Example #1
0
class PatientHistoryDict():
    def __init__(self, key, value):
        self.key = key
        self.value = value

    diet_dict = {
        'veg': "Vegetarian",
        'non-veg': "Non-Vegetarian",
        'egg': "Ovo-Vegetarian",
        'other': "Other"
    }
    diet_choice = CommonDict.generate_choice(diet_dict)
    tobacco_dict = {
        'no': 'No exposure',
        'passive': 'Passive',
        'active': 'Active',
        'pa': 'Passive and Active'
    }
    tobacco_choice = CommonDict.generate_choice(tobacco_dict)
    tobacco_type_passive_dict = {
        'no': 'No exposure',
        'home': "Home",
        'work': "Work",
        'commute': "Commute",
        'social': "Social Interactions",
        'other': 'Other'
    }
    tobacco_type_passive_choice = CommonDict.generate_choice(
        tobacco_type_passive_dict)
    tobacco_type_dict = {
        'no': 'No exposure',
        'cig': "Cigarette",
        'beedi': "Beedi",
        'gutka': "Gutkha",
        'pan_masala': "Pan Masala",
        'jarda': "Jarda/Maava",
        'hookah': "Hookah",
        'patch': "Nicotine Patch",
        'mishri': "Mishri",
        'other': "Other"
    }
    tobacco_type_choice = CommonDict.generate_choice(tobacco_type_dict)
    yes_no_dict = {
        'tbd': "To be filled",
        "N": "No",
        "Y": "Yes",
        'other': "Other"
    }
Example #2
0
class ChemoDict():
    def __init__(self, key, value):
        self.key = key
        self.value = value

    place_nact_dict = {'tbd':"To be filled",'pccm':"At PCCM",'outside': "Outside",
                       'tbd_':"Not Certain, requires follow-up"}
    details_nact_dict = {'tbd':"To be filled","Y":"Details Available","tbd_":"Follow-up required"}
    drugs_dict = {'tbd':"To be filled",'5fu':"5-FluoroUracil",
                  'anthra':"Anthracycline",
                  'anstro':"Anastrozole",
                  'carbop':"Carboplatin",
                  'cisp':"Cisplatin",
                  'cyclo':"Cyclophosphamide",
                  'doci':"Docitaxel",
                  'doxo':"Doxorubicin",
                  'epi':'Epirubicin',
                  'exe':"Exemestane",
                  'fulv':"Fulvestrant",
                  'gem':"Gemcitabine",
                  'gos':"Goserelin",
                  'herc':"Herceptin(Trastuzumab)",
                  'letro':"Letrozole",
                  'leupro':"Leuprolide",
                  'pacli':"Paclitaxel",
                  'tamoxi':"Tamoxifen",
                  'other':"Other"}
    toxic_side_effects_dict = {'tbd':"To be filled",'fever': "Fever",
                                'aneamia': "Anaemia",
                                'neutro': "Neutropenia",
                                'breath': "Breathlessness",
                                'vom': "Vomiting",
                                'nausea': "Nausea",
                                'loose': "Loose Motions",
                                'cough': "Cough",
                                'ui': "Urinary Infections",
                                'cardio': "Cardiotoxicity",
                                'neuro': "Neuropathy",
                                'other': "Other"}
    toxic_side_effects_grade_dict = {'tbd':"To be filled",'mild':"Mild", 'moderate':"Moderate", 'severe':"Severe",
                                     'other':"Other"}
    tumour_response_nact_dict = {'tbd':"To be filled",'partial':"Partial", 'complete':"Complete", 'no':"No Effect",
                              'other':"Other"}
    nact_change_dict = {'tbd':"To be filled", 'no':"No change",'change_tox':"NACT regime changed due to toxicity",
                        'stop_tox': "NACT stopped  due to toxicity", 'change_other': "NACT changed due to other reasons",
                        'stop_other': "NACT stopped due to other reasons"}
    trast_regime_nact_dict = {'tbd':"To be filled",'seq':"Sequential", 'con':"Concurrent", 'other':"Other"}
    reason_incomplete_chemo_dict = {'tbd':"To be filled",'tox':"Toxicity",
                              'reluctance': "Reluctance of patient",
                              'prog': "Progression on chemotherapy",
                              'doctor': "Advised by treating doctor",
                              'death_tox': "Death due to toxicity",
                              'death_disease': "Death due to progressive disease",
                              'centre': "Preferred treatment at another centre",
                              'death': "Death due to unrelated cause",
                              'price': "Patient was unable to afford treatment", 'other': 'Other'}
    menopause_dict = {'tbd':"To be filled",'pre': "Pre-menopausal",'peri': "Peri-menopausal",'post': "Post-Menopausal",
                      'other': "Other"}
    ovary_status_dict = {'tbd':"To be filled",'menses': "Menses ongoing",'ameno_on': "Amenorrhoea on Chemo",
                         'ameno_post': "Amenorrhoea post Chemotherapy", 'other':'Other'}
    place_nact_choice = CommonDict.generate_choice(place_nact_dict)
    details_nact_choice = CommonDict.generate_choice(details_nact_dict)
    drugs_choice = CommonDict.generate_choice(drugs_dict)
    toxic_side_effects_choice = CommonDict.generate_choice(toxic_side_effects_dict)
    toxic_side_effects_grade_choice = CommonDict.generate_choice(toxic_side_effects_grade_dict)
    tumour_response_choice = CommonDict.generate_choice(tumour_response_nact_dict)
    nact_change_choice = CommonDict.generate_choice(nact_change_dict)
    trast_regime_nact_choice = CommonDict.generate_choice(trast_regime_nact_dict)
    reason_incomplete_nact_choice = CommonDict.generate_choice(reason_incomplete_chemo_dict)
