def sonomammo(conn, cursor, file_number):
module_name = "sonomammo"
check = False
while not check:
sonomammo = ask.ask_y_n("Sono-Mammography done?")
if sonomammo:
sonomammo = "Sono-Mammography done"
sonomammo_date = input("Date of examination of Sono-mammography: ")
sonomammo_acc = input("Accession number of Sono-Mammography: ")
sonomammo_tissue = ask.ask_option("Tissue Composition", [
"a. Homogeneous background echotexture – fat",
"b. Homogeneous background echotexture – fibroglandular",
"c. Heterogeneous background echotexture", "Other"
])
mass_sonomammo = ask.ask_y_n("Is there any mass detected")
if mass_sonomammo:
table = "sonnomammography_multiple_mass"
mass_number_sonomammo, mass_location, mass_quad, mass_clock, mass_depth, mass_distance, mass_pect, \
mass_shape_sonomammo, mass_orientation_sonomammo, mass_margin_sonomammo, mass_echo_sonomammo, \
mass_posterior_sonomammo = radio_tables_old.multiple_mass(table, conn, cursor, file_number)
else:
mass_number_sonomammo = "No Mass Detected"
mass_location, mass_quad, mass_clock, mass_depth, mass_distance, mass_pect, mass_shape_sonomammo, \
mass_orientation_sonomammo, mass_margin_sonomammo, mass_echo_sonomammo, \
mass_posterior_sonomammo = ("NA",) * 11
sonomammo_calc = ask.ask_option("Calcification", [
"Right Breast", "Left Breast", "Both", "Not present", "Other"
])
if sonomammo_calc == "Not present":
sonomammo_calc_type = "NA"
else:
sonomammo_calc_type = ask.ask_option(
"Calcification location", [
"Calcifications in a mass",
"Calcifications outside of a mass",
"Intraductal calcifications"
])
sonomammo_arch = ask.ask_option("Architectural distortion", [
"Right Breast", "Left Breast", "Both", "Not present", "Other"
])
sonomammo_duct = ask.ask_option("Duct Changes", [
"Right Breast", "Left Breast", "Both", "Not present", "Other"
])
sonomammo_skin = ask.ask_y_n("Skin Changes")
if sonomammo_skin:
sonomammo_skin = ask.ask_option(
"Type of skin changes",
["Skin thickening", "Skin retraction"])
else:
sonomammo_skin = "No skin changes"
sonomammo_edema = ask.ask_option("Edema", [
"Right Breast", "Left Breast", "Both", "Not present", "Other"
])
sonomammo_vasc = ask.ask_option(
"Vascularity",
["Absent", "Internal vascularity", "Vessels in rim", "Other"])
sonomammo_elast = ask.ask_option(
"Elasticity assessment",
["Soft", "Intermediate", "Hard", "Other"])
sonomammo_lymph_intra = input(
"Description of intramammary lymph nodes: ")
sonomammo_lymph_ax = ask_y_n_statement.ask_option(
"Axillary Lymph Nodes", ["Normal", "Abnormal"])
if sonomammo_lymph_ax == "Abnormal":
lymph_ax_cort = input("Cortical thickness: ")
lymph_ax_hilum = ask_y_n_statement.ask_option(
"Axillary lymph node hilum",
["Lost", "Thin", "Preserved", "Other"])
lymph_ax_vasc = ask_y_n_statement.ask_option(
"Axillary lymph node vascularity",
["Ventral", "Peripheral", "Other"])
else:
lymph_ax_cort, lymph_ax_hilum, lymph_ax_vasc = ("NA", ) * 3
sonomammo_sol_duct = ask_y_n_statement.ask_y_n(
"Is solitary dilated duct present?")
