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Record W4405316672 · doi:10.7759/cureus.75600

Synaptive Magnetic Resonance Imaging for Stereotactic Radiosurgery

2024· article· en· W4405316672 on OpenAlexaboutno aff
Michael Chaga, Timothy Chen, Wenzheng Feng, Daniela Conti, Jing Feng, Tingyu Wang, Ma Rhudelyn Rodrigo, Elizabeth Luick, Daniel Thompson, Brielle Latif, Joseph Hanley, Shabbar F. Danish

Bibliographic record

VenueCureus · 2024
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiosurgeryMagnetic resonance imagingMedical physicsImaging phantomImage qualityQuality assuranceMedical imagingRadiologyContext (archaeology)Nuclear medicineComputer scienceRadiation therapyArtificial intelligence

Abstract

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Introduction The Synaptive magnetic resonance imaging (MRI) system (Synaptive Medical, Toronto, Canada) is a midfield 0.5 T head-only scanner for imaging the head and neck in adults and pediatrics. The system received US FDA and Health Canada clearance for clinical use in 2020. Initial installations occurred at sites throughout Canada with the first international installation occurring in the USA at Hackensack Meridian's Jersey Shore University Medical Center (JSUMC) in October 2023. The design of the Synaptive MRI allows the system to be installed and operated outside the context of standard Radiology facilities. In this study, we describe the implementation and adaptation of the Synaptive MRI into the cranial stereotactic radiosurgery (SRS) workflow, with the intention of reducing the time between consultation, MRI, and treatment. Methods The Synaptive MRI was installed next to the cranial SRS suite in the Radiation Oncology (RO) department, dedicated solely to SRS planning image acquisition. Geometric distortion was evaluated using the Magphan 128 Distortion Phantom (Phantom Laboratory, Greenwich, NY). The simplicity of the Synaptive interface allows Radiation Therapist operation, in the State of New Jersey, without the need for the physical presence of an MRI technologist. During imaging acquisition, the Physician verifies image quality and can rescan or make adjustments as needed, allowing for instantaneous confirmation of image quality. The Synaptive comes with a full set of neuro pulse sequences and protocols ranging from T1 3D spoiled gradient recalled echo to time-of-flight magnetic resonance angiography. Patient MRI comfort was evaluated after treatment by questionnaire for 51 patients using a Likert scale from 1 to 5 (1 = "very poor", 5 = "very good"). The total Synaptive MRI time for 38 patients was tracked from arrival at the MRI suite to completion of imaging. Times from consult, imaging, and treatment for 58 ZAP-X (ZAP Surgical Systems, Inc., San Carlos, CA) SRS patients at JSUMC RO in 2024 who received Synaptive MRI were obtained from Aria (Varian Medical Systems, Palo Alto, CA) electronic medical records. JSUMC RO Departmental data was obtained on times from consult, imaging, and treatment for 58 randomly sampled patients from 2018 to 2023 whose treatment planning imaging was performed on out-of-department MRI units for comparison. Results The distortions on this system are less than 0.52 mm, for distances up to 90 mm from the isocenter. The average MRI comfort was 4.7 ± 0.5. The average total MRI time for 38 patients was 36 ± 3 minutes. The median time for 58 ZAP-X SRS patients from MRI to treatment was seven days (interquartile range: p25 = six days, p75 = 10 days), consult to MRI 1.5 days (p25 = 0 days, p75 = nine days), and consult to treatment 12 days (p25 = seven days, p75 = 19 days). The median time for 34 malignant ZAP-X SRS patients from MRI to treatment was six days (p25 = five days, p75 = eight days) and from consult to treatment nine days (p25 = six days, p75 = 18 days). Significant decreases in MRI to treatment times (P < 0.001) and benign consult to MRI times (P = 0.0039) were demonstrated for 2024 Synaptive patients compared to 2018-2023 patients. Conclusion Dedicated Synaptive MRI installation for SRS in RO departments can improve the SRS workflow, potentially providing a more streamlined experience and reducing the time from diagnosis and imaging to treatment for cranial pathologies.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.286
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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