def tumour_biopsy_data(self):
module_name = "tumour_biopsy_data"
columns_list = names(module_name)
df_cols = columns_list[:-2]
data_list_df = pd.DataFrame(columns=df_cols)
try:
ihc_biopsy = sql.get_value(col_name='IHC_report_PCCM_yes_no', table=self.table,
file_number=self.file_number, cursor=self.cursor)
except sqlite3.Error:
ihc_biopsy = ask.ask_y_n_na("Is the IHC report available?", yes_ans="IHC_report_PCCM_yes",
no_ans="IHC_report_PCCM_no", na_ans="IHC Not Done")
check = False
while not check:
try:
breast_biopsy = sql.get_value(col_name='Breast_Biopsy', table=self.table,
file_number=self.file_number, cursor=self.cursor)
except sqlite3.Error:
breast_biopsy = ask.ask_option('Breast that biopsy has been done for',
['Right Breast', 'Left Breast', 'Unilateral', "Bilateral"])
breasts = BlockDescription.breast_list(breast_biopsy)
for breast in breasts:
check_breast = False
while not check_breast:
print('Please input all data for ' + breast + ' block only')
tumour_er, tumour_er_percent, tumour_pr, tumour_pr_percent, tumour_her2, tumour_her2_grade, \
tumour_fish, tumour_ki67 = (ihc_biopsy, )* 8
if ihc_biopsy == 'IHC_report_PCCM_yes':
ihc_data = BlockDescription.ihc_report()
tumour_er, tumour_er_percent, tumour_pr, tumour_pr_percent, tumour_her2, tumour_her2_grade, \
tumour_fish, tumour_ki67 = ihc_data
fnac = ask.ask_y_n_na(question=("Lymph Node biopsy FNAC for " + breast),
yes_ans="Lymph_Node_biopsy_FNAC_yes",
no_ans="Lymph_Node_biopsy_FNAC_no", na_ans="Data not in report")
fnac_location, fnac_diagnosis = (fnac,) * 2
if fnac == "Lymph_Node_biopsy_FNAC_yes":
fnac_location = input("Please enter lymph node biopsy location: ")
fnac_diagnosis = ask.ask_option("Lymph Node biopsy diagnosis",
["Lymph_Node_biopsy_malignant",
"Lymph_Node_biopsy_non_malignant",
"Data not in report"])
df_data = [tumour_er, tumour_er_percent, tumour_pr, tumour_pr_percent, tumour_her2,
tumour_her2_grade, tumour_fish, tumour_ki67, fnac, fnac_location, fnac_diagnosis]
print('Data entered for ' + breast + 'is as follows:\n')
check_breast = sql.review_input(self.file_number, df_cols, df_data)
data_list_df.loc[breast] = df_data
data_list = BlockDescription.rb_lb_data(data_list_df, df_cols)
check = sql.review_input(self.file_number, columns_list, data_list)
last_update = datetime.now().strftime("%Y-%b-%d %H:%M")
data_list = data_list+[last_update]+[self.user_name]
return data_list
def metastasis(file_number, user_name):
check = False
while not check:
met_has = ask.ask_y_n(
"Has the patient been examined for metastatic disease?")
if not met_has:
met_has = "Not examined for metastatic disease"
else:
met_has = "Examined for metastatic disease"
date_last = ask.check_date("Date of last follow-up: ")
recur = ask.ask_y_n("Has the patient experienced a recurrence?")
if recur:
time_recur = input("Time to disease recurrence: ")
nature_recur = ask.ask_option("Nature of recurrence",
["Distant", "Local", "Other"])
if nature_recur == "Distant":
distant_site = input("Site of distant recurrence: ")
else:
distant_site = "NA"
else:
time_recur, nature_recur, distant_site = ("NA", ) * 3
status = patient_status()
data_list = [
met_has, date_last, time_recur, nature_recur, distant_site, status,
user_name,
last_update()
]
col_list = names.names_longterm("metastasis")
check = review_input(file_number, col_list, data_list)
return data_list
def surgery_block_information_3(self):
module_name = self.module_list[2]
check = False
while not check:
surgery_er, surgery_er_percent, surgery_pr, surgery_pr_percent, surgery_her2, surgery_her2_grade, \
surgery_fish, surgery_ki67, = BlockDescription.ihc_report()
sentinel, sent_number_rem, sent_number_pos = SurgeryBlockData.node_details(
"Sentinel")
ax, ax_number_rem, ax_number_pos = SurgeryBlockData.node_details(
"Axillary")
ap, ap_number_rem, ap_number_pos = SurgeryBlockData.node_details(
"Apical")
per_spread = ask.ask_y_n_na("Perinodal Spread",
yes_ans='Yes',
no_ans='No',
na_ans='Data not in Report')
supra_inv = ask.ask_y_n_na("Supraclavicular Node Involvment",
yes_ans='Yes',
no_ans='No',
na_ans='Data not in Report')
data_list = [
surgery_er, surgery_er_percent, surgery_pr, surgery_pr_percent,
surgery_her2, surgery_her2_grade, surgery_fish, surgery_ki67,
sentinel, sent_number_rem, sent_number_pos, ax, ax_number_rem,
ax_number_pos, ap, ap_number_rem, ap_number_pos, per_spread,
supra_inv
]
columns_list = names(module_name)