if sonomammo_sol_duct:
sol_duct_loc = ask_y_n_statement.ask_option(
"Location of Solitary Dilated duct",
["Right Breast", "Left Breast", "Both"])
sol_duct_diam = input(
"Diameter of solitary dilated duct (mm): ")
sol_mass = ask_y_n_statement.ask_y_n(
"Is Intra-ductal solid mass present?",
"Intra-ductal Solid Mass Present",
"Intra-ductal Solid Mass Absent")
else:
sol_duct_loc = "Not Present"
sol_duct_diam, sol_mass = ("NA", ) * 2
sonomammo_shear = input(
"Strain and shear wave velocity on elastography type/pattern: "
)
sonomammo_vtq = input("Median Shear Velocity (VTQ) in m/s: ")
other = ask_y_n_statement.ask_y_n("Are there any other findings?")
if other:
print(
"If more than one other finding, chose Other and enter findings separated by ; "
)
sonomammo_other = ask_y_n_statement.ask_option(
"Other Findings", [
"Simple cyst", "Clustered microcysts",
"Complicated cyst", "Mass in or on skin",
"Foreign body including implants",
"Vascular abnormalities",
"AVMs (arteriovenous malformations/"
"pseudoaneurysms)", "Mondor disease",
"Postsurgical fluid collection", "Fat necrosis", "Other"
])
else:
sonomammo_other = "NA"
sono_birad = ask_y_n_statement.ask_y_n(
"Does the report include a BI-RAD assessment/Diagnosis?")
if sono_birad:
sonomammo_birad, sonomammo_diag = radio_tables_old.birads()
else:
sonomammo_birad, sonomammo_diag = ("NA", ) * 2
else:
sonomammo = "Sono-Mammography not done"
sonomammo_date, sonomammo_acc, sonomammo_tissue, mass_number_sonomammo, mass_location, mass_quad, \
mass_clock, mass_depth, mass_distance, mass_pect, mass_shape_sonomammo, mass_orientation_sonomammo, \
mass_margin_sonomammo, mass_echo_sonomammo, mass_posterior_sonomammo, sonomammo_calc, sonomammo_calc_type, \
sonomammo_arch, sonomammo_duct, sonomammo_skin, sonomammo_edema, sonomammo_vasc, sonomammo_elast, \
sonomammo_lymph_intra, sonomammo_lymph_ax, lymph_ax_cort, lymph_ax_hilum, lymph_ax_vasc, sol_duct_loc, \
sol_duct_diam, sol_mass, sonomammo_other, sonomammo_shear, sonomammo_vtq, sonomammo_birad, \
sonomammo_diag = ("NA",) * 36
data_list = [
sonomammo, sonomammo_date, sonomammo_acc, sonomammo_tissue,
mass_number_sonomammo, mass_location, mass_quad, mass_clock,
mass_depth, mass_distance, mass_pect, mass_shape_sonomammo,
mass_orientation_sonomammo, mass_margin_sonomammo,
mass_echo_sonomammo, mass_posterior_sonomammo, sonomammo_calc,
sonomammo_calc_type, sonomammo_arch, sonomammo_duct,
sonomammo_skin, sonomammo_edema, sonomammo_vasc, sonomammo_elast,
sonomammo_lymph_intra, sonomammo_lymph_ax, lymph_ax_cort,
lymph_ax_hilum, lymph_ax_vasc, sol_duct_loc, sol_duct_diam,
sol_mass, sonomammo_shear, sonomammo_vtq, sonomammo_other,
sonomammo_birad, sonomammo_diag
]
columns_list = names(module_name)
check = add_update_sql.review_input(file_number, columns_list,
data_list)
return (tuple(data_list))
def mri_breast(conn, cursor, file_number, user_name):
module_name = "mri_breast"
check = False
while not check:
mri_breast = ask_y_n_statement.ask_y_n("Has MRI-Breast been done?")
