TANAKA INDEX CT SCAN OF INCISIONAL HENIA

TANAKA INDEX CT SCAN OF INCISIONAL HENIA\

Reading File

The Tanaka Index is a CT-based scoring system used to predict mesh size and assess the complexity of incisional hernia repair. It measures the ratio of the hernia sac volume to the total abdominal cavity volume on CT scan. Let me pull textbook and literature details simultaneously.

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Tanaka index incisional hernia CT scan

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Tanaka index CT scan incisional hernia formula calculation significance

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Tanaka index CT scan incisional hernia loss of domain volumetry

Reading Web Page

https://www.frontierspartnerships.org/journals/journal-of-ab…

Here is a detailed overview of the Tanaka Index in the context of CT scan assessment of incisional hernias:

Tanaka Index - CT Scan Assessment of Incisional Hernia

Background

The Tanaka Index was introduced by Tanaka EY et al. (2010) in the journal Hernia as a CT-based volumetric method to quantify Loss of Domain (LOD) in complex large incisional hernias. The original paper is: "A computerized tomography scan method for calculating the hernia sac and abdominal cavity volume in complex large incisional hernia with loss of domain." Hernia 14:63-69.

What is Loss of Domain (LOD)?

Loss of domain refers to the condition where a significant portion of the abdominal viscera has herniated out of the abdominal cavity and can no longer be safely returned without risking abdominal compartment syndrome (ACS). The larger the hernia relative to the total abdominal volume, the greater the LOD.

The Tanaka Index Formula

Tanaka Index (TI) = HSV / ACV

Term	Definition
HSV	Hernia Sac Volume
ACV	Abdominal Cavity Volume

Both volumes are measured from CT scan using the ellipsoid volume formula:

V = (π/6) × L × W × H

Where L, W, and H are the three orthogonal diameters (longitudinal, transverse, anteroposterior) of the structure, measured in centimeters on CT.

Abdominal Cavity: measured from the diaphragm superiorly to the pelvic floor inferiorly, bounded laterally by the abdominal wall
Hernia Sac: measured from the neck of the defect to the outermost extent of the sac

Threshold and Clinical Significance

Tanaka Index Value	Interpretation
< 0.25	No significant loss of domain; standard repair feasible
> 0.25	Loss of domain hernia; complex repair required
0.25 - 0.30	Mild LOD - TAR (Transversus Abdominis Release) alone
0.31 - 0.35	Moderate LOD - TAR + peritoneal flap reinforcement
> 0.35	Severe LOD - preoperative preparation required (Botulinum toxin + Progressive Pneumoperitoneum), then TAR + peritoneal flap

Surgical Decision-Making Algorithm (Tanaka Index-based)

CT Abdomen
     |
  Calculate TI = HSV / ACV
     |
  TI < 0.25 ─────────────────────────────────┐
     |                                         |
  TI > 0.25 (Loss of Domain)           Defect size guides:
     |                                    <12cm: Onlay mesh
     ├── 0.25-0.30: TAR alone             >12cm: TAR + retrorectus mesh
     |
     ├── 0.31-0.35: TAR + peritoneal flap
     |
     └── >0.35: BT injections + PPP (Days 1-24)
                  → Surgery Day 24-30
                  → TAR + peritoneal flap

Why CT Scan?

CT (preferably with Valsalva maneuver) provides:

Volumetric measurements of the hernia sac and abdominal cavity
Defect width and location (EHS classification)
Hernia contents (bowel, omentum, solid organs)
Prior mesh position, integrity, migration, or infection
Associated hernias (inguinal, parastomal)
Condition of abdominal wall muscles (atrophy, diastasis recti)

In a 2026 multi-criteria survey of 61 abdominal wall reconstruction specialists, the Tanaka Index was ranked 6th most important CT parameter out of 16, with a mean clinical relevance score of 8.45/10 - Hernia journal survey.

Comparison: Tanaka vs. Sabbagh Method

Feature	Tanaka Method	Sabbagh Method
Formula	HSV / ACV	HSV / (ACV + HSV)
LOD threshold	> 0.25	> 20%
Volume method	Ellipsoid formula	Semi-automated volumetry
Posterior ACV boundary	Anterior aspect of vertebral body	Anterior aspect of vertebral body
Complexity	Simple, manual	More precise, semi-automated

Both methods yield closely correlated hernia sac volumes (r = 0.91).

Clinical Implications

A TI > 0.25 signals that forceful visceral reduction will raise intra-abdominal pressure (IAP) dangerously
Preoperative Botulinum toxin (BT) injections into the lateral abdominal wall muscles cause temporary paralysis and lateral abdominal wall elongation, increasing functional abdominal volume
Progressive Pneumoperitoneum (PPP) gradually re-expands the abdominal cavity to accommodate the herniated contents
These measures, guided by the Tanaka Index severity, reduce the risk of ACS postoperatively and enable safe fascial closure

Key Reference

Tanaka EY, Yoo JH, Rodrigues AJ Jr, Utiyama EM, Birolini D, Rasslan S (2010). A computerized tomography scan method for calculating the hernia sac and abdominal cavity volume in complex large incisional hernia with loss of domain. Hernia, 14:63-69.

PRIVED IMAGES GOW TO MEASURES HSV AND ACV

Let me search for actual CT scan images showing how to measure HSV and ACV for the Tanaka Index.

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CT scan hernia sac volume abdominal cavity volume measurement Tanaka index

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Tanaka index CT scan how to measure HSV ACV hernia sac abdominal cavity volume images diagrams

Found original Tanaka paper images. Let me fetch them all now.

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Excellent - got two real CT scan examples directly from an ECR 2025 radiology poster. Also pulling a YouTube video that visually demonstrates the measurement technique.

