set.rbmdata: Ultrasound profile preparation for metastatic risk estimation

In Morphonodepredictivemodel/morphonode: The Morphonode Predictive Model for ultrasound signatures detection and malignancy prediction in vulvar cancer

Ultrasound profile preparation for metastatic risk estimation

Description

Prepare a new ultrasound profile for metastatic risk estimation using robust binomial modeling. This function includes missing values check and fix (see set.missing).

Usage

set.rbmdata(
  u,
  levels,
  short = 8,
  cortical = 2,
  ist = 1,
  ecs = 1,
  hab = 0,
  eco = 1,
  vp = c(1, 2, 3),
  vfl = c(2, 3, 4),
  ct = c(2),
  fid = c(1, 2, 3),
  cmid = c(2, 3, 4),
  shape = c(3),
  cs = 3,
  grouping = c(2, 3),
  ref = NULL,
  asFactor = FALSE,
  ...
)

Arguments

u	New ultrasound profile generated by new.profile.
levels	A list of length 14, corresponding to the levels of each ultrasound variable. Needed for categorical variables (factors); for continuous variables, it should assume the nominal value of 0. The default levels variable mpm.levels can be used.
short	Numeric value corresponding to the short axis cutoff in millimeters (default = 8).
cortical	Numeric value corresponding to the cortical thickness cutoff in millimeters (default = 2).
ist	Dichotomous value 0, 1 for the presence of inflammatory stroma (perinodal hyperechogenic ring; default = 1).
ecs	Dichotomous value 0, 1 for the presence of extracapsular spread (cortical interruption; default = 1).
hab	Dichotomous value 0, 1 for the absence of the hilum (nodal core sign; default = 0).
eco	Dichotomous value 0, 1 for heterogeneous echogenicity (echostructure; default = 1).
vp	Categorical value (integers from 0 to 4) associated to a high-risk vascular flow architecture pattern (default = c(1, 2, 3)).
vfl	Categorical value (integers from 0 to 4) associated to a high-risk vascular flow localization (default = c(2, 3, 4)).
ct	Categorical value (integers from 0 to 4) associated to a high-risk cortical thickening (default = 2).
fid	Categorical value (integers from 0 to 3) associated to a high-risk focal intranodal deposit (default = c(1, 2, 3)).
cmid	Categorical value (integers from 0 to 4) associated to a high-risk cortical-medullar interface distortion (default = c(2, 3, 4)).
shape	Categorical value (integers from 1 to 3) associated to a high-risk shape (default = 3).
cs	Ordinal value (integers from 1 to 5) associated to a high-risk color score (default = 3).
grouping	Categorical value (integers from 1 to 3) associated to a high-risk grouping (default = c(2, 3)).
ref	Reference ultrasound features dataset as a (n, 14) data.frame, with n being the number of subjects (rows). The default simulated dataset mpm.us can be used.
asFactor	Logical value. If TRUE, data.frame columns are converted to factors (default = FALSE).
...	Currently ignored.

Value

A list of 2 objects:

1. "ultrasound", dichotomized ultrasound features vector;

2. "missing", indices of missing values (empty if no missing values are found).

Author(s)

Fernando Palluzzi [e-mail]

References

Fragomeni SM, Moro F, Palluzzi F, Mascilini F, Rufini V, Collarino A, Inzani F, Giacò L, Scambia G, Testa AC, Garganese G (2022). Evaluating the risk of inguinal lymph node metastases before surgery using the Morphonode Predictive Model: a prospective diagnostic study. Ultrasound xx Xxxxxxxxxx xxx Xxxxxxxxxx. 00(0):000-000. <https://doi.org/00.0000/00000000000000000000>

See Also

See set.rfcdata for random forest classifier data preparation. See also us.predict to launch all morphonode modules at once.

Examples

# Prepare a simulated malignant ultrasound profile
x <- new.profile(us.simulate(y = 1))
print(x)

# Set the new profile for RFC prediction
v <- set.rbmdata(x, ref = mpm.us[, 2:15], levels = mpm.levels)
print(v)

Morphonodepredictivemodel/morphonode documentation built on Feb. 15, 2023, 4:51 a.m.