if mri_breast:
mri_breast = "MRI-Breast done"
mri_breast_date = input("Date of examination of MRI: ")
mri_breast_acc = input(
"Accession number of MRI (Include location): ")
fgt_mri = ask_y_n_statement.ask_option(
"Ammount of Fibroglandular Tissue", [
"a. Almost entirely fat",
"b. Scattered fibroglandular tissue",
"c. Heterogeneous fibroglandular tissue",
"d. Extreme fibroglandular tissue", "Other"
])
bpe_level_mri = ask_y_n_statement.ask_option(
"Background parenchymal enhancement Level",
["Minimal", "Mild", "Moderate", "Marked", "Other"])
bpe_symm_mri = ask_y_n_statement.ask_option(
"Background parenchymal enhancement Symmetry",
["Symmetric", "Asymmetric", "Other"])
focus_mri = input("Details of Focus: ")
mass_mri = ask_y_n_statement.ask_y_n("Are masses detected?")
if mass_mri:
mass_mri = "Mass Detected"
table = "mri_multiple_mass"
mri_mass_number, mass_location, mass_quad, mass_shape, mass_margin, mass_internal = \
radio_tables_old.multiple_mass(table, conn, cursor, file_number)
else:
mass_mri = "No Mass Detected"
mri_mass_number, mass_location, mass_quad, mass_shape, mass_margin, mass_internal = (
"NA", ) * 6
asso_feat = [
"Nipple Retraction", "Nipple Invasion", "Skin Retraction",
"Skin Thickening", "Axillary adenopathy",
"Pectoralis muscle invasion", "Chest wall invasion",
"Architectural Distortion"
]
asso_feat_data = []
for index in (asso_feat):
print("Associated feature: " + index)
print("Detailed description can be added by choosing 'Other'")
var = ask_y_n_statement.ask_option(index, [
"Right Breast", "Left Breast", "Both", "Not Present",
"Other"
])
asso_feat_data.append(var)
asso_feat_9 = ask_y_n_statement.ask_option(
"Associated Feature: Skin Invasion",
["Direct invasion", "Inflammatory cancer", "Other"])
asso_feat_1, asso_feat_2, asso_feat_3, asso_feat_4, asso_feat_5, asso_feat_6, asso_feat_7, \
asso_feat_8 = asso_feat_data
fat_lesions = ask_y_n_statement.ask_option(
"Fat Containing Lesions", [
"Lymph nodes: Normal", "Lymph nodes: Abnormal",
"Fat necrosis", "Hamartoma", "Postoperative seroma",
"hematoma with fat"
])
mri_breast_kinetics_initial = ask_y_n_statement.ask_option(
"Kinetic curve assessment Signal intensity "
"(SI)/time curve description (Initial Phase)",
["Slow", "Medium", "Fast", "Other"])
mri_breast_kinetics_delayed = ask_y_n_statement.ask_option(
"Kinetic curve assessment Signal intensity "
"(SI)/time curve description (Delayed Phase)",
["Persistent", "Plateau", "Washout", "Other"])
mri_breast_non_enhance = ask_y_n_statement.ask_option(
"Non-enhancing findings", [
"Ductal precontrast high signal on T1W", "Cyst",
"Postoperative collections (hematoma/seroma)",
"Post-therapy skin thickening and trabecular "
"thickening", "Signal void from foreign bodies, "
"clips, etc.", "Other"
])
mri_breast_implant = input("Implant related findings: ")
mri_breast_lesion = ask_y_n_statement.ask_option(
"Location of lesion",
["Right Breast", "Left Breast", "Both", "Not present"])
if mri_breast_lesion in {"Right Breast", "Left Breast", "Both"}:
mri_breast_lesion_location = radio_tables_old.lesion_location(
mri_breast_lesion)
mri_breast_lesion_depth = input("Lesion depth: ")
else:
mri_breast_lesion_location, mri_breast_lesion_depth = (
"NA", ) * 2
mri_breast_size = ask_y_n_statement.ask_option(
"Size of lesion", ["<2 cm", "2-5 cm", ">5 cm", "Other"])
mri_breast_dist = ask_y_n_statement.ask_option(
"Distance from Skin (cm)", ["<0.5 cm", ">0.5 cm", "Other"])
mri_breast_pect = input("Distance from Pectoralis Major (cm): ")
mri_breast_birad = ask_y_n_statement.ask_y_n(
"Does the report include a BI-RAD assessment/Diagnosis?")