How to Measure HSV and ACV on CT Scan - Tanaka Index

The Core Principle

Both the hernia sac and the abdominal cavity are treated as ellipsoids on CT. You measure 3 diameters of each and plug them into:

Volume = 0.52 × a × b × c

Where a = cranio-caudal (CC), b = transverse (latero-lateral), c = anteroposterior (AP)

CASE 1 - Moderate Loss of Domain

What the arrows show:

Pink arrows (ACV measurements): Axial slice shows ACV transverse = 17.9 cm (top left); ACV AP = measured in sagittal; ACV cranio-caudal = 34.2 cm (sagittal, right panel)
Green arrows (HSV measurements): Hernia sac CC = 15.1 cm, AP = 6.5 cm (sagittal, middle); HSV transverse = 20.5 cm (axial, bottom middle)
Yellow dashed lines = cranial and caudal limits of the abdominal cavity

Result:

HSV = 1046 mL
ACV = 9454.4 mL
LOD = 1046 / 9454.4 = 0.11 (<25%) - No loss of domain

CASE 2 - Massive Loss of Domain

What the arrows show:

Pink arrows = ACV measurements (axial and sagittal)
Green arrows = HSV measurements (axial for transverse + AP; sagittal for cranio-caudal)
Yellow dashed lines = cranial/caudal limits of ACV on sagittal view

Result:

HSV = 7819 mL
ACV = 7003 mL
LOD = 7819 / 7003 = >25% (>1.0) - Massive loss of domain

Step-by-Step Measurement Protocol

STEP 1 - Identify the Landmarks

Structure	Cranial limit	Caudal limit	Anterior limit	Posterior limit
ACV	First slice showing diaphragm	Last slice showing coccyx	Line joining healthy anterior muscle groups	Line through transverse processes of vertebrae
HSV	Parietal peritoneum of sac (cranial)	Parietal peritoneum of sac (caudal)	Outer skin/sac wall	Same posterior line as ACV

STEP 2 - Measure 3 Diameters on CT

On axial slices - measure the widest transverse (b) and AP (c) diameters of each ellipsoid

On sagittal slices - measure the cranio-caudal (a) height of each ellipsoid

Always take the largest single measurement across all slices - do not average; use the maximum diameter found anywhere in the scan.

STEP 3 - Apply Ellipsoid Formula

HSV (mL) = 0.52 × a(CC) × b(Transverse) × c(AP)
ACV (mL) = 0.52 × A(CC) × B(Transverse) × C(AP)

STEP 4 - Calculate Tanaka Index

Tanaka Index = HSV / ACV

< 0.25  → No LOD → Standard repair
0.25-0.30 → LOD → TAR technique
0.31-0.35 → LOD → TAR + peritoneal flap
> 0.35  → Severe LOD → Botox + PPP preoperatively, then TAR

Video Demonstration

This YouTube video walks through the actual CT measurements for both Tanaka and Sabbagh methods with real cases:

Watch "https://www.youtube.com/watch?v=b2vhoKVhOAQ" on YouTube

https://www.youtube.com/watch?v=b2vhoKVhOAQ

Key Points to Remember

Pink/magenta arrows on CT = ACV measurements; Green arrows = HSV measurements (this is the standard color convention used in teaching material)
The yellow dashed lines mark the cranial and caudal limits of the abdominal cavity on sagittal view
The ACV's posterior boundary passes through the transverse processes of vertebrae - NOT the anterior vertebral body (that is the Sabbagh method's boundary)
The formula constant 0.52 comes from simplifying (4/3 × π × r1 × r2 × r3) when using full diameters instead of radii: 4/3 × π × 1/8 ≈ 0.5236 ≈ 0.52
CT with Valsalva maneuver is preferred as it maximally distends the hernia sac, giving a more accurate HSV

Make ppt from this data

Reading File

Running Command

mkdir -p /tmp/workspace/tanaka-pptx && python /tmp/skills/shared/scripts/fetch_images.py "https://epos.myesr.org/posterimage/esr/ecr2025/167480/media/993460" "https://epos.myesr.org/posterimage/esr/ecr2025/167480/media/993461" 2>/dev/null | python3 -c " import json, base64, sys data = json.load(sys.stdin) for i, img in enumerate(data): if img.get('base64'): raw = base64.b64decode(img['base64'].split(',')[1] if ',' in img['base64'] else img['base64']) with open(f'/tmp/workspace/tanaka-pptx/ct_image_{i+1}.jpg', 'wb') as f: f.write(raw) print(f'Saved ct_image_{i+1}.jpg, size={len(raw)}') else: print(f'Image {i+1} failed: {img.get(\"error\")}') "

Both CT images downloaded. Now writing the full presentation script.

Writing File

~/tanaka-pptx/build_pptx.py

from pptx import Presentation
from pptx.util import Inches, Pt, Emu
from pptx.dml.color import RGBColor
from pptx.enum.text import PP_ALIGN, MSO_ANCHOR
from pptx.util import Inches, Pt
from io import BytesIO
import copy

# ── Palette ──────────────────────────────────────────────────────────────────
DARK_BLUE   = RGBColor(0x0D, 0x2B, 0x55)   # slide backgrounds / header bar
MID_BLUE    = RGBColor(0x1A, 0x5F, 0x9E)   # accent / subtitle bar
ACCENT_GOLD = RGBColor(0xF0, 0xC4, 0x2F)   # key highlight
WHITE       = RGBColor(0xFF, 0xFF, 0xFF)
LIGHT_GREY  = RGBColor(0xF2, 0xF4, 0xF8)
TEXT_DARK   = RGBColor(0x1A, 0x1A, 0x2E)
GREEN       = RGBColor(0x27, 0xAE, 0x60)
RED         = RGBColor(0xC0, 0x39, 0x2B)
ORANGE      = RGBColor(0xE6, 0x7E, 0x22)

prs = Presentation()
prs.slide_width  = Inches(13.333)
prs.slide_height = Inches(7.5)
blank = prs.slide_layouts[6]

