def create_algebra_roi(pm, examination, ss, roi):
pm.CreateRoi(Name=roi.name, Color=roi.color, Type=roi.type)
# Get ROI geometry:
roi_geometry = SSF.rg(ss, roi.name)
# Make sure that all ROI sources exists:
missing = []
sources = list(
roi.sourcesA
) # (we need to make sure that we're working on a copy of this list)
sources.extend(roi.sourcesB)
for source_roi in sources:
if not SSF.has_roi(ss, source_roi.name):
missing.append(source_roi.name)
if len(missing) == 0:
roi_geometry.OfRoi.CreateAlgebraGeometry(
Examination=examination,
ExpressionA=roi.expressionA(),
ExpressionB=roi.expressionB(),
ResultOperation=roi.operator,
ResultMarginSettings=roi.result_margin_settings())
roi_geometry.OfRoi.SetAlgebraExpression(
ExpressionA=roi.expressionA(),
ExpressionB=roi.expressionB(),
ResultOperation=roi.operator,
ResultMarginSettings=roi.result_margin_settings())
roi_geometry.OfRoi.UpdateDerivedGeometry(Examination=examination)
else:
GUIF.handle_missing_roi_for_derived_rois(roi.name, missing)
def setup_clinical_goals(ss, es, site, prescription, target):
for cg in site.target_clinical_goals:
# Make sure corresponding ROI exists before trying to create clinical goal:
if SSF.has_roi(ss, cg.name):
if cg.name in [
ROIS.external.name, ROIS.igtv.name, ROIS.gtv.name
] and cg.criteria == 'AtMost' and cg.tolerance != 5000:
cg.apply_to(es,
normalized_tolerance=round(
cg.tolerance * prescription.total_dose * 100,
0))
elif cg.name in [
ROIS.ctv_sb.name, ROIS.ptv_sbc.name
] and target != ROIS.ctv_sb.name or cg.tolerance == 5000 or cg.type == homogeneity_index:
cg.apply_to(es)
elif cg.type == conformity_index:
cg.apply_to(es,
normalized_value=round(
cg.value * prescription.total_dose * 100, 0))
else:
cg.apply_to(es,
normalized_tolerance=round(
cg.tolerance * prescription.total_dose * 100,
0))
else:
# Missing ROI:
GUIF.handle_missing_roi_for_clinical_goal(cg.name)
for cg in site.oar_clinical_goals:
# Make sure corresponding ROI exists before trying to create clinical goal:
if SSF.has_roi(ss, cg.name):
if cg.type in [dose_at_volume, dose_at_abs_volume, average_dose]:
cg.apply_to(
es,
normalized_tolerance=round(
cg.tolerance.equivalent(prescription.nr_fractions) *
100, 0))
else:
cg.apply_to(
es,
normalized_value=round(
cg.value.equivalent(prescription.nr_fractions) * 100,
0))
else:
# Missing ROI:
GUIF.handle_missing_roi_for_clinical_goal(cg.name)
def create_wall_roi(pm, examination, ss, roi):
pm.CreateRoi(Name=roi.name, Color=roi.color, Type=roi.type)
roi_geometry = SSF.rg(ss, roi.name)
# Make sure that the source ROI exists:
if SSF.has_roi(ss, roi.source.name):
roi_geometry.OfRoi.SetWallExpression(SourceRoiName=roi.source.name,
OutwardDistance=roi.outward_dist,
InwardDistance=roi.inward_dist)
roi_geometry.OfRoi.UpdateDerivedGeometry(Examination=examination,
Algorithm="Auto")
else:
GUIF.handle_missing_roi_for_derived_rois(roi.name, [roi.source.name])
def create_expanded_roi(pm, examination, ss, roi):
pm.CreateRoi(Name=roi.name, Color=roi.color, Type=roi.type)
# Get ROI geometry:
roi_geometry = SSF.rg(ss, roi.name)
# Make sure that the source ROI exists:
if SSF.has_roi(ss, roi.source.name):
roi_geometry.OfRoi.CreateMarginGeometry(
Examination=examination,
SourceRoiName=roi.source.name,
MarginSettings=roi.margin_settings)
roi_geometry.OfRoi.SetMarginExpression(
SourceRoiName=roi.source.name, MarginSettings=roi.margin_settings)
roi_geometry.OfRoi.UpdateDerivedGeometry(Examination=examination)
else:
GUIF.handle_missing_roi_for_derived_rois(roi.name, [roi.source.name])
