Synaptive Magnetic Resonance Imaging for Stereotactic Radiosurgery
Bibliographic record
Abstract
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".