# ── Helper functions ─────────────────────────────────────────────────────────

def add_rect(slide, x, y, w, h, fill_color, alpha=None):
    from pptx.util import Inches
    shape = slide.shapes.add_shape(1, Inches(x), Inches(y), Inches(w), Inches(h))
    shape.fill.solid()
    shape.fill.fore_color.rgb = fill_color
    shape.line.fill.background()
    return shape

def add_text(slide, text, x, y, w, h, size=18, bold=False, color=WHITE,
             align=PP_ALIGN.LEFT, italic=False, wrap=True, valign=MSO_ANCHOR.TOP):
    tb = slide.shapes.add_textbox(Inches(x), Inches(y), Inches(w), Inches(h))
    tf = tb.text_frame
    tf.word_wrap = wrap
    tf.vertical_anchor = valign
    tf.margin_left  = Pt(0)
    tf.margin_right = Pt(0)
    tf.margin_top   = Pt(0)
    tf.margin_bottom= Pt(0)
    p = tf.paragraphs[0]
    p.alignment = align
    r = p.add_run()
    r.text = text
    r.font.size   = Pt(size)
    r.font.bold   = bold
    r.font.italic = italic
    r.font.color.rgb = color
    r.font.name   = "Calibri"
    return tb

def add_multiline(slide, lines, x, y, w, h, size=16, color=WHITE,
                  bold_first=False, line_spacing=1.15, align=PP_ALIGN.LEFT):
    """lines = list of (text, bold, color_override_or_None)"""
    tb = slide.shapes.add_textbox(Inches(x), Inches(y), Inches(w), Inches(h))
    tf = tb.text_frame
    tf.word_wrap = True
    tf.margin_left = tf.margin_right = tf.margin_top = tf.margin_bottom = Pt(2)
    from pptx.oxml.ns import qn
    from lxml import etree
    for i, (txt, bold, col) in enumerate(lines):
        p = tf.paragraphs[0] if i == 0 else tf.add_paragraph()
        p.alignment = align
        # line spacing
        p.line_spacing = line_spacing
        r = p.add_run()
        r.text = txt
        r.font.size  = Pt(size)
        r.font.bold  = bold
        r.font.color.rgb = col if col else color
        r.font.name  = "Calibri"
    return tb

def bg(slide, color=DARK_BLUE):
    add_rect(slide, 0, 0, 13.333, 7.5, color)

def header_bar(slide, title, subtitle=None):
    add_rect(slide, 0, 0, 13.333, 1.1, DARK_BLUE)
    add_rect(slide, 0, 1.1, 13.333, 0.07, ACCENT_GOLD)
    add_text(slide, title, 0.35, 0.08, 12.5, 0.8,
             size=28, bold=True, color=WHITE, align=PP_ALIGN.LEFT, valign=MSO_ANCHOR.MIDDLE)
    if subtitle:
        add_text(slide, subtitle, 0.35, 0.82, 12, 0.35,
                 size=13, bold=False, color=ACCENT_GOLD, align=PP_ALIGN.LEFT)

def slide_number(slide, n, total):
    add_text(slide, f"{n} / {total}", 12.6, 7.15, 0.7, 0.3,
             size=10, color=RGBColor(0xAA, 0xAA, 0xAA), align=PP_ALIGN.RIGHT)

# ── Build slides ─────────────────────────────────────────────────────────────
TOTAL = 10

# ─────────────────────────────────────────────────────────────────
# SLIDE 1 – Title
# ─────────────────────────────────────────────────────────────────
s = prs.slides.add_slide(blank)
bg(s, DARK_BLUE)
# decorative diagonal band
add_rect(s, 0, 5.5, 13.333, 2.0, MID_BLUE)
add_rect(s, 0, 5.47, 13.333, 0.08, ACCENT_GOLD)

add_text(s, "TANAKA INDEX", 1.0, 1.3, 11.5, 1.5,
         size=52, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
add_text(s, "CT Scan Assessment of Incisional Hernia", 1.0, 2.9, 11.5, 0.8,
         size=26, bold=False, color=ACCENT_GOLD, align=PP_ALIGN.CENTER)
add_text(s, "Loss of Domain  |  Volumetric Measurement  |  Surgical Planning",
         1.0, 3.7, 11.5, 0.6,
         size=16, bold=False, italic=True,
         color=RGBColor(0xBB, 0xCC, 0xEE), align=PP_ALIGN.CENTER)
add_text(s, "Tanaka EY et al. Hernia 2010; 14:63-69",
         1.0, 5.7, 11.5, 0.5,
         size=13, color=RGBColor(0xCC, 0xCC, 0xCC), align=PP_ALIGN.CENTER)
slide_number(s, 1, TOTAL)

# ─────────────────────────────────────────────────────────────────
# SLIDE 2 – What is Loss of Domain?
# ─────────────────────────────────────────────────────────────────
s = prs.slides.add_slide(blank)
bg(s, LIGHT_GREY)
header_bar(s, "What is Loss of Domain (LOD)?",
           "The clinical problem that the Tanaka Index solves")

# Left panel – definition box
add_rect(s, 0.35, 1.3, 5.8, 5.6, DARK_BLUE)
add_rect(s, 0.35, 1.3, 5.8, 0.55, MID_BLUE)
add_text(s, "DEFINITION", 0.55, 1.32, 5.4, 0.5,
         size=14, bold=True, color=ACCENT_GOLD, align=PP_ALIGN.LEFT, valign=MSO_ANCHOR.MIDDLE)

defn_lines = [
    ("Loss of domain occurs when herniated viscera can NO", False, None),
    ("longer be safely returned to the abdominal cavity", False, None),
    ("", False, None),
    ("The hernia sac has effectively become part of the", False, None),
    ("'functional abdominal domain'", True, ACCENT_GOLD),
    ("", False, None),
    ("Forceful reduction raises intra-abdominal pressure", False, None),
    ("(IAP) dangerously → risk of Abdominal Compartment", False, None),
    ("Syndrome (ACS)", True, RGBColor(0xFF, 0x88, 0x88)),
]
add_multiline(s, defn_lines, 0.5, 2.0, 5.5, 4.8, size=15, color=WHITE)

