Automatic Diagnosis of Hepatocellular Carcinoma and Metastases Based on Computed Tomography Images.

Liver cancer, a leading cause of cancer mortality, is often diagnosed by analyzing the grayscale variations in liver tissue across different computed tomography (CT) images. However, the intensity similarity can be strong, making it difficult for radiologists to visually identify hepatocellular carcinoma (HCC) and metastases. It is crucial for the management and prevention strategies to accurately differentiate between these two liver cancers. This study proposes an automated system using a convolutional neural network (CNN) to enhance diagnostic accuracy to detect HCC, metastasis, and healthy liver tissue. This system incorporates automatic segmentation and classification. The liver lesions segmentation model is implemented using residual attention U-Net. A 9-layer CNN classifier implements the lesions classification model. Its input is the combination of the results of the segmentation model with original images. The dataset included 300 patients, with 223 used to develop the segmentation model and 77 to test it. These 77 patients also served as inputs for the classification model, consisting of 20 HCC cases, 27 with metastasis, and 30 healthy. The system achieved a mean Dice score of 87.65 % in segmentation and a mean accuracy of 93.97 % in classification, both in the test phase. The proposed method is a preliminary study with great potential in helping radiologists diagnose liver cancers.

Neurological hospitalisations in childhood cancer survivors treated before 2001: findings from the French Childhood Cancer Survivor Study cohort.

PURPOSE: Childhood cancer survivors (CCS) have an increased risk of developing late chronic diseases, which can be influenced by the cancer type and its treatment. These chronic diseases can be severe and disabling, typically emerging years to decades after treatment. These deficits negatively impact quality of life, intelligence quotient, and memory. This study investigated how much the cancer type and treatment could affect the neurological hospitalisations in the French Childhood Cancer Survivors Study (FCCSS). METHODS: We included 5579 childhood cancer survivors (CCS), diagnosed with solid tumours or lymphoma between 1945 and 2000, treated before 2001 and below the age of 21 years at initial treatment. The follow-up period was from 2006 to 2018. Hospitalisation data were obtained by linkage with the National Health Data System. We calculated the relative hospitalisation rate (RHRs) and absolute excess rate (AERs). Multivariable analyses were conducted using a Generalized Linear Model (GLM) with a Poisson distribution to estimate the association between neurological hospitalisation and patient characteristics. The expected number of hospitalisations served as an offset to compare the risk for FCCSS survivors with that of the reference population. Risk estimates were reported as relative risk (RR) with 95% confidence intervals. RESULTS: The hospitalisation rate for CCS was 114.2 per 10,000 person-years (PY), compared to 48.4 in the reference population. The highest hospitalisation rates were observed for epilepsy (AER = 27.1 per 10000 PY, 95%CI: 23.5-31.2 and RHR = 5.1, 95%CI 4.4-5.7). In multivariable analyses, central nervous system (CNS) tumours survivors had the highest relative risk (RR) of hospitalisation (RR = 9.4, 95%CI: 6.7-13.1) followed by neuroblastoma survivors (RR = 2.5, 95%CI: 1.7-3.7). In the whole population, survivors who received radiation to the head and neck had a significantly higher risk of hospitalisation (RR = 3.9, 95%CI: 3.3-4.7) compared to those who did not receive radiotherapy. CONCLUSIONS: Head and neck irradiation was identified as a strong risk factor for hospitalisation. This underlines the importance of implementing specific neurologic surveillance programs for at-risk individuals.

Radiation Doses Received by Major Organs at Risk in Children and Young Adolescents Treated for Cancer with External Beam Radiation Therapy: A Large-scale Study from 12 European Countries.

PURPOSE: Childhood cancer survivors, in particular those treated with radiation therapy, are at high risk of long-term iatrogenic events. The prediction of risk of such events is mainly based on the knowledge of the radiation dose received to healthy organs and tissues during treatment of childhood cancer diagnosed decades ago. We aimed to set up a standardized organ dose table to help former patients and clinicians in charge of long-term follow-up clinics. METHODS AND MATERIALS: We performed whole body dosimetric reconstruction for 2646 patients from 12 European countries treated between 1941 and 2006 (median, 1976). Most plannings were 2- or 3-dimensional. A total of 46% of patients were treated using Cobalt 60, and 41%, using a linear accelerator. The median prescribed dose was 27.2 Gy (IQ1-IQ3, 17.6-40.0 Gy). A patient-specific voxel-based anthropomorphic phantom with more than 200 anatomic structures or substructures delineated as a surrogate of each subject's anatomy was used. The radiation therapy was simulated with a treatment planning system based on available treatment information. The radiation dose received by any organ of the body was estimated by extending the treatment planning system dose calculation to the whole body, by type and localization of childhood cancer. RESULTS: The integral dose and normal tissue doses to most of the 23 considered organs increased between the 1950s and 1970s and decreased or plateaued thereafter. Whatever the organ considered, the type of childhood cancer explained most of the variability in organ dose. The country of treatment explained only a small part of the variability. CONCLUSIONS: The detailed dose estimates provide very useful information for former patients or clinicians who have only limited knowledge about radiation therapy protocols or techniques, but who know the type and site of childhood cancer, sex, age, and year of treatment. This will allow better prediction of the long-term risk of iatrogenic events and better referral to long-term follow-up clinics.

