structuring-radiology-reports

Structuring radiology reports

A radiology report is prose, but its meaning is structured: a technique, a comparison, a list of findings (each with anatomy, laterality, and a measurement), and an impression that may carry an assessment category (BI-RADS, Lung-RADS) and a follow-up recommendation. This skill turns the narrative into that structure so findings are trackable — especially incidental findings that need downstream follow-up.

OpenMed extracts the anatomy, disease/finding, and measurement spans on-device; this skill organizes them into sectioned, coded findings. It is decision-support, not a diagnostic device — every structured finding must be attributable back to its source sentence for radiologist review.

When to use

• You have a CT/MRI/X-ray/US/mammography report and need {technique, comparison, findings[], impression} with measurements and laterality.
• You must capture BI-RADS (breast) or Lung-RADS (lung screening) assessment categories and the recommended action.
• You need to track incidental findings and the follow-up interval/modality the report recommends.
• You are mapping findings toward RadLex terms or a DICOM-SR structured report.

Quick start

import openmed

report = (
    "TECHNIQUE: CT chest without contrast.\n"
    "COMPARISON: CT 2023-11-02.\n"
    "FINDINGS: A 8 mm solid nodule is noted in the right upper lobe, "
    "unchanged. No pleural effusion.\n"
    "IMPRESSION: 8 mm right upper lobe nodule, stable. Lung-RADS 2. "
    "Recommend annual low-dose CT screening."
)

# 1) De-identify the report on-device first (synthetic example shown).
deid = openmed.deidentify(report, policy="hipaa_safe_harbor")
text = deid.deidentified_text

# 2) Run NER for anatomy / finding / measurement spans.
ents = openmed.analyze_text(
    text,
    model_name="anatomy_detection_superclinical",   # Anatomy category
    output_format="dict",
)["entities"]

# 3) Split sections by header, then attach entities + measurements per finding.
import re
SECTION = re.compile(r"(?im)^(TECHNIQUE|COMPARISON|FINDINGS|IMPRESSION)\s*:")
sections, last, name = {}, 0, None
for m in SECTION.finditer(text):
    if name: sections[name] = text[last:m.start()].strip()
    name, last = m.group(1).upper(), m.end()
if name: sections[name] = text[last:].strip()

structured = {
    "technique": sections.get("TECHNIQUE"),
    "comparison": sections.get("COMPARISON"),
    "findings": _split_findings(sections.get("FINDINGS", "")),   # one per sentence
    "impression": sections.get("IMPRESSION"),
    "measurements": re.findall(r"\b\d+(?:\.\d+)?\s?(?:mm|cm)\b", text),
    "laterality": sorted({w for w in ("right", "left", "bilateral")
                          if re.search(rf"\b{w}\b", text, re.I)}),
    "assessment": (re.search(r"\b(?:BI-RADS|Lung-RADS)\s*\d[A-C]?\b", text, re.I)
                   or [None])[0] if re.search(r"RADS", text, re.I) else None,
    "follow_up": _extract_followup(sections.get("IMPRESSION", "")),
}