    menopause_choice = CommonDict.generate_choice(menopause_dict)
    ovary_status_choice = CommonDict.generate_choice(ovary_status_dict)
Example #3
0
class BiopsyDict():
    def __init__(self, key, value):
        self.key = key
        self.value = value

    consent_stat_dict = {
        'tbd': "To be filled",
        "N": "No Consent",
        "Y": "Consent Taken"
    }
    consent_form_dict = {
        'tbd': "To be filled",
        "Y": "Consent form with signature present in folder",
        "N": "Completed consent form not present in folder"
    }
    biopsy_type_dict = {
        'tbd': "To be filled",
        "direct": "Direct",
        "usg_guided": "USG Guided",
        "vab": "VAB",
        "trucut": "Tru-cut",
        "stereo": "Steriotactic",
        "other": "Other"
    }
    tumour_diagnosis_dict = {
        'tbd': "To be filled",
        'benign': 'Benign',
        'dcis_micro': "Ductal carcinoma in situ(DCIS) with microinvasion",
        'dcis_no_micro':
        "Ductal carcinoma in situ(DCIS) without microinvasion",
        "lcs": "Lobular Carcinoma in Situ (LCS)",
        "idc": "Invasive Ductal Carcinoma (IDC)",
        'ilc': "Invasive Lobular Carcinoma (ILC)",
        'gm': "Granulamatous Mastitis",
        'papc': "Papillary Carcinoma",
        'phyc': "Phylloid Carcinoma",
        'imc': "Invasive Mammary Carcinoma",
        'ibc': "Invasive Breast Carcinoma",
        'other': 'Other'
    }
    biopsy_custody_pccm_dict = {
        'tbd': "To be filled",
        "Y": "In PCCM Custody",
        "N": "Not in PCCM custody"
    }
    tumour_grade_dict = {
        'tbd': "To be filled",
        "1": 'Grade 1',
        "2": "Grade 2",
        "3": "Grade 3"
    }
    lymphovascular_emboli_dict = {
        'tbd': "To be filled",
        "Y": "Lymphovascular Emboli Seen",
        "N": "No Lymphovascular Emboli Seen",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    dcis_biopsy_dict = {
        'tbd': "To be filled",
        "Y": "DCIS seen",
        "N": "DCIS not seen",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    tumour_er_dict = {
        'tbd': "To be filled",
        "pos": "Positive",
        "neg": "Negative",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    tumour_pr_dict = {
        'tbd': "To be filled",
        "pos": "Positive",
        "neg": "Negative",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    tumour_her2_dict = {
        'tbd': "To be filled",
        "pos": "Positive",
        "eqv": "Equivocal",
        "neg": "Negative",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    fnac_dict = {
        'tbd': "To be filled",
        "Y": "Done",
        "N": "Not Done",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    fnac_location_dict = {
        'tbd': "To be filled",
        "rb": "Right",
        "lb": "Left",
        "both": "Both",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    fnac_diagnosis_dict = {
        'tbd': "To be filled",
        "normal": "Normal",
        "benign": "Benign",
        "malignant": "Malignant",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }

    consent_stat_choice = CommonDict.generate_choice(consent_stat_dict)
    consent_form_choice = CommonDict.generate_choice(consent_form_dict)
    biopsy_type_choice = CommonDict.generate_choice(biopsy_type_dict)
    tumour_diagnosis_choice = CommonDict.generate_choice(tumour_diagnosis_dict)
    biopsy_custody_pccm_choice = CommonDict.generate_choice(
        biopsy_custody_pccm_dict)
    tumour_grade_choice = CommonDict.generate_choice(tumour_grade_dict)
    lymphovascular_emboli_choice = CommonDict.generate_choice(
        lymphovascular_emboli_dict)
    dcis_biopsy_choice = CommonDict.generate_choice(dcis_biopsy_dict)
    tumour_er_choice = CommonDict.generate_choice(tumour_er_dict)
    tumour_pr_choice = CommonDict.generate_choice(tumour_pr_dict)
    tumour_her2_choice = CommonDict.generate_choice(tumour_her2_dict)
    fnac_choice = CommonDict.generate_choice(fnac_dict)
    fnac_location_choice = CommonDict.generate_choice(fnac_location_dict)
    fnac_diagnosis_choice = CommonDict.generate_choice(fnac_diagnosis_dict)
Example #4
0
class ClinicalExamDict():
    def __init__(self, key, value):
        self.key = key
        self.value = value

    palpable_dict = {
        'tbd': "To be filled",
        'definite': "Definite",
        'vague': "Vague",
        'diffuse': "Diffuse",
        'nil': "Nil",
        'other': "Other"
    }
    lump_size_dict = {
        'tbd': "To be filled",
        '1': "less than 2cm",
        '2': "2-5cm",
        '3': "more than 5cm",
        'other': "Other"
    }
    lump_number_dict = {
        'tbd': "To be filled",
        'single': "Single",
        'multiple': "Multiple",
        'other': "Other"
    }
    lump_consistency_dict = {
        'tbd': "To be filled",
        'soft': "Soft",
        'Firm': "Firm",
        'hard': "Hard",
        'cystic': "Cystic",
        'mobile': "Mobile",
        'other': "Other"
    }
    lump_fixity_dict = {
        'tbd': "To be filled",
        'skin': "Skin",
        'chest wall': "Chest_Wall",
        'Pectoral_major_muscle': "Pectoral major muscle",
        'no_fixation': "No fixation",
        'other': "Other"
    }
    metastasis_type_dict = {
        'tbd': "To be filled",
        'diffuse': "Diffuse",
        'sectoral': "Sectoral",
        'other': "Other"
    }
    discharge_type_dict = {
        'tbd': "To be filled",
        'milky': "Milky",
        'serous': "Serous",
        'brown': "Brown",
        'blood': "Blood",
        'other': "Other"
    }
