse
Affiliation(s)
- Danyal Z Khan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.
- Hawkes Centre, Department of Computer Science, University College London, London, UK.
| | - Alexandra Valetopoulou
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- Hawkes Centre, Department of Computer Science, University College London, London, UK
| | - Adrito Das
- Hawkes Centre, Department of Computer Science, University College London, London, UK
| | - John G Hanrahan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- Hawkes Centre, Department of Computer Science, University College London, London, UK
| | - Simon C Williams
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- Hawkes Centre, Department of Computer Science, University College London, London, UK
| | - Sophia Bano
- Hawkes Centre, Department of Computer Science, University College London, London, UK
| | - Anouk Borg
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Neil L Dorward
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | | | | | - Karen Kerr
- Digital Surgery Ltd, Medtronic, London, UK
| | | | - Danail Stoyanov
- Hawkes Centre, Department of Computer Science, University College London, London, UK
- Digital Surgery Ltd, Medtronic, London, UK
| | - Hani J Marcus
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.
- Hawkes Centre, Department of Computer Science, University College London, London, UK.
| |
Collapse
|
8
|
Khan DZ, Newall N, Koh CH, Das A, Aapan S, Layard Horsfall H, Baldeweg SE, Bano S, Borg A, Chari A, Dorward NL, Elserius A, Giannis T, Jain A, Stoyanov D, Marcus HJ. Video-Based Performance Analysis in Pituitary Surgery - Part 2: Artificial Intelligence Assisted Surgical Coaching. World Neurosurg 2024; 190:e797-e808. [PMID: 39127380 DOI: 10.1016/j.wneu.2024.07.219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2024] [Accepted: 07/31/2024] [Indexed: 08/12/2024]
Abstract
BACKGROUND Superior surgical skill improves surgical outcomes in endoscopic pituitary adenoma surgery. Video-based coaching programs, pioneered in professional sports, have shown promise in surgical training. In this study, we developed and assessed a video-based coaching program using artificial intelligence (AI) assistance. METHODS An AI-assisted video-based surgical coaching was implemented over 6 months with the pituitary surgery team. The program consisted of 1) monthly random video analysis and review; and 2) quarterly 2-hour educational meetings discussing these videos and learning points. Each video was annotated for surgical phases and steps using AI, which improved video interactivity and allowed the calculation of quantitative metrics. Primary outcomes were program feasibility, acceptability, and appropriateness. Surgical performance (via modified Objective Structured Assessment of Technical Skills) and early surgical outcomes were recorded for every case during the 6-month coaching period, and a preceding 6-month control period. Beta and logistic regression were used to assess the change in modified Objective Structured Assessment of Technical Skills scores and surgical outcomes after the coaching program implementation. RESULTS All participants highly rated the program's feasibility, acceptability, and appropriateness. During the coaching program, 63 endoscopic pituitary adenoma cases were included, with 41 in the control group. Surgical performance across all operative phases improved during the coaching period (P < 0.001), with a reduction in new postoperative anterior pituitary hormone deficit (P = 0.01). CONCLUSIONS We have developed a novel AI-assisted video surgical coaching program for endoscopic pituitary adenoma surgery - demonstrating its viability and impact on surgical performance. Early results also suggest improvement in patient outcomes. Future studies should be multicenter and longer term.
Collapse
Affiliation(s)
- Danyal Z Khan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK.
| | - Nicola Newall
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Chan Hee Koh
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Adrito Das
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Sanchit Aapan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Hugo Layard Horsfall
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Stephanie E Baldeweg
- Department of Diabetes & Endocrinology, University College London Hospitals NHS Foundation Trust, London, UK; Division of Medicine, Department of Experimental and Translational Medicine, Centre for Obesity and Metabolism, University College London, London, UK
| | - Sophia Bano
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Anouk Borg
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Aswin Chari
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Neil L Dorward
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Anne Elserius
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Theofanis Giannis
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Abhiney Jain
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Danail Stoyanov
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK; Digital Surgery Ltd, Medtronic, London, UK
| | - Hani J Marcus
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| |
Collapse
|
9
|
Hu J, Fu J, Zhao W, Lou P, Feng M, Ren H, Feng S, Li Y, Fang A. Characterizing pituitary adenomas in clinical notes: Corpus construction and its application in LLMs. Health Informatics J 2024; 30:14604582241291442. [PMID: 39379071 DOI: 10.1177/14604582241291442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/10/2024]
Abstract
Objective: Faced with the challenges of differential diagnosis caused by the complex clinical manifestations and high pathological heterogeneity of pituitary adenomas, this study aims to construct a high-quality annotated corpus to characterize pituitary adenomas in clinical notes containing rich diagnosis and treatment information. Methods: A dataset from a pituitary adenomas neurosurgery treatment center of a tertiary first-class hospital in China was retrospectively collected. A semi-automatic corpus construction framework was designed. A total of 2000 documents containing 9430 sentences and 524,232 words were annotated, and the text corpus of pituitary adenomas (TCPA) was constructed and analyzed. Its potential application in large language models (LLMs) was explored through fine-tuning and prompting experiments. Results: TCPA had 4782 medical entities and 28,998 tokens, achieving good quality with the inter-annotator agreement value of 0.862-0.986. The LLMs experiments showed that TCPA can be used to automatically identify clinical information from free texts, and introducing instances with clinical characteristics can effectively reduce the need for training data, thereby reducing labor costs. Conclusion: This study characterized pituitary adenomas in clinical notes, and the proposed method were able to serve as references for relevant research in medical natural language scenarios with highly specialized language structure and terminology.
