GigHz Precision AI

    Radiology dictation that doesn't make you remember Bosniak at 4pm.

    For every liver mass, manually recall LI-RADS criteria. For every lung nodule, Fleischner. For every renal cyst, Bosniak. For every adrenal nodule, washout calculation. Get them wrong or omit them and you've created liability and inconsistency across your practice.

    GigHz Precision AI structures dictation into Technique → Findings → Impression and embeds the relevant clinical scoring system in the right place — not as a pop-up lookup, but as part of how the report is generated. LI-RADS, Lung-RADS v2022, Fleischner, Bosniak v2019, adrenal washout, TI-RADS, BI-RADS, PI-RADS, and more — applied automatically as the radiologist talks.

    See it work

    40-sec live demo — PE study + Fleischner nodule popup

    What gets missed in a thousand reads a year

    Radiologists dictate thousands of reports a year. Three failure modes that aren't about clinical knowledge — they're about cognitive load and consistency:

    Numeric scoring under fatigue

    LI-RADS, Bosniak, Lung-RADS — these are categorical assignments with numeric thresholds. They aren't easy to recall by 4pm on a 100-RVU day. Wrong category creates downstream care-pathway errors.

    Inconsistency across the practice

    Same finding reported four different ways across four radiologists. Referring physicians can't trend the patient. Quality reviews can't assess. The group looks unstandardized — because it is.

    Generic AI dictation misses the clinical layer

    Most 'AI radiology' tools target image analysis or worklist triage. The dictation tools don't know LI-RADS exists. Radiologists end up doing the scoring as a separate step — or skipping it.

    What Precision AI embeds in the dictation flow

    The system recognizes from context which scoring framework applies. The radiologist describes the finding; the classification surfaces inline.

    Liver

    LI-RADS — automatic

    Describe a liver lesion with size, arterial enhancement, and washout — Precision AI surfaces the LI-RADS category in the impression, with rationale traceable to the criteria. Major and ancillary features mapped automatically.

    LR-1 → LR-5 Major features Ancillary features
    Lung

    Fleischner + Lung-RADS — embedded

    Pulmonary nodule size, density, and growth context produce Fleischner follow-up recommendations or Lung-RADS scoring directly in the impression. Defensible documentation, no separate worksheet.

    Solid / part-solid / GGN Lung-RADS 1–4X Fleischner timing
    Renal

    Bosniak v2019 — applied correctly

    Cyst features → Bosniak category, with the right thresholds for septations, wall thickness, and enhancement. The version that referring urologists actually use, not the 2005 version that's still in some templates.

    I → IV IIF qualifiers v2019 thresholds
    Adrenal

    Washout — calculated

    Pre-contrast, portal-venous, and delayed HU values produce absolute and relative washout percentages and the appropriate adenoma-vs-not call — built into the report instead of a calculator window.

    Absolute washout Relative washout Diameter thresholds

    What it looks like in the workflow

    GigHz Precision AI listens to your natural dictation and detects when classification criteria apply. It surfaces the relevant popup, pre-fills what it can, and lets you confirm or adjust. Semi-automatic — the AI proposes, you verify.

    LI-RADS auto-detection

    Dictate a liver lesion with arterial enhancement and washout. Precision AI detects LI-RADS criteria, surfaces the classification popup, and assigns a category. You review and confirm.

    Adrenal washout calculation

    Pre-contrast, portal-venous, and delayed HU values produce absolute and relative washout — and the adenoma call — directly in the impression. No separate calculator window.

    Lung-RADS classification

    Dictate a pulmonary nodule with size and type. Lung-RADS v2022 applies, the category is assigned, and follow-up language gets generated in the impression.

    🩻 + Bosniak · TI-RADS · BI-RADS · PI-RADS · Fleischner

    Plus the rest

    Bosniak v2019 for renal cysts, TI-RADS for thyroid nodules, BI-RADS for breast, PI-RADS for prostate MRI, Fleischner for pulmonary nodule follow-up — all embedded in the same dictation pass.

    Why Precision AI is different from your current dictation tool

    Most AI radiology tools work on the image. Precision AI works on the report — the part of radiology that touches every read, every day.

    📐

    Embedded, not bolted-on

    Scoring surfaces inline, in the impression — not as a pop-up calculator the radiologist closes without reading. The workflow stays speech-first.

    🩻

    Multiple frameworks in one report

    A chest CT can hit Lung-RADS, Fleischner, and adrenal washout in the same read. Precision AI handles all four scoring layers in a single dictation pass.

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    Defensible documentation

    Every category assignment is traceable to the criteria. Quality reviews and medico-legal audits get a structured trail instead of a free-text impression.

    Who's using it

    Practicing radiologists

    Diagnostic + IR — full-volume practices

    Body imaging, abdominal, thoracic, IR — the radiologists doing the highest scoring-framework volume. Validation Partner program is currently selecting practices.

    Apply →
    Residents & fellows

    Free access in exchange for feedback

    Residency and fellowship trainees get 3+ months of free access. Apply with PGY year and program. Designed to teach structured reporting alongside clinical scoring frameworks.

    Apply (residents) →
    Practice directors

    Standardize departmental reporting

    Practice directors using Precision AI to bring consistency across radiologists — same finding reported the same way, every time, with traceable scoring.

    Talk to us →
    Teleradiology groups

    Enforce quality across distributed reads

    Teleradiology groups whose radiologists work across many client systems benefit most from baked-in scoring frameworks. Same report quality regardless of site template.

    Contact →

    Common questions

    Is this another image-analysis AI?

    No. Precision AI works on the report layer — dictation, structuring, and clinical scoring. It does not analyze pixels. The radiologist still reads the study; Precision AI handles how that read becomes a report.

    Which scoring frameworks are covered?

    LI-RADS (current version), Lung-RADS, Fleischner Society follow-up criteria, Bosniak v2019, adrenal washout calculation, and a growing list of additional frameworks. New frameworks are added based on Validation Partner feedback.

    Does it handle PHI?

    Precision AI processes report text. PHI handling is part of the deployment configuration — most Validation Partner deployments are designed so PHI doesn't leave the practice's environment unnecessarily.

    How do residents and fellows get free access?

    Apply at /radiology-report-assistant/residents/ with PGY year and program. Free 3+ months in exchange for structured feedback. The trainee program is specifically about teaching structured reporting alongside the scoring layer.

    What's the medico-legal posture?

    Precision AI surfaces classification with traceable rationale. The radiologist remains the responsible interpreter and finalizes the report. The structured trail of how each category was assigned is more defensible than free-text impressions, not less.

    Who built it?

    Pouyan Golshani, MD — practicing interventional radiologist — and the GigHz team. Built because the dictation layer is where every read touches and where consistency tooling barely exists.

    Stop recalling Bosniak from memory.

    Apply as a Validation Partner — three months of full Precision AI access in exchange for structured feedback. Or apply for the trainee program if you're a resident or fellow.

    GigHz Precision AI surfaces clinical scoring with traceable rationale to support — not replace — the interpreting radiologist. The radiologist remains responsible for the final report. A GigHz product. Built by Pouyan Golshani, MD.

    Written and reviewed by Pouyan Golshani, MD, Interventional Radiologist — Last updated April 7, 2026