check = sql.review_input(self.file_number, columns_list, data_list)
return (tuple(data_list))
def mammo_mass(self, mass_id):
print(self.table, mass_id)
check = False
data_list = ask.default_data_list(self.col_list)
while not check:
mass_location = self.mammo_breast
if self.mammo_breast == "bilateral":
mass_location = ask.ask_option("Location of mass "
+ str(mass_id),
RadioTables.breast)
mass_quadrant = ask.ask_list('Quadrant location of lesion',
Radio.lesion_quadrant)
mammo_mass_shape = ask.ask_option("Shape of mass",
RadioTables.mass_shape)
mammo_mass_margin = ask.ask_option("Margins of mass",
RadioTables.mass_margin)
mass_nipple = input("Distance from nipple (cm): ")
mass_dimension,
mass_size_unit,
mass_longest_dimension = self.lesion_size()
modality = self.table
data_list = [self.file_number, mass_location, mass_name,
mass_quadrant, mammo_mass_shape, mammo_mass_margin,
mass_nipple, mass_dimension, mass_longest_dimension,
mass_size_unit, modality]
check = sql.review_input(self.file_number, columns=self.col_list,
data=data_list)
data_list = data_list + [self.user_name, sql.last_update()]
return data_list
def surgery_block_information_3(self):
module_name = self.module_list[3]
review_surgery_date, review_surgery_source, review_surgery_diagnosis, review_surgery_diagnosis_comment, \
review_surgery_block_id, review_surgery_er, review_surgery_er_percent, review_surgery_pr, review_surgery_pr_percent, \
review_surgery_her2, review_surgery_her2_grade, review_surgery_fish, review_surgery_ki67 = ['NA', ] * 13
data_list = ['NA', ] * 13
check = False
while not check:
review = ask.ask_y_n('Has a review (of diagnosis or IHC details) been done of this surgery block?')
if review:
review_surgery_date = ask.check_date('Date of review (if multiple dates?): ')
review_surgery_source = input(
'Name of Review Laboratory (Enter multiple if required Lab_test): ')
review_surgery_diagnosis = input('Enter diagnosis of review: ')
review_surgery_diagnosis_comment = input('Additional comments for review diagnosis: ')
review_surgery_block_id = self.surgery_block_id
block_id = ask.ask_y_n('Has the block been relabelled in the review?')
if block_id:
old_block_id = input('Please enter old block id: ')
new_block_id = input('Please enter new block id: ')
review_surgery_block_id = old_block_id + ' relabelled to ' + new_block_id
review_ihc = ask.ask_y_n('Has the IHC result for any marker been reviewed by another lab?')
if review_ihc:
review_surgery_er, review_surgery_er_percent, review_surgery_pr, review_surgery_pr_percent, \
review_surgery_her2, review_surgery_her2_grade, review_surgery_fish, review_surgery_ki67 = \
BlockDescription.ihc_report('review_surgery')
data_list = [review_surgery_date, review_surgery_source, review_surgery_diagnosis,
review_surgery_diagnosis_comment, review_surgery_block_id, review_surgery_er,
review_surgery_er_percent, review_surgery_pr, review_surgery_pr_percent, review_surgery_her2,
review_surgery_her2_grade, review_surgery_fish, review_surgery_ki67]
col_list = names(module_name)
check = sql.review_input(self.file_number, col_list[:-2], data_list)
data = data_list + [self.user_name, sql.last_update()]
return data
def mri_mass(self, mass_id):
check = False
data_list = ask.default_data_list(self.col_list)
while not check:
if self.mammo_breast == "bilateral":
mass_location = ask.ask_option("Location of mass " + str(
mass_id), RadioTables.breast)
else:
mass_location = self.mammo_breast
check_t1_t2 = ask.ask_y_n('Are both T1 and T2 image analysis'
'available for this mass?')
type_of_imaging = ['T1', 'T2']
if not check_t1_t2:
type_of_imaging = ask.ask_list('Observation of this mass is a'
'result of which type of'
'imaging? ',
RadioTables.mri_image_type)
data_list = self.mri_mass_detail(type_of_imaging, mass_id)
if type_of_imaging in {'T1', 'T2'}:
data_list = [('{0}_{1}'.format(type_of_imaging, data)) for
data in data_list]
mass_name = "Lesion " + str(mass_id)
data_list = [self.file_number, mass_location, mass_name]+data_list
check = sql.review_input(self.file_number, columns=self.col_list,
data=data_list)
data_list = [data_list] + [self.user_name, sql.last_update()]
data_list = data_list + [self.user_name, sql.last_update()]
return data_list
def abvs(file_number):
module_name = "abvs"
check = False
while not check:
abvs = ask_y_n_statement.ask_y_n("Automated Breast Volume Scanner (ABVS) done?")