    skin_change_type_dict = {
        'tbd': "To be filled",
        'dimpling': "Dimpling",
        'ulceration': "Ulceration",
        'discoloration': "Discoloration",
        'eczema': "Eczema",
        'edema': "Edema",
        'redness': "Redness",
        'peau': "Peau d'orange",
        'other': "Other"
    }
    contalateral_breast_dict = {
        'tbd': "To be filled",
        'normal': "Normal",
        'diffuse mastitis': "diffuse mastitis",
        'Localised Mastitis': "Localised Mastitis",
        'other': "Other"
    }
    arm_edema_dict = {
        'tbd': "To be filled",
        'right': "Right",
        'left': "Left",
        'not present': "Not present",
        'both': "Both",
        'other': "Other"
    }
    usg_abdomen_dict = {
        'nd': "Not Done",
        'normal': "Normal",
        'abnormal': "Abnormal"
    }
    cect_abdomen_thorax_dict = {
        'nd': "Not done",
        'normal': "Normal",
        'visceral metastasis': "Visceral Metastasis"
    }
    pet_scan_dict = {
        'nd': "Not Done",
        'normal': "Normal",
        'visceral metastasis': "Visceral Metastasis",
        'skeletal metastasis': "Skeletal Metastasis"
    }
    bone_scan_dict = {
        'nd': "Not Done",
        'normal': "Normal",
        'skeletal metastasis': "Skeletal Metastasis"
    }

    palpable_choice = CommonDict.generate_choice(palpable_dict)
    lump_size_choice = CommonDict.generate_choice(lump_size_dict)
    lump_number_choice = CommonDict.generate_choice(lump_number_dict)
    lump_consistency_choice = CommonDict.generate_choice(lump_consistency_dict)
    lump_fixity_choice = CommonDict.generate_choice(lump_fixity_dict)
    metastasis_type_choice = CommonDict.generate_choice(metastasis_type_dict)
    discharge_type_choice = CommonDict.generate_choice(discharge_type_dict)
    skin_change_type_choice = CommonDict.generate_choice(skin_change_type_dict)
    contalateral_breast_choice = CommonDict.generate_choice(
        contalateral_breast_dict)
    arm_edema_choice = CommonDict.generate_choice(arm_edema_dict)
    usg_abdomen_choice = CommonDict.generate_choice(usg_abdomen_dict)
    cect_abdomen_thorax_choice = CommonDict.generate_choice(
        cect_abdomen_thorax_dict)
    pet_scan_choice = CommonDict.generate_choice(pet_scan_dict)
    bone_scan_choice = CommonDict.generate_choice(bone_scan_dict)
Example #5
0
class MammographyDict():
    def __init__(self, key, value):
        self.key = key
        self.value = value
    mammo_location_dict = {'tbd':"To be filled",'pccm':"PCCM", 'out':"Outside",'other': "Other"}
    mammo_details_dict = {'tbd':"To be filled","N": "No","Y":"Yes",}
    mammo_breast_density_dict = {'tbd':"To be filled",'NA': "Information not available in this report",
                                 'a':"a. The breasts are almost entirely fatty", 'b': "b. There are scattered areas of "
                                 "fibroglandular density", 'c': "c. The breasts are heterogeneously dense, which may "
                                 "obscure small masses", 'd': "d. The breasts are extremely dense which lowers the "
                                 "sensitivity of mammography", 'other': "Other"}
    mammo_mass_depth_dict = {'tbd':"To be filled",'NA':"Not Present",'anterior':"Anterior",'middle':"Middle",
                             'posterior':"Posterior",
                             'other':"Other"}
    mammo_mass_shape_dict= {'tbd':"To be filled",'NA':"Not Present",'oval':"Oval", 'round':"Round", 'irreg':"Irregular",
                            'other':"Other"}
    mammo_mass_margin_dict = {'tbd':"To be filled",'NA':"Not Present",'circ':"Circumscribed", 'obsc':"Obscured",
                              'micro':"Microlobulated",
                              'ind':"Indistinct", 'spic':"Spiculated", 'other':"Other"}
    mammo_mass_density_dict = {'tbd':"To be filled",'NA':"Not Present",'high':"High density",'equal':"Equal density",
                               'low': "Low density",
                               'fat':"Fat-containing", 'other': "Other"}
    mammo_calcification_type_dict = {'tbd':"To be filled",'NA':"Not Present",'skin':"Skin",'vascular': "Vascular",
                                     'popcorn': "Coarse or 'Popcorn-like'", 'large': "Large Rod-like",
                                     'round':"Round and punctate", 'egg':"Eggshell or Rim",
                                     'dystrophic': "Dystrophic",'suture': "Suture",'amorphous': "Amorphous",'coarse':
                                     "Coarse Heterogeneous",'fine': "Fine Pleomorphic", 'fine_linear':
                                     "Fine Linear or Fine Linear Branching",'other': "Other"}
    mammo_calcification_diagnosis_dict = {'tbd':"To be filled",'NA':"Not Present",'benign':"Typically Benign",
                                          'suspicious':"Suspicious Morphology"}
    mammo_calcification_distribution_dict = {'tbd':"To be filled",'NA':"Not Present",'diffuse':"Diffuse",
                                             'regional':"Regional",
                                             'grouped':"Grouped",'linear':"Linear", 'segmental':"Segmental"}
    mammo_assym_type_dict = {'tbd':"To be filled",'NA':"Not Present",'assym':"Asymmetry", 'global':"Global asymmetry",
                             'focal':"Focal asymmetry", 'developing':"Developing asymmetry", 'other':"Other"}
    mammo_intra_mammary_lymph_nodes_dict = {'tbd':"To be filled","N":"Intra-mammary lymph nodes absent",
                                            "Y":"Intra-mammary lymph nodes present"}
    mammo_lesion_dict = {'tbd':"To be filled","N":"Skin Lesion not present", "Y":"Skin Lesion present"}
