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| ID | Type | Description | Link |
|---|---|---|---|
| PNRR-TR1-2023-12378146 | Other Grant/Funding Number | European Union (EU) |
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| Name | Class |
|---|---|
| ASL 1 Avezzano Sulmona L'Aquila | OTHER |
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This study focuses on rare brain tumors, which are heterogeneous entities with different morphological, biological, and clinical characteristics. Due to their rarity, many of these tumors fall under the RARECARE definition of rare tumors. The main objective of the study is to standardize care models and pathways for patients with rare brain tumors, using Artificial Intelligence (AI) and Machine Learning (ML) techniques to identify specific predictors of postoperative outcomes.
The study includes both retrospective and prospective phases, with the collection of clinical, cognitive, and psychological data at various time points. Patients will undergo an early neuro-cognitive rehabilitation program using the RehaCom software, which will be conducted at home. The goal is to improve the quality of life and care for patients through a multidisciplinary and innovative approach.
Participants will be adults with rare brain tumors and will be enrolled at two neurosurgery centers in Italy. The study aims to create a network of professionals specialized in predicting surgical outcomes, thereby improving the overall quality of care and the quality of life for patients.
This study aims to improve the care and outcomes for patients with rare brain tumors (rBT) by standardizing clinical pathways and utilizing advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML). Rare brain tumors, including astrocytomas, oligodendrogliomas, neuronal tumors, malignant meningiomas, and embryonal tumors, are defined as rare due to their low incidence (<6 cases per 100,000 people/year).
The study will be conducted in two phases: a retrospective phase and a prospective phase. The retrospective phase will involve the use of existing neurosurgical databases to implement ML algorithms. The prospective phase will include the collection of clinical, cognitive, and psychological data at multiple time points (pre-surgery, discharge, 3 months post-surgery, and 12 months post-surgery).
Patients will participate in an early neuro-cognitive rehabilitation program using the RehaCom software, designed to enhance cognitive functions potentially affected by surgery. The rehabilitation will be conducted at the patient's home.
The primary objective is to develop a common evaluation protocol that includes clinical, cognitive, psychological, and sociodemographic measures. Secondary objectives include identifying predictors of surgical outcomes through retrospective and prospective studies and developing predictive models for rare brain tumors.
The study will enroll approximately 200 adult patients from two neurosurgery centers in Italy. Inclusion criteria include adults (≥18 years) undergoing craniotomy for rare brain tumors, while exclusion criteria include patients undergoing stereotactic biopsy, those with psychiatric disorders, or those lacking the necessary technology for home-based rehabilitation.
The ultimate goal is to create a multidisciplinary network of professionals specialized in predicting surgical outcomes, thereby improving the overall quality of care and the quality of life for patients with rare brain tumors.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Single Group | Experimental | This group includes all adult participants with rare brain tumors who will receive early neuro-cognitive rehabilitation using the RehaCom software. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| RehaCom | Device | Participants will receive a personalized neuro-cognitive rehabilitation program using the RehaCom software. Sessions will last approximately 30/40 minutes and will be held twice a week for 8 weeks. The rehabilitation will be aimed at enhancing and/or recovering cognitive functions that may have been compromised by the neurosurgical intervention. |
| Measure | Description | Time Frame |
|---|---|---|
| Symptoms/Signs Onset | Monitoring of headache, seizures, and neurological deficits pre- and post-operatively. Unit of Measure: Number of patients with specific symptoms. | Pre-operative |
| Karnofsky Performance Status (KPS) | Karnofsky Performance Status (KPS) score - Assessment of functional capacity on a scale from 0 to 100, where 100 indicates no symptoms and full activity, and 0 indicates death. | 12 months. |