if mri_breast_birad:
mri_breast_birad, mri_breast_birad_diag = radio_tables_old.birads(
)
else:
mri_breast_birad, mri_breast_birad_diag = ("NA", ) * 2
else:
mri_breast = "MRI-Breast not done"
mri_breast_date, mri_breast_acc, fgt_mri, bpe_level_mri, bpe_symm_mri, focus_mri, mass_mri, mri_mass_number, \
mass_location, mass_quad, mass_shape, mass_margin, mass_internal, asso_feat_1, asso_feat_2, asso_feat_3, \
asso_feat_4, asso_feat_5, asso_feat_6, asso_feat_7, asso_feat_8, asso_feat_9, fat_lesions, \
mri_breast_lesion, mri_breast_lesion_location, mri_breast_lesion_depth, mri_breast_kinetics_initial, \
mri_breast_kinetics_delayed, mri_breast_non_enhance, mri_breast_implant, mri_breast_size, mri_breast_dist, \
mri_breast_pect, mri_breast_birad, mri_breast_birad_diag = ("NA",) * 35
data_list = [
mri_breast, mri_breast_date, mri_breast_acc, fgt_mri,
bpe_level_mri, bpe_symm_mri, focus_mri, mass_mri, mri_mass_number,
mass_location, mass_quad, mass_shape, mass_margin, mass_internal,
asso_feat_1, asso_feat_2, asso_feat_3, asso_feat_4, asso_feat_5,
asso_feat_6, asso_feat_7, asso_feat_8, asso_feat_9, fat_lesions,
mri_breast_kinetics_initial, mri_breast_kinetics_delayed,
mri_breast_non_enhance, mri_breast_implant, mri_breast_lesion,
mri_breast_lesion_location, mri_breast_lesion_depth,
mri_breast_size, mri_breast_dist, mri_breast_pect,
mri_breast_birad, mri_breast_birad_diag, user_name,
add_update_sql.last_update()
]
columns_list = names(module_name)
check = add_update_sql.review_input(file_number, columns_list,
data_list)
return (tuple(data_list))
def mammography(conn, cursor, file_number):
module_name = "mammography"
check = False
while not check:
mammo_loc = ask.ask_option("Mammography Diagnosis at",
["PCCM", "Outside", "Other"])
mammo_details = ask.ask_y_n("First Mammography?")
if mammo_details:
mammo_date = input("Date when mammography done: ")
mammo_details = "First Mammography"
mammo_number, mammo_rep_previous = ("NA", ) * 2
else:
mammo_date = input("Date of last mammography done: ")
mammo_details = "More than one Mammography"
mammo_number = input("Number of mammographies undergone: ")
mammo_rep_previous = input("Report of previous mammography: ")
mammo = ask.ask_y_n("Mammography diagnosis done")
if mammo:
mammo = "Mammography diagnosis done"
mammo_diag_date = input("Date of mammography diagnosis: ")
mammo_diag_acc = input(
"Accession number of mammography diagnosis: ")
breast_density = ask.ask_option("Density of breast", [
"a. The breasts are almost entirely fatty",
"b. There are scattered areas of fibroglandular density",
"c. The breasts are heterogeneously dense, which may obscure"
" small masses", "d. The breasts are extremely "
"dense which lowers the sensitivity of "
"mammography"
])
mammo_mass_location = ask.ask_y_n("Is there any mass detected")
if mammo_mass_location:
table = "mammography_multiple_mass"
mass_number, mammo_mass_location, mammo_mass_location_quad, mammo_mass_depth, mammo_mass_dist, \
mammo_mass_pect, mammo_mass_shape, mammo_mass_margin, mammo_mass_density = radio_tables_old.multiple_mass(
table, conn, cursor, file_number)
else:
mass_number = "No mass detected"
mammo_mass_location, mammo_mass_location_quad, mammo_mass_depth, mammo_mass_dist, mammo_mass_pect, \
mammo_mass_shape, mammo_mass_margin, mammo_mass_density = ("NA",) * 8
calc = ask.ask_y_n("Is Calcification present?")