if abvs:
abvs = "Automated Breast Volume Scanner done"
abvs_date = input("Date of examination of ABVS: ")
abvs_acc = input("Accession number of ABVS: ")
abvs_lesion = ask_y_n_statement.ask_option("Location of lesion",
["Right Breast", "Left Breast", "Both", "Not present"])
if abvs_lesion in {"Right Breast", "Left Breast", "Both"}:
abvs_lesion_data = radio_tables_old.lesion_location(abvs_lesion)
else:
abvs_lesion_data = "NA"
abvs_size = ask_y_n_statement.ask_option("Size of lesion", ["<2 cm", "2-5 cm", ">5 cm", "Other"])
abvs_dist = ask_y_n_statement.ask_option("Distance from Skin (cm)", ["<0.5 cm", ">0.5 cm", "Other"])
abvs_pect = input("Distance from Pectoralis Major (cm): ")
abvs_diagnosis = ask_y_n_statement.ask_option("ABVS Diagnosis",
["Normal", "Benign", "Suspicious", "Diagnostic for Cancer"])
else:
abvs = "Automated Breast Volume Scanner done"
abvs_date, abvs_acc, abvs_lesion, abvs_lesion_data, abvs_size, abvs_dist, abvs_pect, \
abvs_diagnosis = ("NA",) * 8
data_list = [abvs, abvs_date, abvs_acc, abvs_lesion, abvs_lesion_data, abvs_size, abvs_dist, abvs_pect,
abvs_diagnosis]
columns_list = names(module_name)
check = add_update_sql.review_input(file_number, columns_list, data_list)
return (tuple(data_list))
def report(self):
data_list = ask.default_data_list(self.col_list_all)
check = False
while not check:
reason_report = ask.ask_option(
"What is the purpose of this report"
"?", MultiTest.test_reason_imaging)
report_date = ask.check_date("Date of examination of ABVS: ")
abvs_acc = input("Accession number of ABVS: ")
abvs_lesion = ask.ask_option("Location of lesion",
MultiTest.breast_cancer)
if abvs_lesion in {MultiTest.breast_cancer}:
abvs_lesion_data = radio_tables.lesion_location(abvs_lesion)
else:
abvs_lesion_data = "NA"
abvs_size = ask.ask_option("Size of lesion",
["<2 cm", "2-5 cm", ">5 cm", "Other"])
abvs_dist = ask.ask_option("Distance from Skin (cm)",
["<0.5 cm", ">0.5 cm", "Other"])
abvs_pect = input("Distance from Pectoralis Major (cm): ")
abvs_diagnosis = ask.ask_option("ABVS Diagnosis", Radio.diagnosis)
data_list = [
self.file_number, reason_report, report_date, abvs_acc,
abvs_lesion, abvs_lesion_data, abvs_size, abvs_dist, abvs_pect,
abvs_diagnosis
]
check = sql.review_input(self.file_number, self.col_list_all[:-2],
data_list)
data_list = data_list + [self.user_name, sql.last_update()]
return data_list
def metastasis_symp(file_number):
module_name = "metastasis_symp"
check = False
while not check:
met_none = ask_y_n("Metastatis Symptoms Present?")
met = []
if not met_none:
met = [["No Metastatis Symptoms"]]
else:
met_bone = ask_y_n("Bone Pain")
if met_bone:
met.append(["Bone Pain"])
met_cough = ask_y_n("Cough")
if met_cough:
met.append(["Cough"])
met_jaundice = ask_y_n("Jaundice")
if met_jaundice:
met.append(["Jaundice"])
met_headache = ask_y_n("Headache")
if met_headache:
met.append(["Headache"])
met_weight = ask_y_n("Weight loss")
if met_weight:
met.append(["WeightLoss"])
met_flat = [item for sublist in met for item in sublist]
data_met = "; ".join(met_flat)
columns_list = pccm_names.names_info(module_name)
check = review_input(file_number, columns_list, [data_met])
return (str(data_met))
def node_excision (file_number):
check = False
while not check:
surgery_guide, frozen, gross_tumour, skin, nodes, number_lymph, level_lymph, sentinel_method, sentinel_blue, \
sentinel_hot, sentinel_blue_hot, sentinel_non_blue_hot, sentinel_palpable = (" ",)*13
guide_add = True
guide = []
while guide_add:
surgery_guide = ask_option("Excision guided by",
["Palpation", "USG guided", "Wire placement guided", 'Gamma camera guided',
'Clipped node'])
guide.append(surgery_guide)
guide_add = ask_y_n("Add another method to guide?")
surgery_guide = "; ".join(guide)
frozen_samples = ask_option_y_n("Any samples sent for histopathology (frozen)?")
if frozen_samples == 'Yes':
frozen_samples = []
sn_frozen = ask_y_n("Sentinel Node sent for histopathology (frozen)?", yes_ans="Sentinel Node")
if sn_frozen == 'Sentinel Node':
frozen_samples.append(sn_frozen)
specimen_frozen = ask_y_n_na("Specimen sent for histopathology (frozen)?")