# Right panel – consequences
add_rect(s, 6.5, 1.3, 6.5, 5.6, WHITE)
add_rect(s, 6.5, 1.3, 6.5, 0.55, RED)
add_text(s, "WHY IT MATTERS", 6.7, 1.32, 6.0, 0.5,
         size=14, bold=True, color=WHITE, align=PP_ALIGN.LEFT, valign=MSO_ANCHOR.MIDDLE)

conseq = [
    ("Respiratory compromise post-reduction", True, RED),
    ("  - Diaphragmatic elevation reduces FRC", False, TEXT_DARK),
    ("  - Risk of ventilatory failure", False, TEXT_DARK),
    ("", False, None),
    ("Cardiovascular compromise", True, RED),
    ("  - IVC compression → reduced venous return", False, TEXT_DARK),
    ("", False, None),
    ("Bowel ischemia / abdominal compartment syndrome", True, RED),
    ("", False, None),
    ("Wound closure under tension → recurrence", True, RED),
    ("", False, None),
    ("Pre-operative preparation is MANDATORY", True, MID_BLUE),
    ("  when LOD is identified on CT", False, TEXT_DARK),
]
add_multiline(s, conseq, 6.6, 2.0, 6.2, 4.8, size=13.5, color=TEXT_DARK)
slide_number(s, 2, TOTAL)

# ─────────────────────────────────────────────────────────────────
# SLIDE 3 – The Tanaka Formula
# ─────────────────────────────────────────────────────────────────
s = prs.slides.add_slide(blank)
bg(s, LIGHT_GREY)
header_bar(s, "The Tanaka Index Formula", "Objective CT-based quantification of loss of domain")

# Big formula box
add_rect(s, 1.0, 1.3, 11.333, 1.6, DARK_BLUE)
add_text(s, "Tanaka Index  =  HSV  ÷  ACV", 1.0, 1.35, 11.333, 1.5,
         size=38, bold=True, color=ACCENT_GOLD, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)

# Three columns: HSV | ACV | Volume formula
col_w = 3.6
for i, (title, body, col_color) in enumerate([
    ("HSV", "Hernia Sac Volume\n\nMeasured from the neck of\nthe defect to the outermost\nextent of the hernial sac", MID_BLUE),
    ("ACV", "Abdominal Cavity Volume\n\nMeasured from diaphragm\n(cranially) to coccyx\n(caudally)", GREEN),
    ("Volume Formula", "V = 0.52 × a × b × c\n\na = cranio-caudal (CC)\nb = transverse (latero-lateral)\nc = anteroposterior (AP)\n\n0.52 = π/6 ≈ simplified", ORANGE),
]):
    x = 0.35 + i * (col_w + 0.22)
    add_rect(s, x, 3.1, col_w, 0.55, col_color)
    add_text(s, title, x, 3.12, col_w, 0.5,
             size=16, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
    add_rect(s, x, 3.65, col_w, 3.5, WHITE)
    add_text(s, body, x + 0.1, 3.75, col_w - 0.2, 3.3,
             size=14, bold=False, color=TEXT_DARK, align=PP_ALIGN.LEFT, wrap=True)

# Threshold callout
add_rect(s, 4.5, 6.9, 4.333, 0.5, ACCENT_GOLD)
add_text(s, "Threshold: TI > 0.25 = Loss of Domain", 4.5, 6.9, 4.333, 0.5,
         size=14, bold=True, color=DARK_BLUE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
slide_number(s, 3, TOTAL)

# ─────────────────────────────────────────────────────────────────
# SLIDE 4 – CT Landmarks: ACV
# ─────────────────────────────────────────────────────────────────
s = prs.slides.add_slide(blank)
bg(s, LIGHT_GREY)
header_bar(s, "CT Landmarks: Abdominal Cavity Volume (ACV)",
           "Pink/Magenta arrows on CT = ACV measurements")

# Info boxes left
landmarks = [
    ("CRANIAL LIMIT", "First axial slice showing the diaphragm", MID_BLUE),
    ("CAUDAL LIMIT",  "Last axial slice showing the coccyx", MID_BLUE),
    ("ANTERIOR LIMIT","Line joining the healthy anterior muscle groups\n(not the skin / subcutaneous fat)", GREEN),
    ("POSTERIOR LIMIT","Line through the TRANSVERSE PROCESSES\nof the vertebrae\n(NOT the anterior vertebral body)", ORANGE),
    ("LATERAL LIMITS", "Parietal peritoneum on each side\nof the abdominal cavity", MID_BLUE),
]
box_h = 0.95
for i, (lbl, desc, col) in enumerate(landmarks):
    y = 1.35 + i * (box_h + 0.07)
    add_rect(s, 0.3, y, 2.1, box_h, col)
    add_text(s, lbl, 0.3, y, 2.1, box_h,
             size=11, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
    add_rect(s, 2.4, y, 4.5, box_h, WHITE)
    add_text(s, desc, 2.5, y + 0.05, 4.3, box_h - 0.1,
             size=12, bold=False, color=TEXT_DARK, wrap=True)

# Diagram schematic right
add_rect(s, 7.3, 1.3, 5.7, 5.9, WHITE)
add_rect(s, 7.3, 1.3, 5.7, 0.45, DARK_BLUE)
add_text(s, "SAGITTAL VIEW – ACV Boundaries", 7.3, 1.3, 5.7, 0.45,
         size=12, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)

diagram_lines = [
    ("─── Diaphragm (CRANIAL limit) ───", False, MID_BLUE),
    ("", False, None),
    ("     |  ←── Anterior wall", False, GREEN),
    ("     |        (muscle line)", False, GREEN),
    ("     |", False, TEXT_DARK),
    ("  A  |  ← Abdominal    → |  Vertebra", False, TEXT_DARK),
    ("  C  |    Cavity (ACV)   |  (Posterior)", False, TEXT_DARK),
    ("  V  |                   |  limit =", False, TEXT_DARK),
    ("     |                   |  Transverse", False, ORANGE),
    ("     |                   |  process", False, ORANGE),
    ("", False, None),
    ("─── Coccyx (CAUDAL limit) ───", False, MID_BLUE),
    ("", False, None),
    ("Measure: CC (a) × Transverse (b) × AP (c)", True, DARK_BLUE),
    ("ACV = 0.52 × a × b × c", True, MID_BLUE),
]
add_multiline(s, diagram_lines, 7.4, 1.85, 5.5, 5.3, size=12, color=TEXT_DARK)
slide_number(s, 4, TOTAL)

