def prescription_real_dose_test(self):
t = TEST.Test(
"Skal stemme overens (innenfor 0.5%) med aktuell dose for nomeringsvolum (eller punkt)",
True, self.dose)
if self.ts_beam_set.beam_set.Modality == 'Photons':
cum_pr_dose = RSU.prescription_dose(self.ts_beam_set.beam_set)
diff_pr_dose = RSU.differential_prescription_dose(
self.ts_beam_set.ts_plan.plan, self.ts_beam_set.beam_set)
low_dose = round(diff_pr_dose * 0.995, 2)
high_dose = round(diff_pr_dose * 1.005, 2)
t.expected = "<" + str(low_dose) + " - " + str(high_dose) + ">"
# If the prescription type is "SITE", we are not able to verify the prescription (at least currently):
try:
struct = self.prescription.PrimaryDosePrescription.OnStructure
except:
struct = None
if struct:
# What type of prescription has been used?
if self.prescription.PrimaryDosePrescription.PrescriptionType == 'DoseAtPoint':
norm_poi = RSU.ss_poi_geometry(self.ts_beam_set.beam_set,
struct)
p = {
'x': norm_poi.Point.x,
'y': norm_poi.Point.y,
'z': norm_poi.Point.z
}
real_poi_dose = RSU.gy(
self.ts_beam_set.beam_set.FractionDose.
InterpolateDoseInPoint(Point=p)
) * self.ts_beam_set.beam_set.FractionationPattern.NumberOfFractions
if real_poi_dose < low_dose or real_poi_dose > high_dose:
return t.fail(round(real_poi_dose, 2))
else:
return t.succeed()
if self.prescription.PrimaryDosePrescription.PrescriptionType == 'MedianDose':
real_dose_d50 = RSU.gy(
self.ts_beam_set.beam_set.FractionDose.
GetDoseAtRelativeVolumes(RoiName=struct.Name,
RelativeVolumes=[0.50])[0]
) * self.ts_beam_set.beam_set.FractionationPattern.NumberOfFractions
if real_dose_d50 < low_dose or real_dose_d50 > high_dose:
return t.fail(round(real_dose_d50, 2))
else:
return t.succeed()
elif self.prescription.PrimaryDosePrescription.PrescriptionType == 'DoseAtVolume':
real_dose_d99 = RSU.gy(
self.ts_beam_set.beam_set.FractionDose.
GetDoseAtRelativeVolumes(RoiName=struct.Name,
RelativeVolumes=[0.99])[0]
) * self.ts_beam_set.beam_set.FractionationPattern.NumberOfFractions
if real_dose_d99 < low_dose or real_dose_d99 > high_dose:
return t.fail(round(real_dose_d99, 2))
else:
return t.succeed()
def prescription_dose_test(self):
t = TEST.Test(
"Skal stemme overens med totaldose indikert av beam set label.",
True, self.dose)
cum_pr_dose = RSU.prescription_dose(self.ts_beam_set.beam_set)
diff_pr_dose = RSU.differential_prescription_dose(
self.ts_beam_set.ts_plan.plan, self.ts_beam_set.beam_set)
if self.ts_beam_set.ts_label.label.valid:
label_dose_acc = RSU.accumulated_label_dose(
self.ts_beam_set.ts_plan.plan, self.ts_beam_set.beam_set,
self.ts_beam_set.ts_label.label)
t.expected = round(label_dose_acc, 2)
if label_dose_acc != cum_pr_dose:
return t.fail(cum_pr_dose)
else:
return t.succeed()
def clinical_max_test(self):
ss = self.ts_beam_set.ts_structure_set().structure_set
if SSF.has_named_roi_with_contours(ss, ROIS.external.name):
# Get the external ROI and its volume:
external = ss.OutlineRoiGeometry
volume = external.GetRoiVolume()
# Determine which max dose level and volume fraction is to be used:
if self.is_stereotactic():
# Use point dose (0 cc):
fraction = 0
# For stereotactic treatments, max allowed dose is dependent on site:
if self.ts_beam_set.ts_label.label.region in RC.brain_codes:
# Brain SRT:
max_factor = 1.7
else:
# Other SBRT:
max_factor = 1.5
else:
# Use the fraction which gives a 2 cc volume:
fraction = 2 / volume
# For conventional treatment max allowed dose is 105 %:
max_factor = 1.05
# The differential dose of this prescription:
diff_pr_dose = RSU.differential_prescription_dose(
self.ts_beam_set.ts_plan.plan, self.ts_beam_set.beam_set)
# Create the test:
expected = "<" + str(round(diff_pr_dose * max_factor, 2))
t = TEST.Test(
"Skal i utgangspunktet være mindre enn {} % av normeringsdosen"
.format(round(max_factor * 100)), expected, self.max)
# Get the clinical max dose:
clinical_max_dose = RSU.gy(
self.ts_beam_set.beam_set.FractionDose.