    abvs_diagnosis_dict = {'tbd':"To be filled",'follow_up':'Not Present in Report','normal':"Normal", 'benign':"Benign",
                          'suspicious':"Suspicious", 'cancer':"Diagnostic for Cancer"}
    sonomammo_tissue_dict = {'tbd':"To be filled", 'a': "a. Homogeneous background echotexture – fat",
                        'b':"b. Homogeneous background echotexture – fibroglandular",
                        'c': "c. Heterogeneous background echotexture", 'na':"Not available in Report",
                        'other': 'Other'}
    sonomammo_calc_dict = {'tbd':"To be filled",'no':"Not Present",'mass':"Calcifications in a mass", 'outside':"Calcifications outside of a mass",
                           'intra':"Intraductal calcifications", 'other':'Other'}
    sonomammo_skin_dict = {'tbd':"To be filled", 'na':"Not in Report", 'no':"No Skin Changes", 'thick':"Skin thickening", 'retract':"Skin retraction"}
    sonomammo_vascularity_dict = {'tbd':"To be filled",'na':"Not in Report", 'no':"Absent", 'internal':"Internal vascularity",
                                  'rim':"Vessels in rim", 'other':"Other"}
    sonomammo_elast_dict = {'tbd':"To be filled",'na':"Not in report", 'soft':"Soft", 'intermediate': "Intermediate", 'hard':"Hard",
                            'other':"Other"}
    sonomammo_hilum_dict  = {'tbd':"To be filled",'normal':'Normal Lymph Node','na':'Not in report','lost':"Lost", 'thin':"Thin",
                             'preserved':"Preserved", 'other':"Other"}

    sonomammo_lymph_ax_vasc_dict = {'tbd':"To be filled",'normal':'Normal Lymph Node','na':'Not in report', 'ventral':"Ventral",
                                    'peri':"Peripheral", 'other':"Other"}
    sonomammo_other_findings_dict = {'tbd':"To be filled",'no':"No other findings",'na':"Not mentioned in report",
                                     'cyst':"Simple cyst", 'microcyst':"Clustered microcysts",'complex':"Complicated cyst",
                                     'mass':"Mass in or on skin",'foriegn':"Foreign body including implants",
                                     'vasc':"Vascular abnormalities",'avm':"AVMs (arteriovenous malformations/pseudoaneurysms)",
                                     'mondor':"Mondor disease",'fluid':"Postsurgical fluid collection",'fat':"Fat necrosis",
                                     'other':"Other"}
    sono_mass_shape_dict = {'tbd':"To be filled",'oval':"Oval", 'round':"Round", 'irregular':"Irregular", 'other':"Other"}
    sono_orientation_dict= {'tbd':"To be filled",'na':'Not in report','parallel':"Parallel", 'not':"Not parallel"}
    sono_mass_margin_dict = {'tbd':"To be filled", 'cirumc':"Circumscribed", 'not':"Not circumscribed",'indistinct':"Indistinct",
                             'angular':"Angular", 'micro':"Microlobulated", 'spiculated':"Spiculated"}
    sono_mass_echo_dict = {'tbd':"To be filled", 'anechoic':"Anechoic",'hyper':"Hyperechoic",'complex':"Complex cystic and solid",
                           'hypo':"Hypoechoic",'iso':"Isoechoic", 'hetero':"Heterogeneous", 'other':"Other"}
    sono_posterior_dict = {'tbd':"To be filled", 'no': "No posterior features", 'enhance':"Enhancement", 'shadow':"Shadowing",
                           'combinde':"Combined pattern", 'other':"Other"}
    mammo_location_choice = CommonDict.generate_choice(mammo_location_dict)
    mammo_details_choice = CommonDict.yes_no_choice
    mammo_breast_density_choice = CommonDict.generate_choice(mammo_breast_density_dict)
    mammo_mass_present_choice = CommonDict.yes_no_choice
    mammo_mass_location_right_breast_choice = CommonDict.breast_location_choice
    mammo_mass_location_left_breast_choice =  CommonDict.breast_location_choice
    mammo_mass_depth_choice = CommonDict.generate_choice(mammo_mass_depth_dict)
    mammo_mass_dist_choice = CommonDict.distance_from_nipple_choice
    mammo_mass_shape_choice = CommonDict.generate_choice(mammo_mass_shape_dict)
    mammo_mass_margin_choice = CommonDict.generate_choice(mammo_mass_margin_dict)
    mammo_mass_density_choice = CommonDict.generate_choice(mammo_mass_density_dict)
    mammo_calcification_present_choice = CommonDict.yes_no_choice
    mammo_calc_location_right_breast_choice =  CommonDict.breast_location_choice
    mammo_calc_location_left_breast_choice =  CommonDict.breast_location_choice
    mammo_calc_depth_choice = CommonDict.generate_choice(mammo_mass_depth_dict)
    mamo_calc_dist_choice = CommonDict.distance_from_nipple_choice
    mammo_calcification_type_choice = CommonDict.generate_choice(mammo_calcification_type_dict)
    mammo_calcification_diagnosis_choice = CommonDict.generate_choice( mammo_calcification_diagnosis_dict)
    mammo_arch_present_choice = CommonDict.yes_no_choice
    mammo_arch_location_right_breast_choice = CommonDict.breast_location_choice
    mammo_arch_location_left_breast_choice =  CommonDict.breast_location_choice
    mammo_arch_depth_choice = CommonDict.generate_choice(mammo_mass_depth_dict)
    mammo_arch_dist_choice = CommonDict.distance_from_nipple_choice
    mammo_assym_present_choice = CommonDict.yes_no_choice
    mammo_assym_location_right_breast_choice = CommonDict.breast_location_choice
    mammo_assym_location_left_breast_choice = CommonDict.breast_location_choice
    mammo_assym_depth_choice = CommonDict.generate_choice(mammo_mass_depth_dict)
    mammo_assym_type_right_breast_choice = CommonDict.generate_choice(mammo_assym_type_dict)
    mammo_assym_type_left_breast_choice = CommonDict.generate_choice(mammo_assym_type_dict)
    mammo_intra_mammary_lymph_nodes_choice = CommonDict.generate_choice(mammo_intra_mammary_lymph_nodes_dict)