if specimen_frozen == 'Yes':
nipple_frozen = ask_y_n_na("Under Nipple Surface sent for histopathology (frozen)?",
yes_ans='Under Nipple Surface')
if nipple_frozen == 'Under Nipple Surface':
frozen_samples.append(nipple_frozen)
other_frozen = ask_y_n_na("Any other specimen sent for histopathology (frozen)?")
if other_frozen == 'Yes':
other_frozen = input("Type of tissue sent for histopathology (frozen): ")
frozen_samples.append(other_frozen)
frozen = "; ".join(frozen_samples)
else:
frozen = "NA"
gross_tumour = input ("Size of tumour on cross section (cm): ")
skin = ask_option_y_n("Skin involved", yes_ans="Skin involved", no_ans="Skin not involved")
nodes = ask_option("Nodes excised", ["Sentinel Node", "Sentinel and Axillary Nodes", "Axillary Nodes only",
"Other"])
number_lymph = input("Number of lymph nodes excised (if available): ")
level_lymph = ask_option("Level of lymph node excised", ["I", "II", "III", "Data not available", "Other"])
if nodes == 'Axillary Nodes only':
sentinel_method, sentinel_blue, sentinel_hot, sentinel_blue_hot, sentinel_non_blue_hot, sentinel_palpable = \
('No Sentinel Node excised', )*6
else:
sentinel_method = ask_option("Method of labelling Sentinel Node", ["Isotope", "Blue Dye", "Isotope + Blue Dye",
"Not done", "Other"])
sentinel_blue = ask_option_y_n("Blue Node", yes_ans="Blue Node", no_ans="No Blue Node")
sentinel_hot = ask_option_y_n("Hot Node", yes_ans="Hot Node", no_ans="No Hot Node")
sentinel_blue_hot = ask_option_y_n("Blue Hot Node", yes_ans="Blue Hot Node", no_ans="No Blue Hot Node")
sentinel_non_blue_hot = ask_option_y_n("Non Blue, Hot Node", yes_ans= "Non Blue, Hot Node",
no_ans="No Non Blue, Hot Node")
sentinel_palpable = ask_option_y_n("Palpable Node", yes_ans="Palpable Node", no_ans="No Palpable Node")
data_list = [surgery_guide, frozen, gross_tumour, skin, nodes, number_lymph, level_lymph, sentinel_method,
sentinel_blue, sentinel_hot, sentinel_blue_hot, sentinel_non_blue_hot, sentinel_palpable]
col_list = names("node_excision")
check = add_update_sql.review_input(file_number, col_list, data_list)
return data_list
def bio_info(self):
module_name = "bio_info"
new_data = ['NA'] * 16
check = False
while not check:
mr_number = input('MR number :')
name = input('Name :')
aadhaar_card = input("Aadhaar card number (if available): ")
date_first = check_date("Date of first visit: ")
permanent_address = input('Permanent Address :')
current_address_check = ask_option(
'Current Address', ["Same as Permanent", "Different"])
if current_address_check == "Different":
current_address = input("Current Address: ")
else:
current_address = permanent_address
phone = input('Phone :')
email_id = input('Email_ID :')
gender = ask_option('Gender', ["Female", "Male", "Other"])
age_yrs = input('Age at first visit (yrs) :')
age_diag = input('Age at diagnosis (yrs): ')
date_of_birth = check_date('Date of Birth (dd/mm/yyyy):')
place_birth = input('Place of Birth :')
height = ask_option("Height unit",
["cm", "feet/inches", "Height not available"])
height_cm, height_feet, height_inch, weight, bmi = ['NA'] * 5
if height == "Height not available":
height_cm = "NA"
weight_kg = input('Weight (kg) (if available else enter NA) :')
bmi = "NA"
else:
if height == "cm":
height_cm = input('Height (cm) :')
else:
height_feet = float(input("Height (feet)"))
height_inch = float(input("Height (inches)"))
height_inch = height_inch + 12 * height_feet
height_cm = height_inch * 2.54
weight_kg = input('Weight (kg) (if available else enter NA) :')
try:
weight = float(weight_kg)
height = float(height_cm) / 100
bmi = str(round(weight / (height * height)))
except ValueError:
bmi = 'NA'
columns_list = pccm_names.names_info(module_name)
new_data = [
mr_number, name, aadhaar_card, date_first, permanent_address,
current_address, phone, email_id, gender, age_yrs, age_diag,
date_of_birth, place_birth, height_cm, weight_kg, bmi
]
check = review_input(self.file_number, columns_list, new_data)
return new_data
def pet_breast_cancer(self):
module_name = self.module_list[2]
breast_report = [
'NA',
] * 7
check = False
while not check:
pet_breast = ask.ask_y_n(
'Does this report describe a breast cancer?')