GetDoseAtRelativeVolumes(RoiName=external.OfRoi.Name,
RelativeVolumes=[fraction])[0]
) * self.ts_beam_set.beam_set.FractionationPattern.NumberOfFractions
# Is it outside the set limit?
if clinical_max_dose > diff_pr_dose * max_factor:
return t.fail(round(clinical_max_dose, 2))
else:
return t.succeed()
def clinical_max_test(self):
t = TEST.Test(
"Skal i utgangspunktet være mindre enn 105% av normeringsdosen",
True, self.maks)
ts = TEST.Test(
"Skal i utgangspunktet være mindre enn 150% av normeringsdosen",
True, self.maks)
diff_pr_dose = RSU.differential_prescription_dose(
self.ts_beam_set.ts_plan.plan, self.ts_beam_set.beam_set)
ss = self.ts_beam_set.ts_structure_set().structure_set
if SSF.has_named_roi_with_contours(ss, ROIS.external.name):
#external = RSU.ss_roi_geometry(self.ts_beam_set.beam_set, self.ts_beam_set.ts_plan.ts_case.case.PatientModel.RegionsOfInterest[ROIS.external.name])
external = ss.OutlineRoiGeometry
volume = external.GetRoiVolume()
# Determine the fraction corresponding to a 2cc volume:
fraction = 2 / volume
#clinical_max_dose = RSU.gy(self.ts_beam_set.beam_set.FractionDose.GetDoseAtRelativeVolumes(RoiName = external.OfRoi.Name, RelativeVolumes = [fraction])[0]) * self.ts_beam_set.beam_set.FractionationPattern.NumberOfFractions
if self.ts_beam_set.ts_label.label.technique:
if not self.ts_beam_set.ts_label.label.technique.upper(
) == 'S':
clinical_max_dose = RSU.gy(
self.ts_beam_set.beam_set.FractionDose.
GetDoseAtRelativeVolumes(RoiName=external.OfRoi.Name,
RelativeVolumes=[fraction])[0]
) * self.ts_beam_set.beam_set.FractionationPattern.NumberOfFractions
if clinical_max_dose > diff_pr_dose * 1.05:
t.expected = "<" + str(round(diff_pr_dose * 1.05, 2))
return t.fail(round(clinical_max_dose, 2))
else:
return t.succeed()
elif self.ts_beam_set.ts_label.label.technique.upper() == 'S':
clinical_max_dose = RSU.gy(
self.ts_beam_set.beam_set.FractionDose.
GetDoseAtRelativeVolumes(RoiName=external.OfRoi.Name,
RelativeVolumes=[0])[0]
) * self.ts_beam_set.beam_set.FractionationPattern.NumberOfFractions
if clinical_max_dose > diff_pr_dose * 1.50:
ts.expected = "<" + str(round(diff_pr_dose * 1.50, 2))
ts.fail(round(clinical_max_dose, 2))
else:
ts.succeed()