| Neurology Assessment in Neuro-Oncology (NANO) | NANO scale score - Evaluation of neurological function using the Neurological Assessment in Neuro-Oncology (NANO) scale, which assesses nine clinically relevant domains: gait, strength, ataxia, sensation, visual fields, facial strength, language, level of consciousness, and behavior. Each domain is scored from 0 to 4, with higher scores indicating greater impairment. | From hospital admission until discharge |
| Modified Rankin Scale (mRS) | Disability score (0-6) - Measurement of disability or dependence in daily activities on a scale from 0 to 6, where 0 indicates no symptoms and 6 indicates death. | 12 months |
| American Society of Anesthesiologists (ASA) | Assessment of the patient's physical status before surgery using the ASA classification system. This system categorizes patients based on their overall health and the presence of systemic diseases. ASA classification score from I to VI, with higher scores indicating greater severity of systemic disease and higher perioperative risk. | Pre-operative |
| Charlson Comorbidity Index (CCI) |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| GIORGIA CAMARDA, Master's degree | Contact | +23 02 2394 | 2949 | giorgia.camarda@istituto-besta.it |
| Name | Affiliation | Role |
|---|---|---|
| Paolo Ferroli, MD | Fondazione IRCCS Istituto Neurologico Carlo Besta | Principal Investigator |
| Alessandro Ricci, MD | ASL 1 Abruzzo Avezzano-Sulmona-L'Aquila | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Fondazione IRCCS Istituto Neurologico Carlo Besta | Recruiting | Milan | PA | 20133 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35573928 | Background | Fan FL, Xiong J, Li M, Wang G. On Interpretability of Artificial Neural Networks: A Survey. IEEE Trans Radiat Plasma Med Sci. 2021 Nov;5(6):741-760. doi: 10.1109/trpms.2021.3066428. Epub 2021 Mar 17. | |
| 27315026 | Background | Sagberg LM, Drewes C, Jakola AS, Solheim O. Accuracy of operating neurosurgeons' prediction of functional levels after intracranial tumor surgery. J Neurosurg. 2017 Apr;126(4):1173-1180. doi: 10.3171/2016.3.JNS152927. Epub 2016 Jun 17. |
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| ID | Term |
|---|---|
| D001932 | Brain Neoplasms |
| D008579 | Meningioma |
| ID | Term |
|---|---|
| D016543 | Central Nervous System Neoplasms |
| D009423 | Nervous System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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This group includes all adult participants with rare brain tumors who will receive early neuro-cognitive rehabilitation using the RehaCom software.
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The CCI evaluates comorbid conditions to predict ten-year mortality. It includes 17 categories of comorbidities, such as myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, connective tissue disease, peptic ulcer disease, liver disease, diabetes mellitus, hemiplegia, chronic kidney disease, solid tumor, leukemia, lymphoma, and AIDS. Each condition is assigned a score based on its associated risk of mortality. The total score is the sum of the individual scores for each condition, with higher scores indicating a greater number of comorbid conditions and higher predicted mortality.
| Pre-operative |
| Magnetic Resonance Imaging (MRI) | Measurement of tumor size (in cm or mm), location (e.g., frontal lobe, temporal lobe), and side (right, left, bilateral). | 12 months. |
| Eloquent Area Involvement | Assessment of whether the tumor involves eloquent brain areas (motor, sensory, language, visual; dominant hemisphere). Unit of Measure: Yes/No. | Intra-operative |
| Cranial Nerve Manipulation | Evaluation of cranial nerve involvement during surgery. unit of Measure: Yes/No | Intra-operative |
| Vascular Manipulation | Assessment of vascular involvement during surgery (specify vessels: ICA, ACA, MCA, Acom, PcomA, anterior choroidal, ophthalmic, vertebral, basilar, PICA, AICA, SCA, posterior cerebral; superior sagittal sinus, transverse, sigmoid, straight, internal cerebral veins, vein of Galen, Labbe, Trolard. unit of Measure: Yes/No | Intra-operative |
| Extent of Resection | Measurement of the extent of tumor resection (total 100% (GTR), subtotal 90-100% (STR), partial <90% (PR), open biopsy, needle biopsy | Post-operative immediate |
| Edema | Evaluation of the presence and extent of edema (no, perilesional, diffuse), Unit of Measure: Yes/No, extent in cm or mm | Pre-operative |
| Deep Location | Assessment of whether the tumor is located in deep brain structures (basal ganglia, brainstem, pineal, thalamus, hypothalamus, unit of Measure: Yes/No | Pre-operative |