    mammo_lesion_choice = CommonDict.generate_choice(mammo_lesion_dict)
    mammo_lesion_right_breast_choice =  CommonDict.breast_location_choice
    mammo_lesion_left_breast_choice =  CommonDict.breast_location_choice
    mammo_birad_choice =  CommonDict.birad_choice
    mammo_status_choice = CommonDict.form_status_choice
    abvs_diagnosis_choice = CommonDict.generate_choice(abvs_diagnosis_dict)
    sonomammo_tissue_choice = CommonDict.generate_choice(sonomammo_tissue_dict)
    sonomammo_calc_choice = CommonDict.generate_choice(sonomammo_calc_dict)
    sonomammo_skin_choice = CommonDict.generate_choice(sonomammo_skin_dict)
    sonomammo_vascularity_choice=CommonDict.generate_choice(sonomammo_vascularity_dict)
    sonomammo_elast_choice = CommonDict.generate_choice(sonomammo_elast_dict)
    sonomammo_hilum_choice = CommonDict.generate_choice(sonomammo_hilum_dict)
    sonomammo_lymph_ax_vasc_choice = CommonDict.generate_choice(sonomammo_lymph_ax_vasc_dict)
    sonomammo_other_findings_choice = CommonDict.generate_choice(sonomammo_other_findings_dict)
    sono_mass_shape_choice = CommonDict.generate_choice(sono_mass_shape_dict)
    sono_orientation_choice= CommonDict.generate_choice(sono_orientation_dict)
    sono_mass_margin_choice=CommonDict.generate_choice(sono_mass_margin_dict)
    sono_mass_echo_choice = CommonDict.generate_choice(sono_mass_echo_dict)
    sono_posterior_choice = CommonDict.generate_choice(sono_posterior_dict)
Example #6
0
class PatientHistoryDict():
    def __init__(self, key, value):
        self.key = key
        self.value = value

    diet_dict = {'tbd': "To be filled", 'veg': "Vegetarian",
                 'non-veg': "Non-Vegetarian", 'egg': "Ovo-Vegetarian", 'other': "Other"}
    period_type_dict = {'tbd': "To be filed", 'regular': "Regular",
                        'irregular': "Irregular", 'other': "Other"}
    menopausal_status_dict = {'tbd': "To be filled", 'pre': "Pre Menopausal", 'post': "Post Menopausal",
                              'peri': "Peri Menopausal", 'other': "Other"}
    tobacco_dict = {'tbd': "To be filled", 'no': 'No exposure', 'passive': 'Passive', 'active': 'Active',
                    'pa': 'Passive and Active'}
    tobacco_type_passive_dict = {'tbd': "To be filled", 'no': 'No exposure', 'home': "Home", 'work': "Work", 'commute': "Commute",
                                 'social': "Social Interactions", 'other': 'Other'}
    tobacco_type_dict = {'tbd': "To be filled", 'no': 'No exposure', 'cig': "Cigarette", 'beedi': "Beedi", 'gutka': "Gutkha",
                         'pan_masala': "Pan Masala", 'jarda': "Jarda/Maava", 'hookah': "Hookah", 'patch': "Nicotine Patch", 'mishri': "Mishri",
                         'other': "Other"}
    yes_no_dict = {'tbd': "To be filled",
                   "N": "No", "Y": "Yes", 'other': "Other"}
    current_complain_dict = {'tbd': "To be filled", 'self': "Self", 'physician': "Physician", 'screening_camp_id': "Screening Camp ID",
                             'other': "Other"}
    annual_income_dict = {'tbd': "To be filled", '1': "0-2.5 lakhs", '2': "2.5-5 lakhs", '3': "5-10 lakhs",
                          '4': "more than 10 lakhs"}
    metastasis_symptoms_dict = {'tbd': "To be filled", 'N': "Absent", 'jauncice': "Jaundice", 'bone pain': "Bone Pain", 'cough': "Cough",
                                'weight loss': "Weight Loss", 'headache': "Headache"}
    treatment_type_dict = {'tbd': "To be filled", 'surgery': "Surgery", 'radiation': "Radiation",
                           'chemotherapy': "Chemotherapy", 'hormone': "Hormone",
                           'alternative therapy': "Alternative Therapy", 'home remedies': "Home Remedies",
                           'none': "None", 'other': "Other"}
    degree_of_relation_dict = {'tbd': "To be filled", 'i': "Immediate Family", 'm': "Maternal Family", 'p': "Paternal Family",
                               'other': "Other"}
    marital_status_dict = {'tbd': "To be filled",
                           'married': "Married", 'single': "Single", 'other': "Other"}
    symptom_absent_present_dict = {
        'tbd': "To be filled", 'absent': "Absent", 'other': "Present"}
    diet_choice = CommonDict.generate_choice(diet_dict)
    tobacco_choice = CommonDict.generate_choice(tobacco_dict)
    tobacco_type_passive_choice = CommonDict.generate_choice(
        tobacco_type_passive_dict)
    tobacco_type_choice = CommonDict.generate_choice(tobacco_type_dict)
    current_complain_choice = CommonDict.generate_choice(current_complain_dict)
    annual_income_choice = CommonDict.generate_choice(annual_income_dict)
    period_type_choice = CommonDict.generate_choice(period_type_dict)
    menopausal_status_choice = CommonDict.generate_choice(
        menopausal_status_dict)
    metastasis_symptoms_choice = CommonDict.generate_choice(
        metastasis_symptoms_dict)
    treatment_type_choice = CommonDict.generate_choice(treatment_type_dict)
    degree_of_relation_choice = CommonDict.generate_choice(
        degree_of_relation_dict)
    marital_status_choice = CommonDict.generate_choice(marital_status_dict)
    symptom_absent_present_choice = CommonDict.generate_choice(
        symptom_absent_present_dict)
class SurgeryReportDict():
    def __init__(self, key, value):
        self.key = key
        self.value = value

    location_of_lesion_dict = {
        'tbd': "To be done",
        'left': "Left",
        'right': "Right",
        'bilateral': "Bilateral",
        'other': "Other"
    }
    incision_dict = {
        'tbd': "To be done",
        'inframammary_fold_incision': "Inframammary Fold Incision",
        'lateral_fold': "Lateral Fold",
