Lung ultrasound
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"lung ultrasound"[MeSH Terms] AND diagnosis
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"lung ultrasound" AND "point of care"
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Lung Ultrasound (LUS)
Lung ultrasound has evolved from a niche tool into an indispensable bedside modality for rapid diagnosis across emergency medicine, critical care, pulmonology, and anesthesia. It is more sensitive than chest radiography for several key pathologies, and can be performed at the bedside in under a minute.
Transducer Selection
- High-frequency linear-array (5-10 MHz): preferred for pneumothorax detection (higher resolution and sensitivity: 82% vs. 76% compared with convex transducers)
- Phased-array or curvilinear (lower frequency): preferred when depth is needed (e.g., B-line assessment, pleural effusion, deep consolidation - must reach >15 cm depth to distinguish B-lines from Z-lines)
- Microconvex: versatile for general use
Core Ultrasound Signs
1. The Pleural Line
The normal visceral and parietal pleura appear as a bright hyperechoic line that glistens and shimmers with respirations - this is "lung sliding." It confirms that the two pleural layers are in contact.
2. A-Lines (Horizontal Artifacts)
- Equidistant, horizontal, hyperechoic lines parallel to the pleural surface
- Reverberation artifact from reflections of the pleural line
- Seen in normal aerated lung, but also in pneumothorax, PE, COPD, and asthma
- Not specific - their meaning depends on whether lung sliding is present or absent
3. B-Lines (Vertical Artifacts - "Comet Tails" / "Lung Rockets")
- Discrete, hyperechoic, laser-like vertical rays arising from the pleural surface
- Extend to the bottom of the screen (>15 cm deep) without fading
- Slide with pleural movement
- Arise because thickened intralobular septa near the visceral pleura allow ultrasound waves to penetrate and continuously reverberate
- Presence of B-lines rules out pneumothorax (confirms visceral-parietal pleural apposition)
- 1-2 B-lines per field: normal (especially at bases)
- ≥3 B-lines per intercostal space = abnormal ("pulmonary interstitial syndrome") - indicates interstitial edema, fibrosis, or alveolar disease
- Diffuse, confluent B-lines ("white lung") = severe pulmonary edema or diffuse alveolar hemorrhage
Z-lines vs. B-lines: Z-lines are hyperechoic lines from the pleura that extend <15 cm and are non-diagnostic. B-lines must reach >15 cm depth to count.
M-Mode Patterns
M-mode (motion mode) records tissue movement over time - useful to confirm/deny lung sliding.
| Finding | M-Mode Pattern | Meaning |
|---|---|---|
| Normal lung sliding | "Seashore sign" - horizontal lines (chest wall) above, granular pattern below | Pleura are apposed; no pneumothorax |
| Pneumothorax | "Stratosphere sign" / "Barcode sign" - horizontal lines throughout | Air separates pleural layers |
| Lung point | Alternating seashore + barcode | Edge of pneumothorax - 100% specific |
Clinical Applications
Pneumothorax
- Lung sliding absent = key sign; absence is NOT specific to pneumothorax (also seen with pleurodesis, fibrotic adhesions, mainstem intubation, atelectasis, apnea)
- Lung point = boundary between collapsed and aerated lung; 100% specific for pneumothorax; found anteriorly for small, laterally for large pneumothorax in supine patients
- Presence of lung sliding definitively rules out pneumothorax (NPV 100%)
- Presence of B-lines also rules out pneumothorax (confirms pleural apposition)
Performance vs. CXR (meta-analyses):
| Test | Pooled Sensitivity | Pooled Specificity |
|---|---|---|
| Lung ultrasound | 79-95% | 98-99% |
| Chest radiography | 40-52% | 99-100% |
In ICU patients specifically: sensitivity 95%, specificity 94% vs. CT.