if pet_breast:
print('\nPlease describe primary breast lesion\n')
pet_breast_lesion_size = input(
'Dimensions of breast lesion/s: ')
pet_breast_lesion_size_unit = ask.ask_list(
'Unit of breast lesion size', ['mm', 'cm'])
pet_breast_lesion_suv = ask.check_number_input(
'Please enter SUV max of breast lesion: ',
'Please enter only SUV not description')
pet_breast_lesion_location = input(
'Please enter description of lesion location: ')
pet_breast_lesion_type = input(
'Please input description of lesion: ')
pet_breast_lesion_comments = input(
'Please input any additional notes for breast lesion: ')
pet_breast_nodes = ask.ask_y_n(
'Does the report describe breast related nodes?')
if pet_breast_nodes:
pet_breast_nodes_description = input(
'Please enter nodes description as given: ')
else:
pet_breast_nodes_description = 'nodes_not_described'
pet_breast_skin = ask.ask_y_n(
'Does the PET report describe any skin changes?')
if pet_breast_skin:
pet_breast_lesion_skin = input(
'Please enter description of skin changes: ')
else:
pet_breast_lesion_skin = 'skin_changes_not_described'
else:
pet_breast_lesion_size, pet_breast_lesion_size_unit, pet_breast_lesion_suv, pet_breast_lesion_location,\
pet_breast_lesion_type, pet_breast_lesion_comments, pet_breast_nodes_description, \
pet_breast_lesion_skin = ['no_breast_cancer', ] * 8
breast_report = [
pet_breast_lesion_size, pet_breast_lesion_size_unit,
pet_breast_lesion_suv, pet_breast_lesion_location,
pet_breast_lesion_type, pet_breast_lesion_comments,
pet_breast_nodes_description, pet_breast_lesion_skin
]
columns_list = names(module_name)
check = sql.review_input(self.file_number, columns_list[:-2],
breast_report)
data_list = breast_report + [self.user_name, sql.last_update()]
return data_list
def habits(file_number):
module_name = "habits"
check = False
while not check:
category = "Diet"
options = ["Vegetarian", "Non-Vegetarian", "Ovo-Vegetarian", "Other"]
diet = ask_option(category, options)
alcohol = ask_y_n("Alcohol consumption")
if alcohol:
alcohol_consump = "Alcohol Consumption"
alcohol_age = input("Consumption of alcohol from which age (yrs): ")
alcohol_quant = input("Quantity of alcohol consumed per week: ")
alcohol_duration = input("Duration of alcohol consumption: ")
alcohol_comments = input("Additional comments for alcohol consumption: ")
else:
alcohol_consump = "No Alcohol Consumption"
alcohol_age, alcohol_quant, alcohol_duration, alcohol_comments = ("NA",) * 4
data_list_alc = [diet, alcohol_consump, alcohol_age, alcohol_quant, alcohol_duration, alcohol_comments]
tobacco = ask_y_n("Tobacco exposure (Passive and/or Active)")
if tobacco:
tobacco = "Tobacco consumption"
exposure_type = ask_option("Mode of exposure to Tobacco", ["Passive", "Active", "Other"])
if exposure_type =="Passive":
tobacco_type_partic = ask_option("Mode of passive consumption", ["Home", "Work", "Commute",
"Social Interactions"])
if tobacco_type_partic == "Home":
tobacco_type_who = input ("What is the specific source?")
tobacco_passive = tobacco_type_partic + (" : ") + tobacco_type_who
else:
tobacco_passive = tobacco_type_partic
else:
tobacco_passive = "NA"
tobacco_type = ask_option("Type of tobacco use", ["Cigarette", "Beedi", "Gutkha", "Pan Masala",
"Jarda/Maava", "Hookah", "Nicotine Patch", "Mishri",
"Other"])
tobacco_age = input("Consumption of tobacco from which age (yrs): ")
tobacco_freq = input ("Frequency of tobacco consumption: ")
tobacco_quant = input("Quantity of tobacco consumed per week: ")
tobacco_duration = input("Duration of tobacco consumption: ")
tobacco_comments = input("Additional comments for tobacco consumption: ")
else:
tobacco = "No Tobacco Consumption"
exposure_type, tobacco_type, tobacco_passive, tobacco_age, tobacco_freq, tobacco_quant, tobacco_duration, \
tobacco_comments = ("NA",) * 8
other_del_habits = input("Other Deleterious Habits (if present give details): ")
data_list_tob = [tobacco, exposure_type, tobacco_passive,tobacco_type, tobacco_age, tobacco_freq,
tobacco_quant, tobacco_duration, tobacco_comments, other_del_habits]
columns_list = pccm_names.names_info(module_name)
data_list = data_list_alc + data_list_tob
check = review_input(file_number, columns_list, data_list)
return (tuple(data_list))
def pet_report_identifier(self):
module_name = self.module_list[0]
check = False
report_identifier = ['NA'] * 12
while not check:
pet_scan_date = ask.check_date('Please enter PET report date: ')
pet_scan_number = input(
'Please enter PET scan number as given on the report: ')
pet_scan_source = input(
'Please enter the facility at which PET scan was done: ')
pet_scan_reg_number = input(
"Please enter PET report registration number: ")
pet_scan_history = input(
'Please input patient history as given on report: ')
pet_carcinoma_status = ask.ask_option(
'Please enter breast cancer status',
MultiTest.carcinoma_status)
pet_cancer_location = ask.ask_list(
'What is the location of the cancer', MultiTest.breast_cancer)
pet_recurrence = ask.ask_y_n(
'Does the patient have a previously detected recurrence/mets?')