        'lateral_crease': "Lateral Crease",
        'wise_pattern': "Wise Pattern",
        'radial': "Radial",
        'oblique': "Oblique",
        'transveres_oblique': "Transverse Oblique",
        'oblique_with_supra_aerolar': "Oblique with supra areolar",
        'circum_areolar_at_margin': "Circum areolar at margin",
        'circum_areolar_away_from_margin': "Circum areolar away from margin",
        'axillary': "Axillary",
        'vertical_scar': "Vertical scar",
        'other': "Other"
    }
    masectomy_type_dict = {
        'tbd': "To be done",
        'aereolar_sparing': "Aereolar Sparing",
        'nipple_sparing': "Nipple Sparing",
        'skin_sparing': "Skin Sparing",
        'mrm': "Modified Radical Masectomy",
        'other': "Other"
    }
    type_of_surgery_ibr_dict = {
        'tbd': "To be done",
        'non_sling_conventional_ibrs': "Non Sling Conventional IBRS",
        'sling_alds': "Sling ALDS",
        'advanced_sling_aalds': "Advanced sling AALDS",
        'ld_flap_and_implant': "LD Flap+Implant",
        'tdap_and_implant': "TDAP+Implant",
        'licap_and_implant': "LICAP+Implant",
        'other': "Other"
    }
    type_of_surgery_cbs_dict = {
        'tbd': "To be done",
        'conventional_surgery': "Conventional Surgery",
        'oncoplastic_surgery': "Oncoplastic Surgery",
        'other': "Other"
    }
    type_of_conventional_surgery_dict = {
        'tbd': "To be done",
        'NA': "Not Done",
        'lumpectomy': "Lumpectomy",
        'quadrantectomy': "Quadrantectomy",
        'wedge_resection': "Wedge Resection",
        'other': "Other"
    }
    implant_used_dict = {
        'tbd': "To be done",
        'fixed_volume_smooth': "Fixed volume: smooth",
        'fixed_volume_textured': "Fixed volume: textured",
        'fixed_volume_microtextured': "Fixed Volume: Microtextured",
        'dual_lumen': "Dual Lumen",
        'other': "Other"
    }
    level_oncoplastic_dict = {
        'tbd': "To be done",
        '1': "1",
        '2': "2",
        '3': "3",
        'other': "Other"
    }
    type_levelone_oncoplastic_dict = {
        'tbd': "To be done",
        'NA': "Not done",
        'simple_oncoplastic': "Simple Oncoplastic or mammoplasty",
        'volume_displacement': "Volume Displacement",
        'other': "Other"
    }
    type_flap_used_oncoplastic_levelone_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'grisotti': "Grisotti Flap",
        'round_block': "Round Block",
        'batwing_procedure': "Batwing Procedure",
        'other': "other"
    }
    type_therapeytic_type_leveltwo_oncoplastic_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'simple': "Simple Therapeutic",
        'extreme': "Extreme Therapeutic",
        'other': "other"
    }
    plan_simple_therapeutic_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'wise_pattern': "Wise Pattern",
        'vertical_scar': "Vertical scar",
        'other': "other"
    }
    pedicle_type_simple_therapeutic_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'lower_pedicle': "Lower pedicle",
        'superior_pedicle': "Superior pedicle",
        'superio_medial_pedicle': "Superio-medial pedicle",
        'lateral_pedicle': "Lateral pedicle",
        'dual_pedicle': "Dual Pedicle",
        'other': "other"
    }
    tumour_filled_by_extreme_therapeutic_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'extended_primary_pedicle': "Extended Primary pedicle",
        'secondary_pedicle': "Secondary pedicle",
        'other': "Other"
    }
    flap_used_levelthree_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'local_thoraco_epigastric': "Local thoraco epigastric flap",
        'local_licap': "Local LICAP",
        'Local_tdap': "Local TDAP",
        'local_aicap': "Local AiCAP",
        'local_micap': "Local MiCAP",
        'ld_flaps': "LD Flaps",
        'mini_ld': "Mini LD",
        'other': "Other"
    }
    type_of_surgery_contralateral_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'symmetrisation_same': "Symmetrisation;same as other",
        'symmetrisation_different': "Symmetrisation;different than other",
        'prophylactic_masectomy_wiht_reconstruction':
        "Prophylactic masectomy with reconstruction",
        'other': "Other"
    }
    primary_pedicle_extreme_therapeutic_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'lower': "Lower pedicle",
        'superior': "Superior pedicle",
        'superio_medial': "Superio-medial pedicle",
        'lateral': "Lateral pedicle",
        'inferior': "Inferior pedicle",
        'inferior medial': "Inferior medial pedicle",
        'inferior_medial_lateral': "Inferior medial lateral pedicle",
        'other': "other"
    }
    secondary_pedicle_extreme_therapeutic_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'inferior': "Inferior pedicle",
        'inferior_lateral': "Inferior lateral pedicle",
        'inferior_lateral_medial': "Inferior lateral medial pedicle",
        'superior': "Superior pedicle",
        'superior_medial': "Superior medial pedicle",
        'inferior_medial': "Inferior medial pedicle",
        'other': "other"
    }
    nodes_guided_by_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'palpation': "Palpation",
        'usg_guided': "USG guided",
        'wire_placement': "Wire placement guided",
        'gamma_camera': "Gamma camera guided",
        'blue_dye': "Blue dye",
        'other': "Other"
    }
    sample_sent_from_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'senital_node': "Senital Node",
        'under_nipple_surface': "Under nipple surface",
        'margin_additional': "Margin additional",