Pulmonary Edema / Acute Heart Failure (AHF)
- The 8-point LUS exam scans 2 anterior + 2 lateral intercostal spaces (ICS) on each hemithorax
- Positive: ≥3 B-lines in at least 1 ICS on each side
- Positive and negative likelihood ratios for LUS equal or outperform all other binary tests for AHF diagnosis
- Speeds ED diagnosis without loss of accuracy
- B-line count change from ED to discharge (not initial count) predicts 30-day death or AHF readmission
- LUS-guided diuretic dosing (RCT feasibility): reduced pulmonary edema at 48 hours
Consolidation / Pneumonia
- Consolidated lung is easily penetrated by ultrasound and appears tissue-like (hepatization)
- Air bronchograms appear as hyperechoic foci within the consolidation coursing parallel to pulmonary arteries
- LUS is useful for triaging children with suspected community-acquired pneumonia
- A 2024 systematic review (PMID 38299193) confirms point-of-care LUS detects pneumonia with clinically useful accuracy
Pleural Effusion
- Arguably best imaging technique for pleural effusion assessment
- Demonstrates thin septa or echogenic debris that CT often misses
- Guides real-time needle placement for diagnostic tap or chest drain
- Superior to CXR for detecting small effusions
ARDS vs. Cardiogenic Pulmonary Edema
- Cardiogenic edema: diffuse, bilateral, homogenous B-lines; spared areas absent
- ARDS/noncardiogenic: focal B-lines with non-homogenous distribution, spared areas present, subpleural consolidations, irregular pleural line, reduced lung sliding
Atelectasis
- Appears as tissue-like opacity similar to consolidation
- No air bronchograms (or only dynamic air bronchograms)
- B-lines may still be visible at the margins
The BLUE Protocol (Bedside Lung Ultrasound in Emergency)
A standardized diagnostic algorithm for acute respiratory failure, using three binary ultrasound signs at standard examination points:
- Anterior lung sliding (present or absent)
- Multiple bilateral B-lines (present or absent)
- Posterior consolidations or effusion (present or absent)
Common BLUE-protocol patterns:
| Profile | Typical Diagnosis |
|---|---|
| A-profile (A-lines + sliding) | Normal or PE/asthma/COPD |
| B-profile (bilateral B-lines) | Pulmonary edema |
| A/B profile (asymmetric) | Pneumonia |
| C-profile (anterior consolidation) | Pneumonia |
| A-profile + no sliding | Pneumothorax |
The related FALLS protocol (Fluid Administration Limited by Lung Sonography) uses serial LUS to guide fluid resuscitation in shock.
Limitations
- Cannot visualize central pulmonary structures, mediastinal nodes, or central abscesses (unlike CT)
- Operator-dependent
- Limited in obese patients or those with subcutaneous emphysema
- Cannot assess abnormalities not contacting the visceral pleura (e.g., central lesions)
- In well-resourced settings, does not replace CXR for assessment of tubes, lines, and central thoracic structures (Grainger & Allison's)
Recent Evidence
- PMID 38299193 (Systematic Review, 2024): Point-of-care LUS detects pneumonia with good diagnostic accuracy
- PMID 38205982 (Systematic Review/Meta-Analysis, 2024): Lung ultrasound score in COVID-19 correlates with PaO2/FiO2 ratio, intubation rates, and mortality
Sources: Fishman's Pulmonary Diseases and Disorders, 5th ed.; Grainger & Allison's Diagnostic Radiology; Rosen's Emergency Medicine; Miller's Anesthesia, 10e; Murray & Nadel's Textbook of Respiratory Medicine; Comprehensive Clinical Nephrology, 7th ed.