if pet_recurrence:
pet_recurrence_known = input(
'Please describe the recurrence/metastasis: ')
else:
pet_recurrence_known = 'no_known_recurrence_or_metastasis'
pet_procedure_body_region = ask.ask_list(
"Region of body monitored by PET scan", PetReport.body_region)
pet_procedure_fdg_dose_mci = ask.check_number_input(
"Please enter dose of 18F-FDG used in mCi. ",
"(Please enter only dose. If given in other units "
"enter under additional notes.): ")
pet_procedure_bsl = input(
"Please enter basal sugar level with units as given: ")
pet_scanner_name = ask.ask_list('Please enter name of scanner',
PetReport.machine_name)
pet_procedure_additional_notes = input(
'Please enter additional notes, if any for PET scan and patient '
'conditions: ')
report_identifier = [
self.file_number, pet_scan_date, pet_scan_number,
pet_scan_source, pet_scan_reg_number, pet_scan_history,
pet_carcinoma_status, pet_cancer_location,
pet_recurrence_known, pet_procedure_body_region,
pet_procedure_fdg_dose_mci, pet_procedure_bsl,
pet_scanner_name, pet_procedure_additional_notes
]
columns_list = names(module_name)
check = sql.review_input(self.file_number, columns_list,
report_identifier)
return report_identifier
def clip_information(file_number):
check = False
while not check:
clip = ask_y_n_statement.ask_y_n("Was Clip inserted for surgery?")
if clip:
clip_number = input("Number of clips inserted: ")
clip_date = ask_y_n_statement.check_date("Date of clip insertion: ")
clip_cycle = input("Clip inserted after cycle? ")
else:
clip_date, clip_number, clip_cycle = ("NA", )*3
data_list = clip_number, clip_date, clip_cycle
col_list = names("clip_information")
check = review_input(file_number, col_list, data_list)
return data_list
def other_test(file_number):
module_name = "other_test"
other_tests = [["USG Abdomen", "Abnormal"], ["CECT Abdomen and Thorax", "Visceral Metastasis"],
["PET Scan", "Visceral Metastasis", "Skeletal Metastasis"], ["Bone Scan", "Skeletal Metastasis"]]
check = False
while not check:
data_all = []
for index in other_tests:
data = clinical_tests(index)
data_all.append(data)
data_all_flat = [item for sublist in data_all for item in sublist]
col_list = pccm_names.name_clinical(module_name)
check = add_update_sql.review_input(file_number, col_list, data_all_flat)
return data_all_flat
def other_test(self):
data_list = [
'data_to_be_entered',
] * 14 + [self.user_name, last_update()]
module_name = "other_test"
check = False
while not check:
print(
'In this module please enter data for tests done at the time of diagnosis before the start of '
'treatment')
data = clinical_tests()
data_list = data + [self.user_name, last_update()]
col_list = pccm_names.names_info(module_name)
check = review_input(self.file_number, col_list, data_list)
return data_list
def family_cancer(conn, cursor, file_number):
module_name = "family_cancer"
check = False
while not check:
family_cancer_history_y_n = ask_y_n('Cancer history in Family')
if family_cancer_history_y_n:
family_cancer = family_cancer_table(conn, cursor, file_number)
family_cancer_history_y_n = "Family History of Cancer"
else:
family_cancer_history_y_n = "No Family History of Cancer"
family_cancer = "NA"
data_list = [family_cancer_history_y_n, family_cancer]
columns_list = pccm_names.names_info(module_name)
check = review_input(file_number, columns_list, data_list)
return (tuple(data_list))
def det_by(file_number):
module_name = "det_by"
check = False
while not check:
category = "Current Breast Cancer Detected by"
options = ["Self", "Physician", "Screening Camp", "Other"]
determined_by = ask_option(category, options)
if determined_by == "Screening Camp":
sc_id = input("Screening Camp ID: ")
determined_by = "Screening Camp ID " + sc_id
det_date = input("Date of current breast cancer detection: ")
columns_list = pccm_names.names_info(module_name)
data_list = [determined_by, det_date]
check = review_input(file_number, columns_list, data_list)
return (tuple(data_list))
def med_history(conn, cursor, file_number):
module_name = "med_history"
check = False
while not check:
medical_history_y_n = ask_y_n("Any Other Medical History ?")
if medical_history_y_n:
med_hist = med_history_table(conn, cursor, file_number)
medical_history_y_n = "Previous medical history present"
else:
medical_history_y_n = "No previous medical history present"
med_hist = ("NA",) * 3
condition_hist, diagnosis_date_hist, treatment_hist = med_hist
data_list = [medical_history_y_n, condition_hist, diagnosis_date_hist, treatment_hist]
columns_list = pccm_names.names_info(module_name)
check = review_input(file_number, columns_list, data_list)
return (tuple(data_list))
def phys_act(conn, cursor, file_number):
module_name = "phys_act"
check = False
while not check:
phys_act = ask_y_n("Any Physical Activities ?")