        'tumour_free_margin': "Tumour free margin",
        'any_other_specimen': "Any other specimen",
        'other': "Other"
    }
    nodes_excised_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'senital': "Senital Node",
        'axillary': "Axillary Node",
        'senital_axillary': "Senital and axillary",
        'other': "Other"
    }
    level_lymph_node_excised_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        '1': "Level 1",
        '2': "Level 2",
        '3': "Level 3",
        'other': "other"
    }
    post_surgery_plan_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'chemotherapy': "Chemotherapy",
        'radiology': "Radiology",
        'other': "Other"
    }
    intervention_type_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'surgical': "Surgical",
        'non_surgical': "Non Surgical"
    }
    location_recurrence_dict = {
        'tbd': "To be done",
        'NA': "Not available",
        'loco_regional': "Loco regional",
        'breast': "Breast",
        'axilla': "Axilla",
        'distant': "Distant",
        'other': "Other"
    }
    labelling_senitinel_node_dict = {
        'tbd': "To be done",
        'NA': "Not done",
        'isotope': "Isotope",
        'blue_dye': "Blue dye",
        'isotope_blue_dye': "Isotope and Blue dye",
        'other': "Other"
    }
    location_of_lesion_choice = CommonDict.generate_choice(
        location_of_lesion_dict)
    incision_choice = CommonDict.generate_choice(incision_dict)
    masectomy_type_choice = CommonDict.generate_choice(masectomy_type_dict)
    type_of_surgery_ibr_choice = CommonDict.generate_choice(
        type_of_surgery_ibr_dict)
    implant_used_choice = CommonDict.generate_choice(implant_used_dict)
    type_of_surgery_cbs_choice = CommonDict.generate_choice(
        type_of_surgery_cbs_dict)
    type_of_conventional_surgery_choice = CommonDict.generate_choice(
        type_of_conventional_surgery_dict)
    level_oncoplastic_choice = CommonDict.generate_choice(
        level_oncoplastic_dict)
    type_levelone_oncoplastic_choice = CommonDict.generate_choice(
        type_levelone_oncoplastic_dict)
    type_flap_used_oncoplastic_levelone_choice = CommonDict.generate_choice(
        type_flap_used_oncoplastic_levelone_dict)
    type_therapeytic_type_leveltwo_oncoplastic_choice = CommonDict.generate_choice(
        type_therapeytic_type_leveltwo_oncoplastic_dict)
    plan_simple_therapeutic_choice = CommonDict.generate_choice(
        plan_simple_therapeutic_dict)
    pedicle_type_simple_therapeutic_choice = CommonDict.generate_choice(
        pedicle_type_simple_therapeutic_dict)
    tumour_filled_by_extreme_therapeutic_choice = CommonDict.generate_choice(
        tumour_filled_by_extreme_therapeutic_dict)
    flap_used_levelthree_choice = CommonDict.generate_choice(
        flap_used_levelthree_dict)
    type_of_surgery_contralateral_choice = CommonDict.generate_choice(
        type_of_surgery_contralateral_dict)
    primary_pedicle_extreme_therapeutic_choice = CommonDict.generate_choice(
        primary_pedicle_extreme_therapeutic_dict)
    secondary_pedicle_extreme_therapeutic_choice = CommonDict.generate_choice(
        secondary_pedicle_extreme_therapeutic_dict)
    nodes_guided_by_choice = CommonDict.generate_choice(nodes_guided_by_dict)
    sample_sent_from_choice = CommonDict.generate_choice(sample_sent_from_dict)
    nodes_excised_choice = CommonDict.generate_choice(nodes_excised_dict)
    level_lymph_node_excised_choice = CommonDict.generate_choice(
        level_lymph_node_excised_dict)
    post_surgery_plan_choice = CommonDict.generate_choice(
        post_surgery_plan_dict)
    intervention_type_choice = CommonDict.generate_choice(
        intervention_type_dict)
    location_recurrence_choice = CommonDict.generate_choice(
        location_of_lesion_dict)
    labelling_senitinel_node_choice = CommonDict.generate_choice(
        labelling_senitinel_node_dict)
Example #8
0
class BiopsyDict():
    def __init__(self, key, value):
        self.key = key
        self.value = value

    biopsy_reason_dict = {
        'tbd': "To be filled",
        'diagnostic': "Diagnostic",
        'follow_up': "Follow-up",
        'nact_follow-up': "NACT follow up",
        'recurrence': "Recurrence",
        'other': "Other"
    }
    biopsy_site_dict = {
        'tbd': "To be filled",
        'left_breast': "Left Breast",
        'right_breast': "Right Breast",
        'left_axillary': "Left Axillary",
        'right_axillary': "Right Axillary",
        'other': "Other"
    }
    biopsy_block_id_dict = {
        'tbd': "To be filled",
        'physically_present_at_pccm':
        "If the blocks are physically present at PCCM enter the block id from the blocks",
        'not_physically_present_at_pccm':
        "If the blocks are not physically present at PCCM enetr the block ID from the biopsy report",
        'no_source_of_block':
        "If there is no source for the block ID mention as requires follow up",
        'other': "Other"
    }  #major doubt
    biopsy_block_source_dict = {
        'tbd': "To be filled",
        'ag_diagnostics': "A.G. Diagnostics",
        'ruby_hall_clinic': "Ruby Hall Clinic",
        'srl_pathlab': "SRL Pathlab",
        'golwilkar_lab': "Golwilkar Lab",
        'other': "Other"
    }
    biopsy_type_dict = {
        'tbd': "To be filled",
        "direct": "Direct",
        "usg_guided": "USG Guided",
        "vab": "VAB",
        "trucut": "Tru-cut",
        "stereo": "Steriotactic",
        'other': "Other"
    }

    biopsy_custody_pccm_dict = {
        'tbd': "To be filled",
        "Y": "In PCCM Custody",
        "N": "Not in PCCM custody"