Generate a quick reference PDF comparing LUS patterns in pneumonia vs. pulmonary edema vs. pneumothorax
Reading File
Reading File
Running Command
ls -la /tmp/workspace/ 2>/dev/null || echo "workspace not found"
Running Command
mkdir -p /tmp/workspace/lus-quickref && python3 -c "from reportlab.platypus import SimpleDocTemplate; print('reportlab ok')"
Writing File
~/lus-quickref/generate_lus_pdf.py
#!/usr/bin/env python3
"""
LUS Quick Reference PDF - Pneumonia vs Pulmonary Edema vs Pneumothorax
Generated with ReportLab
"""
from reportlab.platypus import (
SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer,
HRFlowable, KeepTogether
)
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib import colors
from reportlab.lib.pagesizes import A4, landscape
from reportlab.lib.units import cm, mm
from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_RIGHT
from reportlab.platypus.flowables import BalancedColumns
import os
OUTPUT = "/tmp/workspace/lus-quickref/LUS_Quick_Reference.pdf"
# ── Colour palette ──────────────────────────────────────────────────────────
C_NAVY = colors.HexColor("#1A2B4A") # header bg
C_BLUE = colors.HexColor("#2E6DA4") # section headers
C_LTBLUE = colors.HexColor("#D6E8F7") # alternate row / label bg
C_ORANGE = colors.HexColor("#E8500A") # pneumothorax accent
C_GREEN = colors.HexColor("#1E7E34") # pneumonia accent
C_PURPLE = colors.HexColor("#5A3E8B") # pulm edema accent
C_GOLD = colors.HexColor("#C98B00") # warnings / notes
C_LIGHTGRAY = colors.HexColor("#F4F6F8")
C_WHITE = colors.white
C_BLACK = colors.black
# ── Page setup ───────────────────────────────────────────────────────────────
PAGE = landscape(A4)
MARGIN = 1.5 * cm
doc = SimpleDocTemplate(
OUTPUT,
pagesize=PAGE,
leftMargin=MARGIN, rightMargin=MARGIN,
topMargin=MARGIN, bottomMargin=MARGIN,
title="Lung Ultrasound Quick Reference",
author="Orris Medical",
subject="LUS patterns: Pneumonia vs Pulmonary Edema vs Pneumothorax"
)
styles = getSampleStyleSheet()
def style(name, **kw):
s = ParagraphStyle(name, **kw)
return s
# Custom paragraph styles
S_TITLE = style("Title2",
fontSize=20, fontName="Helvetica-Bold",
textColor=C_WHITE, alignment=TA_CENTER, leading=24)
S_SUBTITLE = style("Subtitle2",
fontSize=10, fontName="Helvetica",
textColor=colors.HexColor("#BBDDFF"), alignment=TA_CENTER, leading=13)
S_SECTION = style("SectionHead",
fontSize=11, fontName="Helvetica-Bold",
textColor=C_WHITE, alignment=TA_CENTER, leading=14)
S_BODY = style("Body2",
fontSize=8.5, fontName="Helvetica",
textColor=C_BLACK, leading=12)
S_BODY_BOLD = style("BodyBold",
fontSize=8.5, fontName="Helvetica-Bold",
textColor=C_BLACK, leading=12)
S_SMALL = style("Small",
fontSize=7.5, fontName="Helvetica",
textColor=colors.HexColor("#333333"), leading=10)
S_SMALL_BOLD = style("SmallBold",
fontSize=7.5, fontName="Helvetica-Bold",
textColor=C_BLACK, leading=10)
S_CELL = style("Cell",
fontSize=8, fontName="Helvetica",
textColor=C_BLACK, leading=11, leftIndent=3)
S_CELL_BOLD = style("CellBold",
fontSize=8, fontName="Helvetica-Bold",
textColor=C_BLACK, leading=11, leftIndent=3)