Collapse
Affiliation(s)
- Jiahui Hu
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jin Fu
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Wanqing Zhao
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Pei Lou
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ming Feng
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Huiling Ren
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Shanshan Feng
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yansheng Li
- DHC Mediway Technology Co., Ltd., Beijing, China
| | - An Fang
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| |
Collapse
|
10
|
Zulfaliyeva G, Demir AN, Cetintas SC, Ozaydin D, Tanriover N, Kadioglu P. Role of Medical and Surgical Treatment in Management of the Patients With Prolactinoma: A Single-Center Experience. Exp Clin Endocrinol Diabetes 2024; 132:570-580. [PMID: 38991543 DOI: 10.1055/a-2364-6027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
BACKGROUND Current guidelines recommend dopamine agonists (DA) as the primary therapeutic approach for prolactinomas; however, emerging evidence suggests that surgical intervention can also yield favorable outcomes. OBJECTIVE To comprehensively evaluate prolactinoma patients undergoing surgical and medical treatments at our pituitary center. METHODS Retrospective review of mMedical records from prolactinoma patients treated between 2015 and 2022 was performedwere retrospectively reviewed. The study focused on treatment outcomes and remission rates while investigating factors influencing the success of both treatment modalities in achieving remission. RESULTS A total of 301 prolactinoma patients were included, of whom 199 were women. Among them, 235 were managed medically, while 66 underwent surgical intervention. The overall remission rates of patients treated with medical and surgery were similar at the final examination (Respectively respectively 82.9% and 81.8%, p=0.114). Factors associated with remission in both treatment modalities included female sex, low initial prolactin levels, small adenoma size, and absence of cavernous invasion. Compared to DA treatment, Ssurgical treatment demonstrated a higher rate of drug-free remission compared to DA treatment for microadenomas, and macroadenomas without cavernous invasion. In cases with cavernous invasion, standalone surgical treatment yielded a low rate of drug-free remission (7.7%); however, when combined with DA therapy post-surgery, remission rates increased to 66.7%. CONCLUSION Medical treatment with DAs remains the preferred option for macroadenomas with cavernous sinus invasion, and giant adenomas, with surgery reserved for selected cases to address complications. Conversely, surgery emerges as the most effective modality for achieving remission in patients with microadenomas, and macroadenomas confined to the sella. The recommendation of DAs as first-line therapy for all patients has been withdrawn in the current guidelines, and individual treatment approaches based on tumor characteristics are emphasized. Our results support this approach.
