def update_treatment_volume_overlap_in_db(study_instance_uid, roi_name):
"""
This function will recalculate the PTV overlap of an roi based on data in the SQL DB.
:param study_instance_uid: uid as specified in SQL DB
:param roi_name: roi_name as specified in SQL DB
"""
oar_coordinates_string = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
ptv_coordinates_strings = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_type like 'PTV%%'" %
study_instance_uid)
if ptv_coordinates_strings:
oar = roi_tools.get_planes_from_string(oar_coordinates_string[0][0])
ptvs = [
roi_tools.get_planes_from_string(ptv[0])
for ptv in ptv_coordinates_strings
]
tv = roi_tools.get_union(ptvs)
overlap = roi_tools.calc_roi_overlap(oar, tv)
DVH_SQL().update(
'dvhs', 'ptv_overlap', round(float(overlap), 2),
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
def update_dist_to_ptv_centroids_in_db(study_instance_uid, roi_name):
"""
This function will recalculate the OARtoPTV centroid distance based on data in the SQL DB.
:param study_instance_uid: uid as specified in SQL DB
:param roi_name: roi_name as specified in SQL DB
"""
oar_centroid_string = DVH_SQL().query(
'dvhs', 'centroid', "study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
oar_centroid = np.array(
[float(i) for i in oar_centroid_string[0][0].split(',')])
ptv_coordinates_strings = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_type like 'PTV%%'" %
study_instance_uid)
if ptv_coordinates_strings:
ptvs = [
roi_tools.get_planes_from_string(ptv[0])
for ptv in ptv_coordinates_strings
]
tv = roi_tools.get_union(ptvs)
ptv_centroid = np.array(roi_tools.calc_centroid(tv))
dist_to_ptv_centroids = float(
np.linalg.norm(ptv_centroid - oar_centroid)) / 10.
DVH_SQL().update(
'dvhs', 'dist_to_ptv_centroids', round(dist_to_ptv_centroids, 3),
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
def update_spread_in_db(study_instance_uid, roi_name):
"""
This function will recalculate the spread of an roi based on data in the SQL DB.
:param study_instance_uid: uid as specified in SQL DB
:param roi_name: roi_name as specified in SQL DB
"""
coordinates_string = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
roi = roi_tools.get_planes_from_string(coordinates_string[0][0])
spread = calc_spread(roi)
spread = [str(round(v / 10., 3)) for v in spread]
DVH_SQL().update(
'dvhs', 'spread_x', spread[0],
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
DVH_SQL().update(
'dvhs', 'spread_y', spread[1],
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
DVH_SQL().update(
'dvhs', 'spread_z', spread[2],
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
def update_roi_viewer_data(self):
# if roi_name is an empty string (default selection), return an empty data set
if not self.roi_select.value:
return {'0': {'x': [], 'y': [], 'z': []}}
roi_data = {}
roi_coord_string = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_name = '%s'" %
(self.uid_select.value, self.roi_select.value))
roi_planes = get_planes_from_string(roi_coord_string[0][0])
for z_plane in list(roi_planes):
x, y, z = [], [], []
for polygon in roi_planes[z_plane]:
initial_polygon_index = len(x)
for point in polygon:
x.append(point[0])
y.append(point[1])
z.append(point[2])
x.append(x[initial_polygon_index])
y.append(y[initial_polygon_index])
z.append(z[initial_polygon_index])
x.append(float('nan'))
y.append(float('nan'))
z.append(float('nan'))
roi_data[z_plane] = {'x': x, 'y': y, 'z': z}
self.roi_viewer_data[self.roi_number] = roi_data
def update_tv_data(self):
self.tv_data = {}
uid = self.uid_select.value
ptv_coordinates_strings = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_type like 'PTV%%'" % uid)
if ptv_coordinates_strings:
ptvs = [
get_planes_from_string(ptv[0])
for ptv in ptv_coordinates_strings
]
tv_planes = get_union(ptvs)
for z_plane in list(tv_planes):
x, y, z = [], [], []
for polygon in tv_planes[z_plane]:
initial_polygon_index = len(x)
for point in polygon:
x.append(point[0])
y.append(point[1])
z.append(point[2])
x.append(x[initial_polygon_index])
y.append(y[initial_polygon_index])
z.append(z[initial_polygon_index])
x.append(float('nan'))
y.append(float('nan'))
z.append(float('nan'))
self.tv_data[z_plane] = {'x': x, 'y': y, 'z': z}
def update_volumes_in_db(study_instance_uid, roi_name):
"""
This function will recalculate the volume of an roi based on data in the SQL DB.