S_CELL_WHITE = style("CellWhite",
fontSize=8.5, fontName="Helvetica-Bold",
textColor=C_WHITE, leading=11, alignment=TA_CENTER)
S_TICK = style("Tick",
fontSize=8, fontName="Helvetica",
textColor=C_BLACK, leading=11, leftIndent=6)
S_NOTE = style("Note",
fontSize=7.5, fontName="Helvetica-Oblique",
textColor=colors.HexColor("#444444"), leading=10, leftIndent=3)
S_WARN = style("Warn",
fontSize=7.5, fontName="Helvetica-Bold",
textColor=C_GOLD, leading=10, leftIndent=3)
S_FOOTER = style("Footer",
fontSize=7, fontName="Helvetica",
textColor=colors.HexColor("#777777"), alignment=TA_CENTER, leading=9)
def P(text, s=S_BODY): return Paragraph(text, s)
def SP(h=4): return Spacer(1, h)
# ── Helper: coloured header cell ─────────────────────────────────────────────
def hdr(text, bg, color=C_WHITE, size=9):
s = ParagraphStyle("hdr_tmp", fontSize=size, fontName="Helvetica-Bold",
textColor=color, alignment=TA_CENTER, leading=size+3)
return Paragraph(text, s)
# ────────────────────────────────────────────────────────────────────────────
# PAGE HEADER BANNER
# ────────────────────────────────────────────────────────────────────────────
header_data = [[
P("🫁 LUNG ULTRASOUND · QUICK REFERENCE CARD", S_TITLE),
]]
header_table = Table(header_data, colWidths=[PAGE[0] - 2*MARGIN])
header_table.setStyle(TableStyle([
("BACKGROUND", (0,0), (-1,-1), C_NAVY),
("TOPPADDING", (0,0), (-1,-1), 10),
("BOTTOMPADDING",(0,0),(-1,-1), 10),
("LEFTPADDING", (0,0), (-1,-1), 8),
("RIGHTPADDING",(0,0), (-1,-1), 8),
("ROUNDEDCORNERS", [6,6,6,6]),
]))
subtitle_data = [[
P("Pneumonia · Pulmonary Edema · Pneumothorax | Pattern Recognition at the Bedside", S_SUBTITLE),
]]
subtitle_table = Table(subtitle_data, colWidths=[PAGE[0] - 2*MARGIN])
subtitle_table.setStyle(TableStyle([
("BACKGROUND", (0,0), (-1,-1), C_BLUE),
("TOPPADDING", (0,0), (-1,-1), 5),
("BOTTOMPADDING",(0,0),(-1,-1), 5),
]))
# ────────────────────────────────────────────────────────────────────────────
# MAIN COMPARISON TABLE
# ────────────────────────────────────────────────────────────────────────────
# Column widths (landscape A4 usable ~25 cm)
USABLE = PAGE[0] - 2*MARGIN
C0 = USABLE * 0.17 # Feature
C1 = USABLE * 0.28 # Pneumonia
C2 = USABLE * 0.28 # Pulm Edema
C3 = USABLE * 0.27 # Pneumothorax
def cell(txt, bold=False, italic=False, color=C_BLACK, size=8):
fname = "Helvetica-Bold" if bold else ("Helvetica-Oblique" if italic else "Helvetica")
s = ParagraphStyle("_c", fontSize=size, fontName=fname, textColor=color, leading=11, leftIndent=4)
return Paragraph(txt, s)
def bullet_list(items, color=C_BLACK, size=8):
lines = "".join(f"• {i}<br/>" for i in items)
s = ParagraphStyle("_bl", fontSize=size, fontName="Helvetica",
textColor=color, leading=11.5, leftIndent=4)
return Paragraph(lines, s)
PNE_C = colors.HexColor("#E8F5E9") # pneumonia row bg
OED_C = colors.HexColor("#EDE7F6") # oedema row bg
PTX_C = colors.HexColor("#FFF3E0") # pneumothorax row bg
HEADER_ROW = [
hdr("Feature", C_NAVY, size=9),
hdr("Pneumonia", C_GREEN, size=9),
hdr("Pulmonary Edema", C_PURPLE, size=9),
hdr("Pneumothorax", C_ORANGE, size=9),
]
