R: Dosimetry, volume, conformity, homogeneity indices from...

rt.indices.from.bin {espadon}

R Documentation

Dosimetry, volume, conformity, homogeneity indices from binary selection

Description

The rt.indices.from.bin function calculates, from a "volume" class object of modality "rtdose", all the standard indicators of radiotherapy, as long as their options are transmitted, for the target and healthy "volume" object of modality "binary".

Usage

rt.indices.from.bin(
  vol,
  target.bin.list = NULL,
  healthy.bin.list = NULL,
  T.MAT = NULL,
  presc.dose = NA,
  healthy.tol.dose = NA,
  healthy.weight = 1,
  dosimetry = c("D.min", "D.max", "D.mean", "STD"),
  volume.indices = c("V.tot", "area", "V.prescdose"),
  conformity.indices = c("PITV", "CI.lomax2003", "CN", "NCI", "DSC", "CI.distance",
    "CI.abs_distance", "CDI", "CS3", "ULF", "OHTF", "gCI", "COIN", "G_COSI", "COSI"),
  homogeneity.indices = c("HI.RTOG.max_ref", "HI.RTOG.5_95", "HI.ICRU.max_min",
    "HI.ICRU.2.98_ref", "HI.ICRU.2.98_50", "HI.ICRU.5.95_ref", "HI.mayo2010",
    "HI.heufelder"),
  gradient.indices = c("GI.ratio.50"),
  D.xpc = NULL,
  D.xcc = NULL,
  V.xpc = NULL,
  V.xGy = NULL,
  verbose = TRUE
)

Arguments

`vol`	"volume" class object, of "rtdose" modality.
`target.bin.list`	list of "volume" class objects, of "binary" modality. The `$object.alias` field of each `target.bin.list` object represents the name of the selected region of interest of the target volume.
`healthy.bin.list`	list of "volume" class objects, of "binary" modality. The `$object.alias` field of each `healthy.bin.list` object represents the name of the selected region of interest of the healthy tissues.
`T.MAT`	"t.mat" class object, created by load.patient.from.Rdcm or load.T.MAT. If `T.MAT = NULL`, all `$ref.pseudo` of `bin.list` elements must be equal to `vol$ref.pseudo`.
`presc.dose`	vector of prescription doses that serve as reference doses for the target RoI.
`healthy.tol.dose`	vector of tolerance dose of each healthy RoI.
`healthy.weight`	Vector of weight, indicating the importance of the healthy RoI.
`dosimetry`	Vector indicating the requested dose indicators from among 'D.min', 'D.max', 'D.mean' and 'STD'. If `D.xpc` is different from `NULL`, it will be added.
`volume.indices`	Vector indicating the requested volume indices from among 'V.tot', 'V.prescdose' (i.e. volume over `presc.dose`) and 'area'. If `V.xGy` is different from `NULL`, it will be added.
`conformity.indices`	Vector. Requested conformity indices from among 'PITV', 'PDS', 'CI.lomax2003', 'CN', 'NCI', 'DSC', 'CI.distance', 'CI.abs_distance', 'CDI', 'CS3', 'ULF', 'OHTF', 'gCI', 'COIN', 'COSI' and 'G_COSI'.
`homogeneity.indices`	Vector. Requested homogeneity indices from among 'HI.RTOG.max_ref', 'HI.RTOG.5_95', 'HI.ICRU.max_min', 'HI.ICRU.2.98_ref', 'HI.ICRU.2.98_50', 'HI.ICRU.5.95_ref', 'HI.mayo2010' and 'HI.heufelder.'
`gradient.indices`	Vector. Requested gradient indices from among 'GI.ratio.50', 'mGI'.
`D.xpc`	Vector of the percentage of the volume, for which the dose coverage is requested.
`D.xcc`	Vector of the volume in $cm^3$, for which the dose coverage is requested.
`V.xpc`	Vector of the percentage of the reference dose, received by the volume to be calculated.
`V.xGy`	Vector of the minimum dose in Gy, received by the volume to be calculated.
`verbose`	Boolean. if `TRUE` (default) a progress bar is displayed.

Value

Return a list of indices dataframe. For details, see rt.indices.from.roi.

Examples

# loading of toy-patient objects (decrease dxyz and increase beam.nb for better
# result)
step <- 5
patient <- toy.load.patient (modality = c("rtdose", "rtstruct"), roi.name = "eye",
                             dxyz = rep (step, 3), beam.nb = 3)
D <- patient$rtdose[[1]]
struct <- patient$rtstruct[[1]]
T.MAT <- patient$T.MAT

# creation of the list of target binary volumes
target.roi.idx <- select.names (struct$roi.info$roi.pseudo, roi.sname = "ptv")
healthy.roi.idx <- select.names (struct$roi.info$roi.pseudo, roi.sname = "eye")
target.bin.list <- lapply (target.roi.idx , function (idx) {
  vr <- nesting.roi (D, struct, roi.idx = idx, xyz.margin = c (5, 5, 5),
                     T.MAT = T.MAT, alias = struct$roi.info$name[idx])
  b <- bin.from.roi(vr, struct, roi.idx = idx, T.MAT = T.MAT,
                    alias = struct$roi.info$name[idx], verbose = FALSE)
  })
names (target.bin.list) <- struct$roi.info$name[target.roi.idx]

healthy.bin.list <- lapply (healthy.roi.idx , function (idx) {
  vr <- nesting.roi (D, struct, roi.idx = idx, xyz.margin = c (5, 5, 5),
                     T.MAT = T.MAT, alias = struct$roi.info$name[idx])
  b <- bin.from.roi(vr, struct, roi.idx = idx, T.MAT = T.MAT,
                    alias = struct$roi.info$name[idx], verbose = FALSE)
})
names (healthy.bin.list) <- struct$roi.info$name[healthy.roi.idx]

indices <- rt.indices.from.bin (D, target.bin.list, healthy.bin.list,
                                presc.dose = 50,
                                conformity.indices = c("PITV", "PDS", "CI.lomax2003", 
                                                       "CN", "NCI", "DSC","COIN"),
                                verbose = FALSE)
indices