:param study_instance_uid: uid as specified in SQL DB
:param roi_name: roi_name as specified in SQL DB
"""
coordinates_string = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
roi = roi_tools.get_planes_from_string(coordinates_string[0][0])
volume = roi_tools.calc_volume(roi)
DVH_SQL().update(
'dvhs', 'volume', round(float(volume), 2),
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
def update_surface_area_in_db(study_instance_uid, roi_name):
"""
This function will recalculate the surface area of an roi based on data in the SQL DB.
:param study_instance_uid: uid as specified in SQL DB
:param roi_name: roi_name as specified in SQL DB
"""
coordinates_string = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
roi = roi_tools.get_planes_from_string(coordinates_string[0][0])
surface_area = roi_tools.surface_area_of_roi(roi,
coord_type="sets_of_points")
DVH_SQL().update(
'dvhs', 'surface_area', round(float(surface_area), 2),
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
def update_centroid_in_db(study_instance_uid, roi_name):
"""
This function will recalculate the centroid of an roi based on data in the SQL DB.
:param study_instance_uid: uid as specified in SQL DB
:param roi_name: roi_name as specified in SQL DB
"""
coordinates_string = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
roi = roi_tools.get_planes_from_string(coordinates_string[0][0])
centroid = roi_tools.calc_centroid(roi)
centroid = [str(round(v, 3)) for v in centroid]
DVH_SQL().update(
'dvhs', 'centroid', ','.join(centroid),
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
def update_cross_section_in_db(study_instance_uid, roi_name):
"""
This function will recalculate the centoid of an roi based on data in the SQL DB.
:param study_instance_uid: uid as specified in SQL DB
:param roi_name: roi_name as specified in SQL DB
"""
coordinates_string = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
roi = roi_tools.get_planes_from_string(coordinates_string[0][0])
area = roi_tools.calc_cross_section(roi)
DVH_SQL().update(
'dvhs', 'cross_section_max', area['max'],
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
DVH_SQL().update(
'dvhs', 'cross_section_median', area['median'],
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
def update_min_distances_in_db(study_instance_uid, roi_name):
"""
This function will recalculate the min, mean, median, and max PTV distances an roi based on data in the SQL DB.