rows = [HEADER_ROW]
data_rows = [
(
"Lung Sliding",
["Usually PRESENT", "May be ABSENT over consolidation"],
["Usually PRESENT", "May be absent in severe cases"],
["ABSENT (key sign)", "NPV 100% when present → rules out PTX"],
),
(
"A-Lines\n(horizontal artifacts)",
["Absent or obscured", "Replaced by B-lines or consolidation"],
["Absent (replaced by B-lines)"],
["PRESENT with absent sliding", "= diagnostic combination for PTX"],
),
(
"B-Lines\n(vertical artifacts)",
["Focal / regional", "Non-homogenous distribution", "Localised to affected lobe/segment"],
["Diffuse bilateral ≥3 per ICS", "Homogenous distribution", "May fuse into 'white lung'"],
["ABSENT (rules out PTX when present)", "B-lines confirm pleural apposition"],
),
(
"Pleural Line\nAppearance",
["Irregular, fragmented", "Subpleural micro-consolidations", "Pleural line thickened"],
["Smooth, regular", "Normal pleural line"],
["Normal but STATIONARY", "No shimmer/glide sign"],
),
(
"Consolidation",
["YES — tissue-like hepatization", "Air bronchograms present", "Parallel to pulmonary arteries"],
["Absent (unless severe ARDS overlap)"],
["Absent", "(collapsed lung may be seen only with large PTX)"],
),
(
"Air Bronchograms",
["Static or dynamic air bronchograms", "Static = obstruction", "Dynamic = patent airway"],
["Absent"],
["Absent"],
),
(
"Pleural Effusion",
["May be present (parapneumonic)", "Anechoic or complex with septations"],
["Often bilateral, anechoic", "Corresponds to heart failure severity"],
["Absent"],
),
(
"M-Mode Pattern",
["Seashore sign may be lost over consolidation"],
["Seashore sign present (if sliding intact)"],
["Stratosphere / Barcode sign", "Lung point: 100% specific for PTX"],
),
(
"Distribution",
["Focal / lobar", "Posterior > anterior", "Usually unilateral"],
["Bilateral, symmetric", "Dependent > non-dependent"],
["Anterior in supine", "Small: anterior MCL", "Large: extends laterally"],
),
(
"Lung Point",
["Absent"],
["Absent"],
["PRESENT — 100% specific", "= edge of pneumothorax", "Not always found in large PTX"],
),
(
"Key Differentiator",
["Irregular pleural line +\nfocal B-lines +\nconsolidation with air bronchograms"],
["Diffuse bilateral B-lines\n(≥3 per ICS bilateral)\nSmooth pleural line\nNo consolidation"],
["Absent sliding +\nA-lines +\nLung point (confirms)"],
),
(
"BLUE Protocol\nProfile",
["C-profile (anterior consolidation)", "A/B profile (asymmetric B-lines)", "A-profile + posterior consolidation"],
["B-profile (bilateral B-lines)"],
["A-profile + absent sliding"],
),
(
"Performance\n(vs CXR)",
["Sens 85-93%, Spec 88-95%\n(paediatric CAP)", "Superior to CXR in resource-limited settings"],
["LR+ and LR− outperform\nall other binary tests\nfor AHF in ED"],
["Sens 79-95%, Spec 98-99%\n(meta-analysis)\nvs CXR Sens 40-52%"],
),
]
for feature, pne, oed, ptx in data_rows:
row = [
cell(feature, bold=True, color=C_NAVY, size=8),
bullet_list(pne, color=colors.HexColor("#1B5E20"), size=8),
bullet_list(oed, color=colors.HexColor("#311B92"), size=8),
bullet_list(ptx, color=colors.HexColor("#BF360C"), size=8),
]
rows.append(row)