| Histology and Molecular Data | Histological classification according to WHO 2021, integrated with molecular data | Post-operative |
| Preoperative Neurological Examination (EON) | Description of deficits (none; motor; sensory; cognitive; language; cranial nerves; intracranial hypertension; epilepsy; hormonal/hypothalamic disturbances; optic pathways; cerebellar, unit of Measure: Type of deficit | Pre-operative |
| Tumor Side | Side of the tumor (right; left; bilateral; median). | during surgery |
| Tumor Location | Location of the tumor (frontal, Rolandic, Broca, insular, temporal, parietal, occipital, intraventricular (lateral only), third ventricle, sella, sella+suprasellar/parasellar, clivus, optic+optic pathways, orbit, petroclival, cavernous sinus, planum/olfactory grooves, clinoid, falx, cerebellar, cerebellopontine angle, medulla, pons, midbrain, fourth ventricle, foramen magnum, pineal). | pre-procedure |
| Cranial Nerve Status | Status of cranial nerves I-XII (normal; deficit), House-Brackmann scale for cranial nerve VII (1-5), hearing status for cranial nerve VIII (useful hearing; non-useful hearing), status of cranial nerves IX-X (normal; deficit; tracheostomy; PEG). | pre-procedure |
| Cognitive Data Collection: Phonemic Verbal Fluency | Assessment of verbal fluency by asking patients to generate as many words as possible beginning with a specific letter within a set time limit. Unit of Measure: Number of words generated. Higher scores indicate better verbal fluency. | 12 months. |
| Cognitive Data Collection: Semantic Verbal Fluency | Assessment of verbal fluency by asking patients to generate as many words as possible within a specific category (e.g., animals) within a set time limit. Unit of Measure: Number of words generated. Higher scores indicate better verbal fluency. | 12 months. |
| Cognitive Data Collection:Token Test | Assessment of language comprehension by asking patients to follow verbal instructions involving tokens of different shapes, sizes, and colors. Unit of Measure: Higher scores indicate better language comprehension. | 12 months. |
| Cognitive Data Collection: Digit Span Forward and Backward | Assessment of working memory by asking patients to repeat a sequence of numbers in the same order (forward) and in reverse order (backward). Unit of Measure: Number of digits correctly recalled. Higher scores indicate better working memory. | 12 months. |
| Cognitive Data Collection: Rey 15-Word List | Assessment of verbal memory by asking patients to recall a list of 15 words immediately after presentation and after a delay. Unit of Measure: Number of words correctly recalled. Higher scores indicate better verbal memory. | 12 months. |
| Cognitive Data Collection: Rey Figure Reproduction | Assessment of visuospatial memory by asking patients to reproduce a complex figure from memory. Unit of Measure: Score on the Rey Figure Reproduction. Higher scores indicate better visuospatial memory. | 12 months. |
| Cognitive Data Collection: Modified Taylor Complex Figure | Assessment of visuospatial construction and memory by asking patients to copy and then reproduce a complex figure from memory. Unit of Measure: Score on the Modified Taylor Complex Figure. Higher scores indicate better visuospatial construction and memory. | Pre-operative, follow-up at 3 and 12 months. |
| Cognitive Data Collection:Trail Making Test | Assessment of attention and task-switching by asking patients to connect a sequence of numbered and lettered circles as quickly as possible. Unit of Measure: Time taken to complete the task. Lower times indicate better performance. | Pre-operative, follow-up at 3 and 12 months. |
| Cognitive Data Collection: Stroop Test | Assessment of cognitive flexibility and processing speed by asking patients to name the color of the ink in which a word is printed, which may differ from the word itself (e.g., the word "red" printed in blue ink). Unit of Measure: Time taken to complete the task. Lower times indicate better performance. | 12 months. |
| Cognitive Data Collection: Mini-Mental State Examination (MMSE) | Assessment of general cognitive function, including orientation, registration, attention and calculation, recall, and language. Unit of Measure: Score on the MMSE (0-30). Higher scores indicate better cognitive function. | 12 months. |
| Cognitive Data Collection: Frontal Assessment Battery | Assessment of executive functions, including conceptualization, mental flexibility, motor programming, sensitivity to interference, inhibitory control, and environmental autonomy. Unit of Measure: Score on the FAB (0-18). Higher scores indicate better executive function. | 12 months. |
