Estimation of the radiation dose from radiotherapy for skin haemangiomas in childhood: the ICTA software for epidemiology.

Radium applicators and pure beta emitters have been widely used in the past to treat skin haemangioma in early childhood. A well defined relationship between the low doses received from these applicators and radiation-induced cancers requires accurate dosimetry. A human-based CT scan phantom has been used to simulate every patient and treatment condition and then to calculate the source target distance when radium and pure beta applicators were used. The effective transmission factor psi(r) for the gamma spectrum emitted by the radium sources applied on the skin surface was modelled using Monte Carlo simulations. The well-known quantization approach was used to calculate gamma doses delivered from radium applicators to various anatomical points. For 32P, 90Sr/90Y applicators and 90Y needles we have used the apparent exponential attenuation equation. The dose calculation algorithm was integrated into the ICTA software (standing for a model that constructs an Individualized phantom based on CT slices and Auxological data), which has been developed for epidemiological studies of cohorts of patients who received radium and beta-treatments for skin haemangioma. The psi(r) values obtained for radium skin applicators are in good agreement with the available values in the first 10 cm but higher at greater distances. Gamma doses can be calculated with this algorithm at 165 anatomical points throughout the body of patients treated with radium applicators. Lung heterogeneity and air crossed by the gamma rays are considered. Comparison of absorbed doses in water from a 10 mg equivalent radium source simulated by ICTA with those measured at the Radiumhemmet, Karolinska Hospital (RAH) showed good agreement, but ICTA estimation of organ doses did not always correspond those estimated at the RAH. Beta doses from 32P, 90Sr/90Y applicators and 90Y needles are calculated up to the maximum beta range (11 mm).

P53 germline mutations in childhood cancers and cancer risk for carrier individuals.

The family history of cancer in children treated for a solid malignant tumour in the Paediatric Oncology Department at Institute Gustave-Roussy, has been investigated. In order to determine the role of germline p53 mutations in genetic predisposition to childhood cancer, germline p53 mutations were sought in individuals with at least one relative (first- or second-degree relative or first cousin) affected by any cancer before 46 years of age, or affected by multiple cancers. Screening for germline p53 mutation was possible in 268 index cases among individuals fulfilling selection criteria. Seventeen (6.3%) mutations were identified, of which 13 were inherited and four were de novo. Using maximum likelihood methods that incorporate retrospective family data and correct for ascertainment bias, the lifetime risk of cancer for mutation carriers was estimated to be 73% for males and nearly 100% for females with a high risk of breast cancer accounting for the difference. The risk of cancer associated with such mutations is very high and no evidence of low penetrance mutation was found. These mutations are frequently inherited but de novo mutations are not rare.

Individualized phantom based on CT slices and auxological data (ICTA) for dose estimations following radiotherapy for skin haemangioma in childhood.

BACKGROUND AND PURPOSE: Before 1974 about 5000 children were treated by radiotherapy at the Institut Gustave-Roussy (IGR) for a skin haemangioma. A human model whose characteristics are as close as possible to those of the patient at the time of the treatment is necessary to effectuate an accurate retrospective estimation of the radiation doses received at distant organs. METHODS: We have developed a software package which constructs an individualized phantom based on CT slices and auxological data (ICTA) for this purpose. A set of real CT slices is used to produce a 3-D representation of the human body which is then adjusted to fit the dimensions supplied by published auxological data relative to sex and age for each patient. One hundred sixty-one anatomical landmarks of epidemiological interest have been defined inside the phantom for dose estimation. RESULTS: The transverse, frontal and sagittal views of the phantom displayed permit accurate positioning of radioactive applicators. The software calculates the relevant parameters required for dose estimation based on the patient's probable anatomy.

BRCA1 sequence variations in 160 individuals referred to a breast/ovarian family cancer clinic. Institut Curie Breast Cancer Group.

An account of familial aggregation in breast/ovarian cancer has become possible with the identification of BRCA1 germ-line mutations. We evaluated, for 249 individuals registered with the Institut Curie in Paris, the prior probability that an individual carried a mutation that predisposes to these diseases. We chose 160 women for BRCA1 analysis: 103 with a family history of breast cancer and 57 with a family history of breast-ovarian cancer. To detect small mutations, we generated and analyzed 35 overlapping genomic PCR products that cover the coding portion of the gene, by using denaturing gradient gel electrophoresis. Thirty-eight truncating mutations (32 frameshifts, 4 nonsense mutations, and 2 splice variants) were observed in 15% of women with a family history of breast cancer only and in 40% of those with a history of breast-ovarian cancer. Twelve of 25 distinct truncating mutations identified were novel and unique. Most BRCA1 mutations that had been reported more than five times in the Breast Cancer Information Core were present in our series. One mutation (5149del4) observed in two apparently unrelated families most likely originates from a common ancestor. The position of truncating mutations did not significantly affect the ratio of the risk of breast cancer to that of ovarian cancer. In addition, 15 DNA variants (14 missense mutations and 1 neutral mutation) were identified, 9 of which were novel. Indirect evidence suggests that seven of these mutations are deleterious.