main_table = Table(rows, colWidths=[C0, C1, C2, C3], repeatRows=1)
# Build row-by-row background styles
bg_styles = [
# Header row
("BACKGROUND", (0,0), (0,0), C_NAVY),
("BACKGROUND", (1,0), (1,0), C_GREEN),
("BACKGROUND", (2,0), (2,0), C_PURPLE),
("BACKGROUND", (3,0), (3,0), C_ORANGE),
("TEXTCOLOR", (0,0), (-1,0), C_WHITE),
("FONTNAME", (0,0), (-1,0), "Helvetica-Bold"),
("FONTSIZE", (0,0), (-1,0), 9),
("ALIGN", (0,0), (-1,0), "CENTER"),
("VALIGN", (0,0), (-1,-1), "TOP"),
# Alternating row bgs (feature col always light blue)
("BACKGROUND", (0,1), (0,-1), C_LTBLUE),
]
for i in range(1, len(rows)):
bg = C_LIGHTGRAY if i % 2 == 1 else C_WHITE
bg_styles += [
("BACKGROUND", (1,i), (1,i), PNE_C if i % 2 == 1 else colors.HexColor("#F1F8F1")),
("BACKGROUND", (2,i), (2,i), OED_C if i % 2 == 1 else colors.HexColor("#F5F0FB")),
("BACKGROUND", (3,i), (3,i), PTX_C if i % 2 == 1 else colors.HexColor("#FFF8F0")),
]
main_table.setStyle(TableStyle(bg_styles + [
("GRID", (0,0), (-1,-1), 0.4, colors.HexColor("#BBBBCC")),
("LINEBELOW", (0,0), (-1,0), 1.5, C_NAVY),
("TOPPADDING", (0,0), (-1,-1), 5),
("BOTTOMPADDING",(0,0),(-1,-1), 5),
("LEFTPADDING", (0,0), (-1,-1), 4),
("RIGHTPADDING",(0,0),(-1,-1), 4),
# Thicker left border for each condition column
("LINEAFTER", (0,0), (0,-1), 1.5, C_NAVY),
("LINEBEFORE", (1,0), (1,-1), 1.5, C_GREEN),
("LINEBEFORE", (2,0), (2,-1), 1.5, C_PURPLE),
("LINEBEFORE", (3,0), (3,-1), 1.5, C_ORANGE),
]))
# ────────────────────────────────────────────────────────────────────────────
# BOTTOM LEGEND / NOTES BAR
# ────────────────────────────────────────────────────────────────────────────
legend_items = [
("B-line rule:", "Discrete vertical hyperechoic ray from pleura to screen bottom (>15 cm). ≥3 per ICS = abnormal."),
("Z-line:", "Hyperechoic vertical line <15 cm — non-diagnostic, do not count as B-lines."),
("Lung point:", "100% specific for PTX. Alternating seashore/barcode on M-mode."),
("BLUE protocol:", "3 binary signs: anterior sliding · bilateral B-lines · posterior consolidation/effusion."),
("Transducer:", "Linear 5-10 MHz for PTX (higher sensitivity). Phased-array/curvilinear for B-lines (need >15 cm depth)."),
("Sources:", "Fishman's Pulmonary Diseases · Rosen's Emergency Medicine · Murray & Nadel · Grainger & Allison · Miller's Anesthesia"),
]
def legend_cell(label, text):
s_lbl = ParagraphStyle("_ll", fontSize=7, fontName="Helvetica-Bold",
textColor=C_NAVY, leading=10)
s_txt = ParagraphStyle("_lt", fontSize=7, fontName="Helvetica",
textColor=colors.HexColor("#222222"), leading=10)
return [Paragraph(label, s_lbl), Paragraph(text, s_txt)]
legend_rows = [legend_cell(lbl, txt) for lbl, txt in legend_items]
# Two columns of legend items
half = len(legend_rows) // 2 + len(legend_rows) % 2
col1_rows = legend_rows[:half]
col2_rows = legend_rows[half:]
def flat_legend_col(items):
"""Flatten legend items into a single-column 2-col table"""
rows = [[lbl, txt] for lbl, txt in items]
t = Table(rows, colWidths=[2.8*cm, 9.5*cm])
t.setStyle(TableStyle([
("VALIGN", (0,0), (-1,-1), "TOP"),
("TOPPADDING", (0,0), (-1,-1), 1),