Collapse
Affiliation(s)
- Guldana Zulfaliyeva
- Department of Internal Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Ahmet Numan Demir
- Department of Endocrinology, Metabolism and Diabetes, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Semih Can Cetintas
- Department of Neurosurgery, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Dilan Ozaydin
- Department of Neurosurgery, Health Science University Kartal Dr Lutfi Kırdar City Hospital, Istanbul, Turkey
| | - Necmettin Tanriover
- Department of Neurosurgery, Istanbul University-Cerrahpasa, Istanbul, Turkey
- Pituitary Center, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Pinar Kadioglu
- Department of Endocrinology, Metabolism and Diabetes, Istanbul University-Cerrahpasa, Istanbul, Turkey
- Pituitary Center, Istanbul University-Cerrahpasa, Istanbul, Turkey
| |
Collapse
|
11
|
Khan DZ, Koh CH, Das A, Valetopolou A, Hanrahan JG, Horsfall HL, Baldeweg SE, Bano S, Borg A, Dorward NL, Olukoya O, Stoyanov D, Marcus HJ. Video-Based Performance Analysis in Pituitary Surgery-Part 1: Surgical Outcomes. World Neurosurg 2024; 190:e787-e796. [PMID: 39122112 DOI: 10.1016/j.wneu.2024.07.218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2024] [Accepted: 07/31/2024] [Indexed: 08/12/2024]
Abstract
BACKGROUND Endoscopic pituitary adenoma surgery has a steep learning curve, with varying surgical techniques and outcomes across centers. In other surgeries, superior performance is linked with superior surgical outcomes. This study aimed to explore the prediction of patient-specific outcomes using surgical video analysis in pituitary surgery. METHODS Endoscopic pituitary adenoma surgery videos from a single center were annotated by experts for operative workflow (3 surgical phases and 15 surgical steps) and operative skill (using modified Objective Structured Assessment of Technical Skills [mOSATS]). Quantitative workflow metrics were calculated, including phase duration and step transitions. Poisson or logistic regression was used to assess the association of workflow metrics and mOSATS with common inpatient surgical outcomes. RESULTS 100 videos from 100 patients were included. Nasal phase mean duration was 24 minutes and mean mOSATS was 21.2/30. Mean duration was 34 minutes and mean mOSATS was 20.9/30 for the sellar phase, and 11 minutes and 21.7/30, respectively, for the closure phase. The most common adverse outcomes were new anterior pituitary hormone deficiency (n = 26), dysnatremia (n = 24), and cerebrospinal fluid leak (n = 5). Higher mOSATS for all 3 phases and shorter operation duration were associated with decreased length of stay (P = 0.003 &P < 0.001). Superior closure phase mOSATS were associated with reduced postoperative cerebrospinal fluid leak (P < 0.001), and superior sellar phase mOSATS were associated with reduced postoperative visual deterioration (P = 0.041). CONCLUSIONS Superior surgical skill and shorter surgical time were associated with superior surgical outcomes, at a generic and phase-specific level. Such video-based analysis has promise for integration into data-driven training and service improvement initiatives.
Collapse
Affiliation(s)
- Danyal Z Khan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK.
| | - Chan Hee Koh
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Adrito Das
- Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Alexandra Valetopolou
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - John G Hanrahan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Hugo Layard Horsfall
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Stephanie E Baldeweg
- Department of Diabetes & Endocrinology, University College London Hospitals NHS Foundation Trust, London, UK; Division of Medicine, Department of Experimental and Translational Medicine, Centre for Obesity and Metabolism, University College London, London, UK
| | - Sophia Bano
- Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Anouk Borg
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Neil L Dorward
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Olatomiwa Olukoya
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Danail Stoyanov
- Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK; Digital Surgery Ltd, Medtronic, London, UK
| | - Hani J Marcus
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK; Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| |
Collapse
|
12
|
Zhou S, Zeng Z, Chen M, Zou L, Shao S. Incidence and influencing factors of olfactory dysfunction in patients 1 week after endoscopic transsphenoidal resection of pituitary tumor: a cross-sectional study of 158 patients. Front Neurol 2024; 15:1402626. [PMID: 39087015 PMCID: PMC11289771 DOI: 10.3389/fneur.2024.1402626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 06/28/2024] [Indexed: 08/02/2024] Open
Abstract
Objective To investigate the current situation of olfactory dysfunction in patients after endoscopic transsphenoidal resection of pituitary tumors, and analyze its influencing factors, to provide references for clinical nursing and rehabilitation. Methods A cross-sectional study design and convenience sampling method were used to investigate 158 patients with pituitary tumors treated by endoscopic transsphenoidal pituitary tumor resection in the Department of Neurosurgery of three Grade-A general hospitals in Sichuan Province from January 2022 and June 2023. The olfactory function of patients was evaluated 1 week after surgery, and the general clinical data and olfactory related data of patients were collected, and the influencing factors of olfactory disorder were analyzed by logistic regression. Results The incidence of olfactory dysfunction was 73.42%. analysis revealed that the formation of blood scabs, nasal cavity adhesion, cerebrospinal fluid leakage and operation time were independent risk factors for olfactory dysfunction in patients after transsphenoidal pituitary tumor resection (p < 0.05). Conclusion The incidence of olfactory dysfunction is high in patients after endoscopic transsphenoidal resection of pituitary tumors, suggesting that medical staff should pay close attention to and identify patients with olfactory dysfunction based on the guidance of disease knowledge and skills, develop targeted nursing interventions, and promote the improvement of patients' olfactory function and quality of life.