# ─────────────────────────────────────────────────────────────────
# SLIDE 5 – CT Landmarks: HSV
# ─────────────────────────────────────────────────────────────────
s = prs.slides.add_slide(blank)
bg(s, LIGHT_GREY)
header_bar(s, "CT Landmarks: Hernia Sac Volume (HSV)",
           "Green arrows on CT = HSV measurements")

hsv_lm = [
    ("CRANIAL LIMIT",  "Parietal peritoneum of the hernia sac\nat its cranial extent (defect neck)", GREEN),
    ("CAUDAL LIMIT",   "Parietal peritoneum of the hernia sac\nat its most caudal point", GREEN),
    ("ANTERIOR LIMIT", "Outer wall of hernia sac\n(parietal peritoneum / subcutaneous tissue)", GREEN),
    ("POSTERIOR LIMIT","SAME LINE as ACV posterior limit\n(transverse processes of vertebrae)\n→ ensures no double-counting", ORANGE),
    ("LATERAL LIMITS", "Parietal peritoneum of the hernia\nsac on each side", GREEN),
    ("KEY RULE",       "Take the LARGEST measurement from any\nCT slice — do NOT average. Use maximum\ndiameter found across the entire scan.", RED),
]
box_h = 0.9
for i, (lbl, desc, col) in enumerate(hsv_lm):
    y = 1.35 + i * (box_h + 0.06)
    add_rect(s, 0.3, y, 2.1, box_h, col)
    add_text(s, lbl, 0.3, y, 2.1, box_h,
             size=11, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
    add_rect(s, 2.4, y, 4.9, box_h, WHITE)
    add_text(s, desc, 2.5, y + 0.05, 4.7, box_h - 0.1,
             size=12, bold=False, color=TEXT_DARK, wrap=True)

# Right panel
add_rect(s, 7.7, 1.3, 5.3, 5.9, DARK_BLUE)
add_rect(s, 7.7, 1.3, 5.3, 0.45, GREEN)
add_text(s, "STEP-BY-STEP MEASUREMENT", 7.7, 1.3, 5.3, 0.45,
         size=12, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
steps = [
    ("STEP 1", "On AXIAL slices:", "Measure widest TRANSVERSE (b) and\nAP (c) diameters of hernia sac", GREEN),
    ("STEP 2", "On SAGITTAL slices:", "Measure CRANIO-CAUDAL (a)\nheight of hernia sac", GREEN),
    ("STEP 3", "Apply formula:", "HSV = 0.52 × a × b × c", ACCENT_GOLD),
    ("STEP 4", "Repeat for ACV:", "Same process using ACV landmarks\nACV = 0.52 × A × B × C", MID_BLUE),
    ("STEP 5", "Calculate TI:", "TI = HSV / ACV\n> 0.25 = Loss of Domain", RED),
]
y0 = 1.95
for snum, slbl, sdesc, col in steps:
    add_rect(s, 7.8, y0, 0.75, 0.72, col)
    add_text(s, snum, 7.8, y0, 0.75, 0.72,
             size=10, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
    add_text(s, slbl, 8.65, y0, 1.5, 0.3,
             size=11, bold=True, color=ACCENT_GOLD)
    add_text(s, sdesc, 8.65, y0 + 0.3, 4.1, 0.5,
             size=11, color=WHITE, wrap=True)
    y0 += 0.88
slide_number(s, 5, TOTAL)

# ─────────────────────────────────────────────────────────────────
# SLIDE 6 – CT Image Case 1 (moderate LOD)
# ─────────────────────────────────────────────────────────────────
s = prs.slides.add_slide(blank)
bg(s, RGBColor(0x10, 0x10, 0x10))
header_bar(s, "CT Case 1: Moderate Incisional Hernia (TI < 0.25)",
           "Pink arrows = ACV measurements  |  Green arrows = HSV measurements")

# Insert CT image
s.shapes.add_picture("/tmp/workspace/tanaka-pptx/ct_image_1.jpg",
                     Inches(0.25), Inches(1.3), Inches(8.8), Inches(5.8))

# Result panel right
add_rect(s, 9.25, 1.3, 3.8, 5.8, DARK_BLUE)
add_rect(s, 9.25, 1.3, 3.8, 0.5, MID_BLUE)
add_text(s, "MEASUREMENTS", 9.25, 1.3, 3.8, 0.5,
         size=13, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)

meas_lines = [
    ("ACV Diameters (pink):", True, ACCENT_GOLD),
    ("  Transverse (B) = 17.9 cm", False, WHITE),
    ("  AP (C) = 29.7 cm", False, WHITE),
    ("  CC (A) = 34.2 cm", False, WHITE),
    ("", False, None),
    ("HSV Diameters (green):", True, GREEN),
    ("  CC (a) = 15.1 cm", False, WHITE),
    ("  AP (c) = 6.5 cm", False, WHITE),
    ("  Transverse (b) = 20.5 cm", False, WHITE),
    ("", False, None),
    ("RESULTS:", True, ACCENT_GOLD),
    ("  HSV = 1,046 mL", False, WHITE),
    ("  ACV = 9,454 mL", False, WHITE),
    ("", False, None),
]
add_multiline(s, meas_lines, 9.3, 2.0, 3.6, 4.0, size=13)

# Result badge
add_rect(s, 9.3, 6.2, 3.6, 0.75, GREEN)
add_text(s, "TI = 0.11   (<0.25)\nNO Loss of Domain", 9.3, 6.2, 3.6, 0.75,
         size=14, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
slide_number(s, 6, TOTAL)