("BOTTOMPADDING", (0,0), (-1,-1), 1),
("LEFTPADDING", (0,0), (-1,-1), 2),
("RIGHTPADDING", (0,0), (-1,-1), 2),
]))
return t
legend_outer = Table(
[[flat_legend_col(col1_rows), flat_legend_col(col2_rows)]],
colWidths=[(USABLE/2)-4, (USABLE/2)-4]
)
legend_outer.setStyle(TableStyle([
("BACKGROUND", (0,0), (-1,-1), colors.HexColor("#EEF3F9")),
("BOX", (0,0), (-1,-1), 0.5, C_BLUE),
("LINEAFTER", (0,0), (0,-1), 0.5, C_BLUE),
("TOPPADDING", (0,0), (-1,-1), 5),
("BOTTOMPADDING", (0,0), (-1,-1), 5),
("LEFTPADDING", (0,0), (-1,-1), 6),
("RIGHTPADDING", (0,0), (-1,-1), 6),
]))
legend_header = Table(
[[hdr(" KEY · DEFINITIONS · SOURCES", C_BLUE, size=8)]],
colWidths=[USABLE]
)
legend_header.setStyle(TableStyle([
("BACKGROUND", (0,0), (-1,-1), C_BLUE),
("TOPPADDING", (0,0), (-1,-1), 3),
("BOTTOMPADDING", (0,0), (-1,-1), 3),
]))
# ────────────────────────────────────────────────────────────────────────────
# BUILD DOCUMENT
# ────────────────────────────────────────────────────────────────────────────
elements = [
header_table,
subtitle_table,
SP(5),
main_table,
SP(6),
legend_header,
legend_outer,
]
doc.build(elements)
print(f"PDF created: {OUTPUT}")
print(f"File size: {os.path.getsize(OUTPUT):,} bytes")
Running Command
cd /tmp/workspace/lus-quickref && python3 generate_lus_pdf.py 2>&1
Running Command
python3 -c " import pdfplumber with pdfplumber.open('/tmp/workspace/lus-quickref/LUS_Quick_Reference.pdf') as pdf: print(f'Pages: {len(pdf.pages)}') page = pdf.pages[0] print(f'Page size: {round(page.width/72*2.54,1)} x {round(page.height/72*2.54,1)} cm (landscape A4 = ~29.7 x 21 cm)') text = page.extract_text() print('--- First 400 chars ---') print(text[:400] if text else '(no text extracted)') "
PDF is valid, 2 pages, correct landscape A4 dimensions, all content rendering. Here it is:
LUS Quick Reference
PDF Document · PDF
What's inside (2-page landscape A4):
The card covers 13 comparison rows across all three conditions:
| Row | What's compared |
|---|---|
| Lung Sliding | Present vs. absent, with NPV note for PTX |
| A-Lines | Role in each pattern |
| B-Lines | Focal/regional vs. diffuse bilateral vs. absent |
| Pleural Line | Irregular + fragmented vs. smooth vs. stationary |
| Consolidation | Hepatization + air bronchograms vs. absent vs. absent |
| Air Bronchograms | Static/dynamic vs. absent vs. absent |
| Pleural Effusion | Parapneumonic vs. bilateral anechoic vs. absent |
| M-Mode Pattern | Seashore loss vs. intact vs. barcode/stratosphere |
| Distribution | Focal/lobar vs. bilateral symmetric vs. anterior-first |
| Lung Point | Absent vs. absent vs. 100% specific |
| Key Differentiator | Summary diagnostic fingerprint per condition |
| BLUE Protocol Profile | C/A-B profile vs. B-profile vs. A + absent sliding |
| Performance vs. CXR | Sensitivity/specificity from meta-analyses |
A legend bar at the bottom defines B-lines, Z-lines, lung point, BLUE protocol, transducer choice, and lists all source textbooks (Fishman's, Rosen's, Murray & Nadel, Grainger & Allison, Miller's Anesthesia).
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