Collapse
|
13
|
Yataco-Wilcas CA, Diaz-Llanes BE, Coasaca-Tito YS, Lengua-Vega LA, Salazar-Campos CE. Morphometric analysis of transsphenoidal surgery in Peruvian population. Surg Neurol Int 2024; 15:156. [PMID: 38840596 PMCID: PMC11152524 DOI: 10.25259/sni_239_2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Accepted: 04/16/2024] [Indexed: 06/07/2024] Open
Abstract
Background Transsphenoidal surgery has become a key element in the approach to skull base pathologies. The objective of the study was to explore the morphometry of the sphenoidal region in the Peruvian population, with an emphasis on understanding its specific anatomical characteristics and providing quantitative data for the planning of transsphenoidal surgery. Methods A cross-sectional study included a random sample of 81 cases of healthy individuals who presented to the Radiology Department of a Private Hospital Center in Peru over 1 year. Skull computed tomography scans without contrast were performed, and a detailed morphometric analysis was conducted by an expert neurosurgeon, including measurements of four parameters to evaluate the anatomy of the craniofacial region. Results Most participants exhibited complete sellar pneumatization, followed by incomplete sellar pneumatization, while conchal pneumatization was rare. Significant differences were found between men and women in the distance from the nasal opening to the dorsum of the sella turcica. No significant gender differences were observed in other anatomical measurements or significant changes with age in anatomical measurements. Conclusion Morphometric analysis provides crucial data for the precise customization of surgical interventions in the Peruvian population, especially in transsphenoidal surgery. The results highlight the importance of considering individual anatomical differences and gender variability during surgical planning. Morphometry emerges as a valuable tool to enhance the quality and safety of transsphenoidal surgery by adapting surgical strategies to the specific anatomical dimensions of each patient.
Collapse
|
14
|
Marques P, Sagarribay A, Tortosa F, Neto L, Tavares Ferreira J, Subtil J, Palha A, Dias D, Sapinho I. Multidisciplinary Team Care in Pituitary Tumours. Cancers (Basel) 2024; 16:950. [PMID: 38473312 DOI: 10.3390/cancers16050950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 12/05/2023] [Accepted: 02/21/2024] [Indexed: 03/14/2024] Open
Abstract
The optimal care for patients with pituitary tumours is best provided in a multidisciplinary and collaborative environment, which requires the contribution of multiple medical specialties working together. The benefits and advantages of the pituitary multidisciplinary team (MDT) are broad, and all relevant international consensus and guidelines in the field recommend that patients with pituitary tumours should always be managed in a MDT. Endocrinologists and neurosurgeons are normally the leading specialties within the pituitary MDT, supported by many other specialties with significant contributions to the diagnosis and management of pituitary tumours, including neuropathology, neuroradiology, neuro-ophthalmology, and otorhinolaryngology, among others. Here, we review the literature concerning the concepts of Pituitary MDT/Pituitary Tumour Centre of Excellence (PTCOE) in terms of their mission, goals, benefits, structure, proposed models of function, and barriers, and we also provide the views of different specialists involved in our Pituitary MDT.
Collapse
Affiliation(s)
- Pedro Marques
- Pituitary Tumor Unit, Endocrinology Department, Hospital CUF Descobertas, 1998-018 Lisbon, Portugal
- Faculty of Medicine, Universidade Católica Portuguesa, 1649-023 Lisbon, Portugal
| | - Amets Sagarribay
- Pituitary Tumor Unit, Neurosurgery Department, Hospital CUF Descobertas, 1998-018 Lisbon, Portugal
| | - Francisco Tortosa
- Pituitary Tumor Unit, Pathology Department, Hospital CUF Descobertas, 1998-018 Lisbon, Portugal
| | - Lia Neto
- Pituitary Tumor Unit, Radiology Department, Hospital CUF Descobertas, 1998-018 Lisbon, Portugal
| | - Joana Tavares Ferreira
- Pituitary Tumor Unit, Ophthalmology Department, Hospital CUF Descobertas, 1998-018 Lisbon, Portugal
| | - João Subtil
- Pituitary Tumor Unit, Otorhinolaryngology Department, Hospital CUF Descobertas, 1998-018 Lisbon, Portugal
| | - Ana Palha
- Pituitary Tumor Unit, Endocrinology Department, Hospital CUF Descobertas, 1998-018 Lisbon, Portugal
| | - Daniela Dias
- Pituitary Tumor Unit, Endocrinology Department, Hospital CUF Descobertas, 1998-018 Lisbon, Portugal
| | - Inês Sapinho
- Pituitary Tumor Unit, Endocrinology Department, Hospital CUF Descobertas, 1998-018 Lisbon, Portugal
| |
Collapse
|