if phys_act:
phys = physical_activity_table(conn, cursor, file_number)
phys_act = "Physical Activities Performed"
phys_act_done, phys_act_freq = phys
else:
phys_act = "No Physical Activities"
phys_act_done, phys_act_freq = ("NA", ) * 2
data_list = [phys_act, phys_act_done, phys_act_freq]
columns_list = pccm_names.names_info(module_name)
check = review_input(file_number, columns_list, data_list)
return (tuple(data_list))
def cancer_history(conn, cursor, file_number):
module_name = "cancer_history"
check = False
while not check:
previous_cancer_history_y_n = ask_y_n("Previous history of cancer ?")
if previous_cancer_history_y_n:
previous_cancer = cancer_table(conn, cursor, file_number)
previous_cancer_history_y_n = "Previous history of cancer"
else:
previous_cancer_history_y_n = "No previous history of cancer"
previous_cancer = ("NA",) * 5
type_of_cancer_list, year_diagnosis_list, treat_all, type_all, duration_all = previous_cancer
data_list = [previous_cancer_history_y_n, type_of_cancer_list, year_diagnosis_list, treat_all,
type_all, duration_all]
columns_list = pccm_names.names_info(module_name)
check = review_input(file_number, columns_list, data_list)
return (tuple(data_list))
def nut_supplements(conn, cursor, file_number):
module_name = "nut_supplements"
check = False
while not check:
nut_supplements = ask_y_n("Nutritional supplements taken")
if nut_supplements:
nuts = nut_supp_table(conn, cursor, file_number)
nut_supplements = "Nutritional supplements taken"
else:
nut_supplements = "No nutritional supplements taken"
nuts = ("NA", ) * 3
nuts_type, nuts_quant, nuts_dur = nuts
data_list = [nut_supplements, nuts_type, nuts_quant, nuts_dur]
columns_list = pccm_names.names_info(module_name)
check = review_input(file_number, columns_list, data_list)
return (tuple(data_list))
def metastasis(file_number, user_name):
check = False
while not check:
met_has = ask_y_n_statement.ask_y_n(
"Has the patient been examined for metastatic disease?")
if not met_has:
met_has = "Not examined for metastatic disease"
else:
met_has = "Examined for metastatic disease"
date_last = input("Date of last follow-up: ")
recur = ask_y_n_statement.ask_y_n(
"Has the patient experienced a recurrence?")
if recur:
time_recur = input("Time to disease recurrence: ")
nature_recur = ask_y_n_statement.ask_option(
"Nature of recurrence", ["Distant", "Local", "Other"])
if nature_recur == "Distant":
distant_site = input("Site of distant recurrence: ")
else:
distant_site = "NA"
else:
time_recur, nature_recur, distant_site = ("NA", ) * 3
status = ask_y_n_statement.ask_option(
"Status at last follow up",
["Survivor", "Deceased", "Lost to follow-up", "Other"])
if status == "Survivor":
type_survivor = ask_y_n_statement.ask_option(
"the Survivor is ", [
"disease Free", "with recurrence",
"disease free with no known recurrence", "with disease"
])
status = status + ": " + type_survivor
if status == "Deceased":
type_death = ask_y_n_statement.ask_option(
"Cause of death",
["due to disease", "due to unrelated causes", "not known"])
status = status + ": " + type_death
last_update = datetime.now().strftime("%Y-%b-%d %H:%M")
data_list = [
met_has, date_last, time_recur, nature_recur, distant_site, status,
user_name, last_update
]
col_list = names.names_longterm("metastasis")
check = review_input(file_number, col_list, data_list)
return data_list
def tomosynthesis(file_number):
module_name = "tomosynthesis"
check = False
while not check:
tomo = ask_y_n_statement.ask_y_n("3D digital Tomosynthesis done")
if tomo:
tomo = "3D digital Tomosynthesis done"
print ("Please add details of tomography in mammography section")
tomo_date = input("Date of Tomosynthesis examination: ")
tomo_acc = input("Accession number of Tomosynthesis: ")
else:
tomo = "3D digital Tomosynthesis not done"
tomo_date, tomo_acc, = ("NA",) * 2
data_list = [tomo, tomo_date, tomo_acc, ]
columns_list = names(module_name)
check = add_update_sql.review_input(file_number, columns_list, data_list)
return (tuple(data_list))
def nipple_cytology (file_number):
module_name = "nipple_cytology"
check = False
while not check:
cyto = ask_y_n_statement.ask_option("Nipple Cytology", ["Done", "Not Done"])
if cyto == "Not Done":
cyto_date, cyto_number, cyto_report = ("NA",)*3
else:
cyto_date = input("Date of nipple cytology: ")
cyto_number = input("Nipple Cytology number: ")
cyto_report = ask_y_n_statement.ask_option("Nipple Cytology report and interpretation", ["Normal",
"Suspicious",
"Diagnostic for "
"Cancer", "Other"])