# ─────────────────────────────────────────────────────────────────
# SLIDE 7 – CT Image Case 2 (massive LOD)
# ─────────────────────────────────────────────────────────────────
s = prs.slides.add_slide(blank)
bg(s, RGBColor(0x10, 0x10, 0x10))
header_bar(s, "CT Case 2: Massive Loss of Domain Hernia (TI > 0.25)",
           "Pink arrows = ACV measurements  |  Green arrows = HSV measurements")

s.shapes.add_picture("/tmp/workspace/tanaka-pptx/ct_image_2.jpg",
                     Inches(0.25), Inches(1.3), Inches(8.8), Inches(5.8))

add_rect(s, 9.25, 1.3, 3.8, 5.8, DARK_BLUE)
add_rect(s, 9.25, 1.3, 3.8, 0.5, RED)
add_text(s, "MEASUREMENTS", 9.25, 1.3, 3.8, 0.5,
         size=13, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)

meas2 = [
    ("ACV Diameters (pink):", True, ACCENT_GOLD),
    ("  Multiple slices measured", False, WHITE),
    ("  across axial + sagittal views", False, WHITE),
    ("", False, None),
    ("HSV Diameters (green):", True, GREEN),
    ("  Measured axial + sagittal", False, WHITE),
    ("  Note: HSV > ACV in this case", True, RGBColor(0xFF, 0x88, 0x88)),
    ("", False, None),
    ("RESULTS:", True, ACCENT_GOLD),
    ("  HSV = 7,819 mL", False, WHITE),
    ("  ACV = 7,003 mL", False, WHITE),
    ("", False, None),
    ("Ratio = 7819/7003 = 1.12", True, ACCENT_GOLD),
]
add_multiline(s, meas2, 9.3, 2.0, 3.6, 4.1, size=13)

add_rect(s, 9.3, 6.2, 3.6, 0.75, RED)
add_text(s, "TI = 1.12   (>>0.25)\nMASSIVE Loss of Domain", 9.3, 6.2, 3.6, 0.75,
         size=14, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
slide_number(s, 7, TOTAL)

# ─────────────────────────────────────────────────────────────────
# SLIDE 8 – Tanaka Index Threshold & Grading
# ─────────────────────────────────────────────────────────────────
s = prs.slides.add_slide(blank)
bg(s, LIGHT_GREY)
header_bar(s, "Tanaka Index: Thresholds & Clinical Grading",
           "Guides surgical decision-making for incisional hernia repair")

tiers = [
    ("TI < 0.25",    "No Loss of Domain",    "Standard repair - proceed directly to surgery",
     "Onlay mesh  /  Retrorectus mesh  /  Component separation\nbased on defect size (<12cm vs >12cm)",
     GREEN, "NO LOD"),
    ("TI 0.25-0.30", "Mild LOD",             "Component separation required",
     "Transversus Abdominis Release (TAR) alone\nDirect surgery without preoperative preparation",
     ORANGE, "MILD"),
    ("TI 0.31-0.35", "Moderate LOD",         "Advanced reconstruction required",
     "TAR + Peritoneal flap reinforcement\nDirect surgery without preoperative preparation",
     RGBColor(0xE0, 0x60, 0x10), "MODERATE"),
    ("TI > 0.35",    "Severe LOD",           "Preoperative preparation MANDATORY",
     "Botulinum Toxin (BT) injections + Progressive Pneumoperitoneum (PPP)\n→ Wait 24-30 days → TAR + Peritoneal flap",
     RED, "SEVERE"),
]

col_x = [0.3, 2.0, 4.2, 7.5, 11.0]
col_w_list = [1.6, 2.0, 3.1, 3.3, 2.1]
headers = ["TI VALUE", "GRADE", "DECISION", "SURGICAL APPROACH", "PREOP PREP"]

# Header row
for j, (hdr, cx, cw) in enumerate(zip(headers, col_x, col_w_list)):
    add_rect(s, cx, 1.35, cw, 0.5, DARK_BLUE)
    add_text(s, hdr, cx, 1.35, cw, 0.5,
             size=11, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)

row_h = 1.18
for i, (ti_val, grade, decision, approach, color, badge) in enumerate(tiers):
    y = 1.97 + i * (row_h + 0.05)
    bg_color = RGBColor(0xF8, 0xF8, 0xF8) if i % 2 == 0 else WHITE
    # TI value
    add_rect(s, col_x[0], y, col_w_list[0], row_h, color)
    add_text(s, ti_val, col_x[0], y, col_w_list[0], row_h,
             size=13, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
    # Grade
    add_rect(s, col_x[1], y, col_w_list[1], row_h, bg_color)
    add_text(s, grade, col_x[1] + 0.05, y + 0.1, col_w_list[1] - 0.1, row_h - 0.2,
             size=13, bold=True, color=color, wrap=True)
    # Decision
    add_rect(s, col_x[2], y, col_w_list[2], row_h, bg_color)
    add_text(s, decision, col_x[2] + 0.05, y + 0.1, col_w_list[2] - 0.1, row_h - 0.2,
             size=11, color=TEXT_DARK, wrap=True)
    # Approach
    add_rect(s, col_x[3], y, col_w_list[3], row_h, bg_color)
    add_text(s, approach, col_x[3] + 0.05, y + 0.05, col_w_list[3] - 0.1, row_h - 0.1,
             size=10.5, color=TEXT_DARK, wrap=True)
    # Preop badge
    add_rect(s, col_x[4], y + 0.2, col_w_list[4], row_h - 0.4, color)
    add_text(s, badge, col_x[4], y + 0.2, col_w_list[4], row_h - 0.4,
             size=12, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)

slide_number(s, 8, TOTAL)

# ─────────────────────────────────────────────────────────────────
# SLIDE 9 – Tanaka vs Sabbagh Comparison
# ─────────────────────────────────────────────────────────────────
s = prs.slides.add_slide(blank)
bg(s, LIGHT_GREY)
header_bar(s, "Tanaka vs. Sabbagh Method",
           "Two validated CT volumetric methods for Loss of Domain assessment")