    }
    tumour_grade_dict = {
        'tbd': "To be filled",
        "1": 'Grade 1',
        "2": "Grade 2",
        "3": "Grade 3"
    }
    lymphovascular_emboli_dict = {
        'tbd': "To be filled",
        "Y": "Lymphovascular Emboli Seen",
        "N": "No Lymphovascular Emboli Seen",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    dcis_biopsy_dict = {
        'tbd': "To be filled",
        "Y": "DCIS seen",
        "N": "DCIS not seen",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    tumour_er_dict = {
        'tbd': "To be filled",
        "pos": "Positive",
        "neg": "Negative",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    tumour_pr_dict = {
        'tbd': "To be filled",
        "pos": "Positive",
        "neg": "Negative",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    tumour_her2_dict = {
        'tbd': "To be filled",
        "pos": "Positive",
        "eqv": "Equivocal",
        "neg": "Negative",
        'report': 'Not done',
        'other': 'Other'
    }
    tumor_biopsy_fish_dict = {
        'tbd': "To be filled",
        'positive': "Positive",
        'negetive': "Negetive",
        'not_done': "Not Done",
        'other': 'Other'
    }
    fnac_dict = {
        'tbd': "To be filled",
        "Y": "Done",
        "N": "Not Done",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    fnac_location_dict = {
        'tbd': "To be filled",
        "rb": "Right",
        "lb": "Left",
        "both": "Both",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    fnac_diagnosis_dict = {
        'tbd': "To be filled",
        "normal": "Normal",
        "benign": "Benign",
        "malignant": "Malignant",
        'report': 'Not mentioned in Report',
        'other': 'Other'
    }
    surgery_type_dict = {
        'bcs': "Breast Conservation Surgery (BCS)",
        'tm': "Therapeutic Mammoplasty",
        'rm': "Reduction Mammoplasty",
        'reconstruction': "Reconstruction",
        'reco-mastectomy': "Reconstruction: Mastectomy",
        'reco:mrm': "Reconstruction: Modified Radical Mastectomy",
        'reco:implant': "Reconstruction: Implant",
        'wle': "Wide Local Excision",
        'other': "Other",
    }
    surgery_diagnosis_dict = {
        'tbd': "To be filled",
        'dcis': "Ductal carcinoma in situ",
        "lcs": "Lobular Carcinoma in Situ (LCS)",
        "idc": "Invasive Ductal Carcinoma (IDC)",
        'ilc': "Invasive Lobular Carcinoma (ILC)",
        'gm': "Granulamatous Mastitis",
        'papc': "Papillary Carcinoma",
        'phyc': "Phylloid Carcinoma",
        'imc': "Invasive Mammary Carcinoma",
        'ibc': "Invasive Breast Carcinoma",
        'other': 'Other'
    }
    lymphovascular_invasion_dict = {
        'tbd': "To be filled",
        'seen': "Seen",
        'not_seen': "Not seen",
        'data_not_entered': "Data not entered",
        'other': "Other"
    }
    pathological_staging_pt_dict = {
        'tbd': "To be filled",
        '1': "1",
        '2': "2",
        '3': "3",
        '4': "4",
        'other': "Other"
    }
    pathological_staging_m_dict = {
        'tbd': "To be filled",
        '0': "0",
        '1': "1",
        'other': "Other"
    }
    pathological_staging_p_stage_dict = {
        'tbd': "To be filled",
        '1': "1",
        '2': "2",
        '3': "3",
        'other': "Other"
    }
    nact_naht_dict = {
        'tbd': "To be filled",
        'nact': "NACT",
        'naht': "NAHT",
        'both': "Both",
        'none': "None",
        'other': "Other"
    }
    surgery_dict = {
        'tbd': "To be filled",
        'yes': "Yes",
        'no': "No",
        'not_done': "Not done",
        'other': "Other"
    }

    biopsy_reason_choice = CommonDict.generate_choice(biopsy_reason_dict)
    biopsy_site_choice = CommonDict.generate_choice(biopsy_site_dict)
    biopsy_block_id_choice = CommonDict.generate_choice(biopsy_block_id_dict)
    biopsy_block_source_choice = CommonDict.generate_choice(
        biopsy_block_source_dict)
    biopsy_type_choice = CommonDict.generate_choice(biopsy_type_dict)
    biopsy_custody_pccm_choice = CommonDict.generate_choice(
        biopsy_custody_pccm_dict)
    tumour_grade_choice = CommonDict.generate_choice(tumour_grade_dict)
    lymphovascular_emboli_choice = CommonDict.generate_choice(
        lymphovascular_emboli_dict)
    dcis_biopsy_choice = CommonDict.generate_choice(dcis_biopsy_dict)
    tumour_er_choice = CommonDict.generate_choice(tumour_er_dict)
    tumour_pr_choice = CommonDict.generate_choice(tumour_pr_dict)
    tumour_her2_choice = CommonDict.generate_choice(tumour_her2_dict)
    tumor_biopsy_fish_choice = CommonDict.generate_choice(
        tumor_biopsy_fish_dict)
    fnac_choice = CommonDict.generate_choice(fnac_dict)
    fnac_location_choice = CommonDict.generate_choice(fnac_location_dict)
    fnac_diagnosis_choice = CommonDict.generate_choice(fnac_diagnosis_dict)
    surgery_type_choice = CommonDict.generate_choice(surgery_type_dict)
    surgery_diagnosis_choice = CommonDict.generate_choice(
        surgery_diagnosis_dict)
    lymphovascular_invasion_choice = CommonDict.generate_choice(
        lymphovascular_invasion_dict)
    pathological_staging_pt_choice = CommonDict.generate_choice(
        pathological_staging_pt_dict)
    pathological_staging_m_choice = CommonDict.generate_choice(
        pathological_staging_m_dict)
    pathological_staging_p_stage_choice = CommonDict.generate_choice(
        pathological_staging_p_stage_dict)
    nact_naht_choice = CommonDict.generate_choice(nact_naht_dict)
    surgery_choice = CommonDict.generate_choice(surgery_dict)