| Psychological and Quality of Life Data Collection: WHO Disability Assessment Schedule (WHODAS 2.0) | Assessment of disability using the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). This tool evaluates six domains of functioning: cognition, mobility, self-care, getting along, life activities, and participation. Scores range from 0 to 100, with higher scores indicating greater disability. | 12 months. |
| Psychological and Quality of Life Data Collection: European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) | Assessment of quality of life using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). This 30-item questionnaire measures various aspects of quality of life in cancer patients, including physical, role, cognitive, emotional, and social functioning, as well as symptoms and global health status. Higher scores on functional scales indicate better functioning, while higher scores on symptom scales indicate worse symptoms | 12 months. |
| Psychological and Quality of Life Data Collection: European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire - Brain Neoplasms 20 (EORTC QLQ-BN20) | Assessment of quality of life specific to brain tumor patients using the EORTC QLQ-BN20. This module evaluates symptoms and issues relevant to brain tumor patients, such as future uncertainty, visual disorders, motor dysfunction, and communication deficits. Higher scores indicate worse symptoms or issues. | 12 months. |
| Psychological and Quality of Life Data Collection: Hospital Anxiety and Depression Scale (HADS) | Assessment of anxiety and depression using the Hospital Anxiety and Depression Scale (HADS). This 14-item tool produces two subscales: HADS-A (anxiety) and HADS-D (depression). Scores range from 0 to 21 for each subscale, with higher scores indicating greater levels of anxiety or depression. | 12 months. |
| ASL 1 Abruzzo Avezzano-Sulmona-L'Aquila | Not yet recruiting | L’Aquila | 67100 | Italy |
|
| 33572349 | Background | Lopez-Nunez O, Alaggio R, John I, Ciolfi A, Pedace L, Mastronuzzi A, Gianno F, Giangaspero F, Rossi S, Donofrio V, Cinalli G, Surrey LF, Tartaglia M, Locatelli F, Miele E. Melanotic Neuroectodermal Tumor of Infancy (MNTI) and Pineal Anlage Tumor (PAT) Harbor A Medulloblastoma Signature by DNA Methylation Profiling. Cancers (Basel). 2021 Feb 9;13(4):706. doi: 10.3390/cancers13040706. |
| 24254135 | Background | Bunevicius A, Tamasauskas S, Deltuva V, Tamasauskas A, Radziunas A, Bunevicius R. Predictors of health-related quality of life in neurosurgical brain tumor patients: focus on patient-centered perspective. Acta Neurochir (Wien). 2014 Feb;156(2):367-74. doi: 10.1007/s00701-013-1930-7. Epub 2013 Nov 20. |
| 24266542 | Background | Rolston JD, Han SJ, Lau CY, Berger MS, Parsa AT. Frequency and predictors of complications in neurological surgery: national trends from 2006 to 2011. J Neurosurg. 2014 Mar;120(3):736-45. doi: 10.3171/2013.10.JNS122419. Epub 2013 Nov 22. |
| 29629232 | Background | Broggi M, Zattra C, Ferroli P. How to compare outcomes and complications in neurosurgery: We must make the mission possible! Surg Neurol Int. 2018 Mar 19;9:65. doi: 10.4103/sni.sni_424_17. eCollection 2018. No abstract available. |
| 26621412 | Background | Ferroli P, Broggi M, Schiavolin S, Acerbi F, Bettamio V, Caldiroli D, Cusin A, La Corte E, Leonardi M, Raggi A, Schiariti M, Visintini S, Franzini A, Broggi G. Predicting functional impairment in brain tumor surgery: the Big Five and the Milan Complexity Scale. Neurosurg Focus. 2015 Dec;39(6):E14. doi: 10.3171/2015.9.FOCUS15339. |
| 28986230 | Background | Senders JT, Staples PC, Karhade AV, Zaki MM, Gormley WB, Broekman MLD, Smith TR, Arnaout O. Machine Learning and Neurosurgical Outcome Prediction: A Systematic Review. World Neurosurg. 2018 Jan;109:476-486.e1. doi: 10.1016/j.wneu.2017.09.149. Epub 2017 Oct 3. |
| 29502163 | Background | Schiavolin S, Raggi A, Scaratti C, Leonardi M, Cusin A, Visintini S, Acerbi F, Schiariti M, Zattra C, Broggi M, Ferroli P. Patients' reported outcome measures and clinical scales in brain tumor surgery: results from a prospective cohort study. Acta Neurochir (Wien). 2018 May;160(5):1053-1061. doi: 10.1007/s00701-018-3505-0. Epub 2018 Mar 3. |
| 25046789 | Background | Reponen E, Tuominen H, Korja M. Evidence for the use of preoperative risk assessment scores in elective cranial neurosurgery: a systematic review of the literature. Anesth Analg. 2014 Aug;119(2):420-432. doi: 10.1213/ANE.0000000000000234. |
| D001927 |
| Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D009380 | Neoplasms, Nerve Tissue |
| D009370 | Neoplasms by Histologic Type |
| D009383 | Neoplasms, Vascular Tissue |
| D008577 | Meningeal Neoplasms |