# Left - Tanaka
add_rect(s, 0.3, 1.3, 6.0, 5.9, DARK_BLUE)
add_rect(s, 0.3, 1.3, 6.0, 0.55, MID_BLUE)
add_text(s, "TANAKA METHOD", 0.3, 1.3, 6.0, 0.55,
         size=17, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
tanaka_lines = [
    ("Formula:", True, ACCENT_GOLD),
    ("   LOD = HSV / ACV", False, WHITE),
    ("", False, None),
    ("Threshold:", True, ACCENT_GOLD),
    ("   > 0.25 = Loss of Domain", False, WHITE),
    ("", False, None),
    ("Volume method:", True, ACCENT_GOLD),
    ("   Ellipsoid formula (manual)", False, WHITE),
    ("   V = 0.52 × a × b × c", False, WHITE),
    ("", False, None),
    ("ACV Posterior boundary:", True, ACCENT_GOLD),
    ("   Transverse processes of vertebrae", False, WHITE),
    ("", False, None),
    ("Complexity:", True, ACCENT_GOLD),
    ("   Simple - fully manual on PACS", False, WHITE),
    ("   No special software required", False, WHITE),
]
add_multiline(s, tanaka_lines, 0.5, 2.0, 5.7, 5.0, size=13.5, color=WHITE)

# Right - Sabbagh
add_rect(s, 6.8, 1.3, 6.2, 5.9, WHITE)
add_rect(s, 6.8, 1.3, 6.2, 0.55, GREEN)
add_text(s, "SABBAGH METHOD", 6.8, 1.3, 6.2, 0.55,
         size=17, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
sabbagh_lines = [
    ("Formula:", True, GREEN),
    ("   LOD = HSV / (ACV + HSV) × 100%", False, TEXT_DARK),
    ("", False, None),
    ("Threshold:", True, GREEN),
    ("   > 20% = Loss of Domain", False, TEXT_DARK),
    ("", False, None),
    ("Volume method:", True, GREEN),
    ("   Semi-automated volumetry", False, TEXT_DARK),
    ("   (more precise but needs software)", False, TEXT_DARK),
    ("", False, None),
    ("ACV Posterior boundary:", True, GREEN),
    ("   Anterior aspect of vertebral body", False, TEXT_DARK),
    ("", False, None),
    ("Complexity:", True, GREEN),
    ("   More accurate, semi-automated", False, TEXT_DARK),
    ("   Correlation with Tanaka: r = 0.91", False, TEXT_DARK),
]
add_multiline(s, sabbagh_lines, 7.0, 2.0, 5.8, 5.0, size=13.5, color=TEXT_DARK)

# VS circle
add_rect(s, 6.0, 3.8, 0.9, 0.9, ACCENT_GOLD)
add_text(s, "VS", 6.0, 3.8, 0.9, 0.9,
         size=20, bold=True, color=DARK_BLUE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
slide_number(s, 9, TOTAL)

# ─────────────────────────────────────────────────────────────────
# SLIDE 10 – Summary & Key Takeaways
# ─────────────────────────────────────────────────────────────────
s = prs.slides.add_slide(blank)
bg(s, DARK_BLUE)
add_rect(s, 0, 0, 13.333, 1.1, RGBColor(0x08, 0x1E, 0x40))
add_rect(s, 0, 1.1, 13.333, 0.07, ACCENT_GOLD)
add_text(s, "Key Takeaways: Tanaka Index in CT of Incisional Hernia",
         0.35, 0.08, 12.5, 0.92,
         size=24, bold=True, color=WHITE, align=PP_ALIGN.LEFT, valign=MSO_ANCHOR.MIDDLE)

takeaways = [
    ("1", "The Tanaka Index = HSV ÷ ACV, calculated from CT using the ellipsoid formula: V = 0.52 × a × b × c", MID_BLUE),
    ("2", "TI > 0.25 defines Loss of Domain — viscera cannot be safely reduced without risking abdominal compartment syndrome", RED),
    ("3", "ACV posterior boundary = TRANSVERSE PROCESSES; anterior boundary = healthy muscle line; cranial = diaphragm; caudal = coccyx", ORANGE),
    ("4", "HSV posterior boundary = SAME as ACV (transverse processes); all other limits = parietal peritoneum of the sac", GREEN),
    ("5", "Always use the MAXIMUM diameter from any CT slice - never average; CT with Valsalva maneuver is preferred", ACCENT_GOLD),
    ("6", "TI grades guide surgery: <0.25 standard repair | 0.25-0.30 TAR | 0.31-0.35 TAR+flap | >0.35 Botox+PPP then TAR", MID_BLUE),
]

for i, (num, text, color) in enumerate(takeaways):
    y = 1.35 + i * 0.98
    add_rect(s, 0.3, y, 0.6, 0.75, color)
    add_text(s, num, 0.3, y, 0.6, 0.75,
             size=20, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
    add_rect(s, 1.05, y, 11.9, 0.75, RGBColor(0x15, 0x3A, 0x65))
    add_text(s, text, 1.15, y + 0.05, 11.7, 0.65,
             size=13.5, color=WHITE, wrap=True, valign=MSO_ANCHOR.MIDDLE)

# Footer
add_rect(s, 0, 7.1, 13.333, 0.4, RGBColor(0x08, 0x1E, 0x40))
add_text(s, "Reference: Tanaka EY et al. Hernia 2010; 14:63-69  |  Images: ECR 2025 Poster",
         0.3, 7.1, 12.7, 0.4,
         size=11, italic=True,
         color=RGBColor(0xAA, 0xBB, 0xCC), align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
slide_number(s, 10, TOTAL)

# ── Save ──────────────────────────────────────────────────────────────────────
out = "/tmp/workspace/tanaka-pptx/Tanaka_Index_CT_Incisional_Hernia.pptx"
buf = BytesIO()
prs.save(buf)
with open(out, "wb") as f:
    f.write(buf.getvalue())
print(f"Saved: {out}  ({len(buf.getvalue())//1024} KB)")

Running Command

cd /tmp/workspace/tanaka-pptx && python build_pptx.py

Running Command

python3 -c " from pptx import Presentation prs = Presentation('/tmp/workspace/tanaka-pptx/Tanaka_Index_CT_Incisional_Hernia.pptx') print(f'Slides: {len(prs.slides)}') for i, slide in enumerate(prs.slides, 1): texts = [s.text_frame.text[:60] for s in slide.shapes if s.has_text_frame and s.text_frame.text.strip()] print(f' Slide {i}: {texts[0] if texts else \"(no text)\"}') "

Your presentation is ready - 10 slides, 1.8 MB, with the actual CT scan images embedded.