selected_oar_list[ROIS.submand_l] = True selected_oar_list[ROIS.submand_r] = True if selected_oar_list.get(ROIS.ribs_l): selected_oar_list[ROIS.rib_y_l] = True selected_oar_list[ROIS.rib_x_l] = True if selected_oar_list.get(ROIS.ribs_r): selected_oar_list[ROIS.rib_y_r] = True selected_oar_list[ROIS.rib_x_r] = True if selected_oar_list.get(ROIS.lungs): selected_oar_list[ROIS.lung_l] = True selected_oar_list[ROIS.lung_r] = True if selected_oar_list.get(ROIS.breast_l): selected_oar_list[ROIS.breast_l_draft] =True if selected_oar_list.get(ROIS.breast_r): selected_oar_list[ROIS.breast_r_draft] =True if selected_oar_list.get(ROIS.markers)and SSF.has_roi(ss, ROIS.rectum.name): del selected_oar_list[ROIS.markers] selected_oar_list[ROIS.marker1] = True selected_oar_list[ROIS.marker2] = True selected_oar_list[ROIS.marker3] = True selected_oar_list[ROIS.marker4] = True if selected_oar_list.get(ROIS.couch): PMF.create_couch(patient_db, pm, ss, examination) if selected_oar_list.get(ROIS.body): PMF.create_stereotactic_body_geometry(pm, examination, ss) PMF.create_stereotactic_external_geometry(pm, examination, ss) if selected_oar_list.get(ROIS.external): PMF.create_external_geometry(pm, examination, ss) if selected_oar_list.get(ROIS.anal_canal): PMF.create_bottom_part_x_cm(pm, examination, ss, ROIS.rectum, ROIS.anal_canal, 4) if selected_oar_list.get(ROIS.dorso_rectum):
def setup_clinical_goals(ss, es, site, total_dose, nr_fractions, target):
for cg in site.target_clinical_goals:
# Make sure corresponding ROI exists before trying to create clinical goal:
if SSF.has_roi(ss, cg.name):
if cg.name in [
ROIS.external.name, ROIS.igtv.name, ROIS.gtv.name
] and cg.criteria == 'AtMost' and cg.tolerance != 5000:
c = es.AddClinicalGoal(RoiName=cg.name,
GoalCriteria=cg.criteria,
GoalType=cg.type,
AcceptanceLevel=round(
cg.tolerance * total_dose * 100, 0),
ParameterValue=cg.value,
Priority=cg.priority)
elif cg.name in [
ROIS.ctv_sb.name, ROIS.ptv_sbc.name
] and target != ROIS.ctv_sb.name or cg.tolerance == 5000 or cg.type == homogeneity_index:
c = es.AddClinicalGoal(RoiName=cg.name,
GoalCriteria=cg.criteria,
GoalType=cg.type,
AcceptanceLevel=cg.tolerance,
ParameterValue=cg.value,
Priority=cg.priority)
elif cg.type == conformity_index:
c = es.AddClinicalGoal(RoiName=cg.name,
GoalCriteria=cg.criteria,
GoalType=cg.type,
AcceptanceLevel=cg.tolerance,
ParameterValue=round(
cg.value * total_dose * 100, 0),
Priority=cg.priority)
else:
c = es.AddClinicalGoal(RoiName=cg.name,
GoalCriteria=cg.criteria,
GoalType=cg.type,
AcceptanceLevel=round(
cg.tolerance * total_dose * 100, 0),
ParameterValue=cg.value,
Priority=cg.priority)
else:
# Missing ROI:
GUIF.handle_missing_roi_for_clinical_goal(cg.name)
for cg in site.oar_clinical_goals:
# Make sure corresponding ROI exists before trying to create clinical goal:
if SSF.has_roi(ss, cg.name):
if cg.type != average_dose:
if cg.type in [dose_at_volume, dose_at_abs_volume]:
c = es.AddClinicalGoal(
RoiName=cg.name,
GoalCriteria=cg.criteria,
GoalType=cg.type,
AcceptanceLevel=round(
cg.tolerance.equivalent(nr_fractions) * 100, 0),
ParameterValue=cg.value,
Priority=cg.priority)
else:
c = es.AddClinicalGoal(
RoiName=cg.name,
GoalCriteria=cg.criteria,
GoalType=cg.type,
AcceptanceLevel=cg.tolerance,
ParameterValue=round(
cg.value.equivalent(nr_fractions) * 100, 0),
Priority=cg.priority)
else:
c = es.AddClinicalGoal(
RoiName=cg.name,
GoalCriteria=cg.criteria,
GoalType=cg.type,
AcceptanceLevel=round(
cg.tolerance.equivalent(nr_fractions) * 100, 0),
Priority=cg.priority)
else:
# Missing ROI:
GUIF.handle_missing_roi_for_clinical_goal(cg.name)