if calc:
calc_number, calc_location, location_quad, calc_depth, calc_dist, calc_pect, calc_name, calc_type, \
calc_distribution = radio_tables_old.cal_table(file_number, conn, cursor)
else:
calc_number = "No Calcification detected"
calc_location, location_quad, calc_depth, calc_dist, calc_pect, calc_name, calc_type, calc_distribution = \
("NA",) * 8
mammo_arch, arch_loc, arch_quad, arch_depth, arch_dist, arch_pect = radio_tables_old.mammo_arch(
)
asym_loc, asym_quad, asym_depth, asym_dist, asym_pect, mammo_asymm = radio_tables_old.mammo_asym(
)
intra_lymph = ask.ask_y_n("Are intra-mammary lymph nodes present?")
if intra_lymph:
mammo_intra = input(
"Description of intra-mammary lymph nodes: ")
else:
mammo_intra = "Intra-mammary lymph nodes not present"
lesion = ask.ask_y_n("Skin Lesion present?")
if lesion:
mammo_lesion = ask.ask_option(
"Location of lesion",
["Right Breast", "Left Breast", "Both"])
else:
mammo_lesion = "NA"
asso_feat_1, asso_feat_2, asso_feat_3, asso_feat_4, asso_feat_5, asso_feat_6, \
asso_feat_7 = radio_tables_old.mammo_asso_feat()
mammo_birad = ask.ask_y_n(
"Does the report include a BI-RAD assessment/diagnosis?")
if mammo_birad:
mammo_birad, mammo_diag = radio_tables_old.birads()
else:
mammo_birad, mammo_diag = ("NA", ) * 2
else:
mammo = "Mammography diagnosis not done"
mammo_diag_date, mammo_diag_acc, breast_density, mass_number, mammo_mass_location, mammo_mass_location_quad, \
mammo_mass_depth, mammo_mass_dist, mammo_mass_pect, mammo_mass_shape, mammo_mass_margin, mammo_mass_density, \
calc_number, calc_location, location_quad, calc_depth, calc_dist, calc_pect, calc_name, calc_type, \
calc_distribution, mammo_arch, arch_loc, arch_quad, arch_depth, arch_dist, arch_pect, asym_loc, asym_quad, asym_depth, asym_dist, \
asym_pect, mammo_asymm, mammo_intra, mammo_lesion, asso_feat_1, asso_feat_2, asso_feat_3, asso_feat_4, \
asso_feat_5, asso_feat_6, asso_feat_7, mammo_birad, mammo_diag = ("NA",) * 42
data_list = [
mammo_loc, mammo_details, mammo_date, mammo_number,
mammo_rep_previous, mammo, mammo_diag_date, mammo_diag_acc,
breast_density,
str(mass_number), mammo_mass_location, mammo_mass_location_quad,
mammo_mass_depth, mammo_mass_dist, mammo_mass_pect,
mammo_mass_shape, mammo_mass_margin, mammo_mass_density,
calc_number, calc_location, location_quad, calc_depth, calc_dist,
calc_pect, calc_name, calc_type, calc_distribution, mammo_arch,
arch_loc, arch_quad, arch_depth, arch_dist, arch_pect, asym_loc,
asym_quad, asym_depth, asym_dist, asym_pect, mammo_asymm,
mammo_intra, mammo_lesion, asso_feat_1, asso_feat_2, asso_feat_3,
asso_feat_4, asso_feat_5, asso_feat_6, asso_feat_7, mammo_birad,
mammo_diag
]
columns_list = names(module_name)
check = add_update_sql.review_input(file_number, columns_list,
data_list)
return (tuple(data_list))