Tanaka Index CT Incisional Hernia

Presentation · PPTX

Slide contents:

#	Slide
1	Title slide - Tanaka Index, CT Assessment of Incisional Hernia
2	What is Loss of Domain? - definition + clinical consequences
3	The Tanaka Formula - TI = HSV/ACV, ellipsoid formula, threshold
4	CT Landmarks for ACV - all 5 boundaries with diagram
5	CT Landmarks for HSV - all 5 boundaries + step-by-step measurement
6	CT Case 1 (real image) - Moderate hernia, TI = 0.11, no LOD
7	CT Case 2 (real image) - Massive LOD, TI = 1.12
8	Grading table - TI <0.25 / 0.25-0.30 / 0.31-0.35 / >0.35 with surgical approach
9	Tanaka vs. Sabbagh method comparison
10	Key Takeaways - 6 clinical pearls

why HCV posterior limit same as ACV?

Great question. This is a fundamental concept in the Tanaka method's design logic.

Why Does the HSV Share the Same Posterior Boundary as ACV?

The Core Reason: To Avoid Double-Counting

The Tanaka Index is a ratio - HSV divided by ACV. For this ratio to be meaningful, the two volumes must be mutually exclusive - the same physical space cannot be counted in both.

Think About It Anatomically

When a hernia develops, the abdominal wall defect creates a communication between:

The true abdominal cavity (behind the anterior abdominal wall)
The hernia sac (protruding through the defect, outside the wall)

The posterior abdominal wall (retroperitoneum, spine, paraspinal muscles) is shared anatomy - it forms the back wall of BOTH the residual abdominal cavity AND the hernia sac space, since they are ultimately one continuous peritoneal cavity separated only by the defect.

What Would Happen Without a Shared Boundary?

Imagine if the HSV posterior limit extended all the way to the back of the hernia sac skin (posteriorly):

[Spine] ← ACV posterior limit
   |
   |  ← This zone would be counted in BOTH ACV and HSV
   |
[Defect neck]
   |
[Hernia sac content]

The space between the spine and the defect neck would be measured in ACV (correctly) AND again in HSV (incorrectly). This would artificially inflate HSV and make the Tanaka Index unreliable.

The Elegant Solution

By setting both posterior limits at the transverse processes of the vertebrae, Tanaka ensures:

          TRANSVERSE PROCESS LINE (shared posterior limit)
                    |
     ←─── ACV ───→ | ←── HSV ──→
   (residual cavity)|  (sac space)
                    |
         NO OVERLAP. Clean split.

The two volumes tile perfectly together to fill the total peritoneal space without overlap or gap.

Why Transverse Processes Specifically?

The transverse processes represent the outermost bony landmark of the posterior abdominal wall visible consistently on every axial CT slice. They:

Are reproducible across all patients and all CT readers
Mark the true lateral extent of the retroperitoneal space
Sit at the junction of the musculoskeletal back and the peritoneal cavity
Are easy to identify on axial CT without special software

Note: The Sabbagh method uses the anterior aspect of the vertebral body instead - slightly more anterior - which is why Sabbagh ACV values are slightly smaller than Tanaka ACV values for the same patient.

One-Line Summary

The HSV posterior limit = ACV posterior limit because the hernia sac is simply an extension of the same peritoneal cavity - using one shared posterior boundary prevents the retroperitoneal space from being double-counted in both volumes, keeping the ratio mathematically valid.

Why in case 1 HCV ap diameter in posterior boundary is not same as ASV

Excellent observation. Let me re-examine the actual CT image from Case 1 carefully.

Loading Image

This is a very sharp observation. Looking carefully at the image:

Why the ACV AP and HSV AP Diameters Are Different in Case 1

What the image actually shows:

Measurement	Value	Plane	Color
ACV transverse (B)	17.9 cm	Axial (top left)	Pink - anterior-posterior direction
ACV AP (C)	29.7 cm	Axial (bottom left)	Pink - horizontal arrow
ACV cranio-caudal (A)	34.2 cm	Sagittal (right panel)	Pink
HSV cranio-caudal (a)	15.1 cm	Sagittal (middle)	Green
HSV AP (c)	6.5 cm	Sagittal (middle)	Green
HSV transverse (b)	20.5 cm	Axial (bottom middle)	Green

The Key Anatomical Reason

Look at the bottom-left axial slice (ACV AP = 29.7 cm) vs the middle sagittal slice (HSV AP = 6.5 cm):

AXIAL VIEW (cross-section at level of hernia):

←────────── 29.7 cm (ACV AP) ──────────→
[Spine] ←──────────────────────────────→ [Anterior abdominal wall muscle line]
          ↑
          This is the FULL depth of the
          abdominal cavity at that level

←─ 6.5 cm (HSV AP) ─→
[Posterior sac wall]←→[Anterior sac wall]
   (only the sac      (small, herniated
    protrusion)        through defect)

The hernia sac in Case 1 is a SMALL ventral hernia. It protrudes only a short distance (6.5 cm) anteriorly from the defect - it is a shallow sac sitting on the anterior abdominal wall.

The ACV AP (29.7 cm) measures the full front-to-back depth of the entire abdominal cavity - from the transverse processes of the vertebrae (posterior limit) all the way to the anterior rectus muscle line.

The HSV AP (6.5 cm) measures only the shallow depth of the small hernia sac protruding through the defect - from its posterior neck to its anterior dome.

Why They Would ONLY Be Equal in One Extreme Scenario

The HSV AP = ACV AP ONLY if the hernia sac extended posteriorly all the way to the spine - i.e., a massive loss of domain hernia where the sac has essentially replaced the entire abdominal cavity. That is the situation in Case 2, where HSV (7819 mL) actually exceeds ACV (7003 mL).

Summary

The shared posterior boundary rule does NOT mean the two AP measurements will be equal. It means both measurements start from the same posterior reference line (transverse processes). But the HSV AP is always shorter than the ACV AP in most hernias, because the hernia sac only projects a limited distance anteriorly from its neck - not the full depth of the abdomen.

Shared posterior limit = same starting point, not same distance.

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