:param study_instance_uid: uid as specified in SQL DB
:param roi_name: roi_name as specified in SQL DB
"""
oar_coordinates_string = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
ptv_coordinates_strings = DVH_SQL().query(
'dvhs', 'roi_coord_string',
"study_instance_uid = '%s' and roi_type like 'PTV%%'" %
study_instance_uid)
if ptv_coordinates_strings:
oar_coordinates = roi_tools.get_roi_coordinates_from_string(
oar_coordinates_string[0][0])
ptvs = [
roi_tools.get_planes_from_string(ptv[0])
for ptv in ptv_coordinates_strings
]
tv_coordinates = roi_tools.get_roi_coordinates_from_planes(
roi_tools.get_union(ptvs))
try:
min_distances = roi_tools.get_min_distances_to_target(
oar_coordinates, tv_coordinates)
dth = calc_dth(min_distances)
dth_string = ','.join(['%.3f' % num for num in dth])
DVH_SQL().update(
'dvhs', 'dist_to_ptv_min',
round(float(np.min(min_distances)),
2), "study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
DVH_SQL().update(
'dvhs', 'dist_to_ptv_mean',
round(float(np.mean(min_distances)),
2), "study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
DVH_SQL().update(
'dvhs', 'dist_to_ptv_median',
round(float(np.median(min_distances)),
2), "study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
DVH_SQL().update(
'dvhs', 'dist_to_ptv_max',
round(float(np.max(min_distances)),
2), "study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
DVH_SQL().update(
'dvhs', 'dth_string', dth_string,
"study_instance_uid = '%s' and roi_name = '%s'" %
(study_instance_uid, roi_name))
except:
print('dist_to_ptv calculation failure, skipping')
def __init__(self, structure_file, dose_file):
# Get ROI Category Map
database_rois = DatabaseROIs()
# Import RT Structure and RT Dose files using dicompyler
rt_structure_dicom = dicom.read_file(structure_file)
mrn = rt_structure_dicom.PatientID
study_instance_uid = rt_structure_dicom.StudyInstanceUID
rt_structure = dicomparser.DicomParser(structure_file)
rt_structures = rt_structure.GetStructures()
if hasattr(rt_structure_dicom, 'PhysiciansOfRecord'):
physician = rt_structure_dicom.PhysiciansOfRecord.upper()
elif hasattr(rt_structure_dicom, 'ReferringPhysicianName'):
physician = rt_structure_dicom.ReferringPhysicianName.upper()
else:
physician = '(NULL)'
values = {}
row_counter = 0
self.dvhs = {}
for key in rt_structures:
# Import DVH from RT Structure and RT Dose files
if rt_structures[key]['type'] != 'MARKER':
current_dvh_calc = dvhcalc.get_dvh(structure_file, dose_file,
key)
self.dvhs[row_counter] = current_dvh_calc.counts
if current_dvh_calc.volume > 0:
print('Importing', current_dvh_calc.name, sep=' ')
if rt_structures[key]['name'].lower().find('itv') == 0:
roi_type = 'ITV'
else:
roi_type = rt_structures[key]['type']
current_roi_name = clean_name(rt_structures[key]['name'])
if database_rois.is_roi(current_roi_name):
if database_rois.is_physician(physician):
physician_roi = database_rois.get_physician_roi(
physician, current_roi_name)
institutional_roi = database_rois.get_institutional_roi(
physician, physician_roi)
else:
if current_roi_name in database_rois.institutional_rois:
institutional_roi = current_roi_name
else:
institutional_roi = 'uncategorized'
physician_roi = 'uncategorized'
else:
institutional_roi = 'uncategorized'
physician_roi = 'uncategorized'
coord = rt_structure.GetStructureCoordinates(key)
roi_coord_str = dicompyler_roi_coord_to_db_string(
rt_structure.GetStructureCoordinates(key))
try:
surface_area = surface_area_of_roi(coord)
except:
print(
"Surface area calculation failed for key, name: %s, %s"
% (key, current_dvh_calc.name))
surface_area = '(NULL)'
planes = get_planes_from_string(roi_coord_str)
centroid = calc_centroid(planes)
spread = calc_spread(planes)
cross_sections = calc_cross_section(planes)
current_dvh_row = DVHRow(
mrn, study_instance_uid, institutional_roi,
physician_roi, current_roi_name, roi_type,
current_dvh_calc.volume, current_dvh_calc.min,
current_dvh_calc.mean, current_dvh_calc.max, ','.join([
'%.2f' % num for num in current_dvh_calc.counts
]), roi_coord_str, surface_area,
','.join(['%.3f' % num for num in centroid
]), spread[0], spread[1], spread[2],
cross_sections['max'], cross_sections['median'])
values[row_counter] = current_dvh_row
row_counter += 1
self.count = row_counter
dvh_range = range(self.count)
for attr in dir(values[0]):
if not attr.startswith('_'):
setattr(self, attr,
[getattr(values[x], attr) for x in dvh_range])