data_list = [cyto, cyto_date, cyto_number, cyto_report]
columns_list = pccm_names.name_clinical(module_name)
check = add_update_sql.review_input(file_number, columns_list, data_list)
return (tuple(data_list))
def family_cancer(self):
module_name = "family_cancer"
check = False
while not check:
family_cancer_history_y_n = ask_y_n_na('Cancer history in Family')
if family_cancer_history_y_n == 'Yes':
family_cancer = family_cancer_table(self.conn, self.cursor,
self.file_number)
family_cancer_history_y_n = "Family History of Cancer"
elif family_cancer_history_y_n == 'No':
family_cancer_history_y_n = "No Family History of Cancer"
family_cancer = "No Family History of Cancer"
else:
family_cancer = family_cancer_history_y_n
data_list = [family_cancer_history_y_n, family_cancer]
columns_list = pccm_names.names_info(module_name)
check = review_input(self.file_number, columns_list, data_list)
return data_list
def usg_mass(self, mass_id):
print(self.table, mass_id)
check = False
data_list = ask.default_data_list(self.col_list)
while not check:
mass_location = self.mammo_breast
if self.mammo_breast == "bilateral":
mass_location = ask.ask_option("Location of mass "
+ str(mass_id),
RadioTables.breast)
location_clock = ask.check_number_input("What is the clock"
"position of mass "
+ str(mass_id) + "?",
'Please enter only numbers'
' additional paramters '
'can be entered '
'next')
location_add = input('Additional parameters for clock position')
location_clock = location_clock + location_add + " o'clock"
mass_quadrant = 'data_not_available'
quad = ask.ask_y_n('Is the quadrant location given?')
if quad:
mass_quadrant = ask.ask_list('what is the quadrant location',
Radio.lesion_quadrant)
mass_shape = ask.ask_list("Shape of mass " + str(mass_id),
RadioTables.mass_shape)
mass_name = "lesion_" + str(mass_id)
mass_dimension,
mass_size_unit,
mass_longest_dimension = self.lesion_size()
mass_margin = ask.ask_option("Margin of mass " + str(mass_id),
RadioTables.mass_margin_usg)
mass_echo = ask.ask_option("Echo pattern of mass " + str(mass_id),
RadioTables.mass_echo)
mass_id = "Mass " + str(mass_id)
modality = self.table
data_list = [self.file_number, mass_name, mass_location,
location_clock, mass_quadrant, mass_shape,
mass_margin, mass_echo, mass_dimension,
mass_longest_dimension, mass_size_unit, modality]
check = sql.review_input(self.file_number, columns=self.col_list,
data=data_list)
data_list = data_list + [self.user_name, sql.last_update()]
return data_list
def nut_supplements(self):
module_name = "nut_supplements"
data_list = ['NA'] * 4
check = False
while not check:
nutrition = ask_y_n_na("Nutritional supplements taken")
if nutrition == 'Yes':
nuts = nut_supp_table(self.conn, self.cursor, self.file_number)
nutrition = "Nutritional supplements taken"
elif nutrition == 'No':
nutrition = "No nutritional supplements taken"
nuts = ("No nutritional supplements taken", ) * 3
else:
nuts = (nutrition, ) * 3
nuts_type, nuts_quant, nuts_dur = nuts
data_list = [nutrition, nuts_type, nuts_quant, nuts_dur]
columns_list = pccm_names.names_info(module_name)
check = review_input(self.file_number, columns_list, data_list)
return data_list
def get_consent(self, file_number):
consent_discussed = sql.get_value_no_error('consent_discussed',
self.table_name,
file_number, 'file_number',
self.cursor)
consent = sql.get_value_no_error('consent', self.table_name,
file_number, 'file_number',
self.cursor)
if not consent_discussed:
consent_discussed = ask.ask_y_n(
'Has the consent form been discussed with the patient/family? '
)
if not consent and consent_discussed:
consent = ask.ask_y_n('Did patient give consent?',
yes_ans='consent_given',
no_ans='consent_not_given')
elif not consent and not consent_discussed:
consent = 'consent_TBD'
print('consent_discussed: ' + str(consent_discussed),
'consent: ' + consent)
check = ask.ask_y_n('Is this correct?')
if not check:
check_review = False
data = [str(consent_discussed), consent]
col_list = ['consent_discussed', 'consent']
while not check_review:
consent_discussed = ask.ask_y_n(
'Has the consent form been discussed with the patient/family? '
)
consent = ask.ask_y_n('Did patient give consent?',
yes_ans='consent_given',
no_ans='consent_not_given')
data = [str(consent_discussed), consent]
check_review = sql.review_input(file_number, col_list, data)
sql.update_multiple_key(conn=self.conn,
cursor=self.cursor,
table=self.table_name,
columns=col_list,
key_name='file_number',
key_value=file_number,
data=data)
return str(consent_discussed), consent
