SIMPLIFication of Care Pathways for Patients With Rare Brain Tumors Through Artificial Intelligence (SIMPLIF-AI)

SIMPLIF-AI: SIMPLIFication and Standardization of Care Pathways for Patients With Rare Brain Tumors Through Artificial Intelligence

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.

Study Overview

• Status: Recruiting
• Conditions: Brain Tumors
• Intervention / Treatment: Device: RehaCom

Detailed Description

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.

• Study Type: Interventional
• Enrollment (Estimated): 200
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: GIORGIA CAMARDA, Master's degree; Phone Number: 2949 +23 02 2394; Email: giorgia.camarda@istituto-besta.it

Study Locations

• Italy
  • L’Aquila, Italy, 67100
    • Not yet recruiting
    • ASL 1 Abruzzo Avezzano-Sulmona-L'Aquila
    • Contact: Alessandro Ricci, MD; Phone Number: 2949 + 02 2394; Email: protocollogenerale@pec.asl1abruzzo.it
  • PA
    • Milan, PA, Italy, 20133
      • Recruiting
      • Fondazione IRCCS Istituto Neurologico Carlo Besta
      • Contact: GIORGIA CAMARDA; Phone Number: 2949 02 2394; Email: giorgia.camarda@istituto-besta.it

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Adults (age ≥18 years)
• Both sexes
• Patients with rare brain tumors (incidence <6 cases per 100,000 people/year)
• Candidates for craniotomy for rare brain tumors
• Native Italian speakers for cognitive and psychological evaluation and neuro-cognitive rehabilitation

Exclusion Criteria:

• Patients undergoing stereotactic/frameless biopsy
• Patients with psychiatric disorders or on psychotropic medications
• Patients with known cognitive decline (not due to the lesion)
• Patients admitted on the same day as the surgery
• Patients with severe impairments referred to rehabilitation centers
• Patients without a Windows PC or laptop with Internet connection for neuro-cognitive rehabilitation

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Single Group; This group includes all adult participants with rare brain tumors who will receive early neuro-cognitive rehabilitation using the RehaCom software.	Device: RehaCom; 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	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
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)	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
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: 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.
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
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.
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: 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.

Collaborators and Investigators

• Sponsor: Fondazione I.R.C.C.S. Istituto Neurologico Carlo Besta
• Collaborators: ASL 1 Avezzano Sulmona L'Aquila
• Investigators: Principal Investigator: Paolo Ferroli, MD, Fondazione IRCCS Istituto Neurologico Carlo Besta; Principal Investigator: Alessandro Ricci, MD, ASL 1 Abruzzo Avezzano-Sulmona-L'Aquila

Publications and helpful links

General Publications

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.

Study record dates

Study Major Dates

• Study Start (Actual): January 27, 2025
• Primary Completion (Actual): July 1, 2025
• Study Completion (Estimated): February 1, 2027

Study Registration Dates

• First Submitted: January 30, 2025
• First Submitted That Met QC Criteria: March 12, 2025
• First Posted (Actual): March 17, 2025

Study Record Updates

• Last Update Posted (Actual): February 19, 2026
• Last Update Submitted That Met QC Criteria: February 17, 2026
• Last Verified: February 1, 2026

More Information

Terms related to this study

• Keywords: Artificial Intelligence; neurosurgery; Machine Learning; neurocognitive rehabilitation; Rare brain tumors; outcomes predictions; innovative models; health care pathways; Astrocytic tumors of CNS; Oligodendroglial tumors of CNS; Ependymal tumors of CNS; Neuronal and mixed neuronal-glial tumors; Choroid plexus carcinoma of CNS; Malignant meningiomas; Embryonal tumors of CNS
• Additional Relevant MeSH Terms: Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Neoplasms by Site; Neoplasms; Neoplasms by Histologic Type; Neoplasms, Nerve Tissue; Nervous System Neoplasms; Neoplasms, Vascular Tissue; Meningeal Neoplasms; Central Nervous System Neoplasms; Meningioma; Brain Neoplasms
• Other Study ID Numbers: SIMPLIF-AI; PNRR-TR1-2023-12378146 (Other Grant/Funding Number: European Union (EU))

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No