Radiomics-Based Classification of Tumor and Healthy Liver on Computed Tomography Images.

Liver malignancies, particularly hepatocellular carcinoma and metastasis, stand as prominent contributors to cancer mortality. Much of the data from abdominal computed tomography images remain underused by radiologists. This study explores the application of machine learning in differentiating tumor tissue from healthy liver tissue using radiomics features. Preoperative contrast-enhanced images of 94 patients were used. A total of 1686 features classified as first-order, second-order, higher-order, and shape statistics were extracted from the regions of interest of each patient's imaging data. Then, the variance threshold, the selection of statistically significant variables using the Student's t-test, and lasso regression were used for feature selection. Six classifiers were used to identify tumor and non-tumor liver tissue, including random forest, support vector machines, naive Bayes, adaptive boosting, extreme gradient boosting, and logistic regression. Grid search was used as a hyperparameter tuning technique, and a 10-fold cross-validation procedure was applied. The area under the receiver operating curve (AUROC) assessed the performance. The AUROC scores varied from 0.5929 to 0.9268, with naive Bayes achieving the best score. The radiomics features extracted were classified with a good score, and the radiomics signature enabled a prognostic biomarker for hepatic tumor screening.

Risk of subsequent gliomas and meningiomas among 69,460 5-year survivors of childhood and adolescent cancer in Europe: the PanCareSurFup study.

BACKGROUND: Childhood cancer survivors are at risk of subsequent gliomas and meningiomas, but the risks beyond age 40 years are uncertain. We quantified these risks in the largest ever cohort. METHODS: Using data from 69,460 5-year childhood cancer survivors (diagnosed 1940-2008), across Europe, standardized incidence ratios (SIRs) and cumulative incidence were calculated. RESULTS: In total, 279 glioma and 761 meningioma were identified. CNS tumour (SIR: 16.2, 95% CI: 13.7, 19.2) and leukaemia (SIR: 11.2, 95% CI: 8.8, 14.2) survivors were at greatest risk of glioma. The SIR for CNS tumour survivors was still 4.3-fold after age 50 (95% CI: 1.9, 9.6), and for leukaemia survivors still 10.2-fold after age 40 (95% CI: 4.9, 21.4). Following cranial radiotherapy (CRT), the cumulative incidence of a glioma in CNS tumour survivors was 2.7%, 3.7% and 5.0% by ages 40, 50 and 60, respectively, whilst for leukaemia this was 1.2% and 1.7% by ages 40 and 50. The cumulative incidence of a meningioma after CRT in CNS tumour survivors doubled from 5.9% to 12.5% between ages 40 and 60, and in leukaemia survivors increased from 5.8% to 10.2% between ages 40 and 50. DISCUSSION: Clinicians following up survivors should be aware that the substantial risks of meningioma and glioma following CRT are sustained beyond age 40 and be vigilant for symptoms.

Cumulative Absolute Risk of Subsequent Colorectal Cancer After Abdominopelvic Radiotherapy Among Childhood Cancer Survivors: A PanCareSurFup Study.

PURPOSE: Childhood cancer survivors are at the risk of developing subsequent colorectal cancers (CRCs), but the absolute risks by treatment modality are uncertain. We quantified the absolute risks by radiotherapy treatment characteristics using clinically accessible data from a Pan-European wide case-control study nested within a large cohort of childhood cancer survivors: the PanCareSurFup Study. METHODS: Odds ratios (ORs) from a case-control study comprising 143 CRC cases and 143 controls nested within a cohort of 69,460 survivors were calculated. These, together with standardized incidence ratios for CRC for this cohort and European general population CRC incidence rates and survivors' mortality rates, were used to estimate cumulative absolute risks (CARs) by attained age for different categories of radiation to the abdominopelvic area. RESULTS: Overall, survivors treated with abdominopelvic radiotherapy treatment (ART) were three times more likely to develop a subsequent CRC than those who did not receive ART (OR, 3.1 [95% CI, 1.4 to 6.6]). For male survivors treated with ART, the CAR was 0.27% (95% CI, 0.17 to 0.59) by age 40 years, 1.08% (95% CI, 0.69 to 2.34) by age 50 years (0.27% expected in the general population), and 3.7% (95% CI, 2.36 to 7.80) by age 60 years (0.95% expected). For female survivors treated with ART, the CAR was 0.29% (95% CI, 0.18 to 0.62) by age 40 years, 1.03% (95% CI, 0.65 to 2.22) by age 50 years (0.27% expected), and 3.0% (95% CI, 1.91 to 6.37) by age 60 years (0.82% expected). CONCLUSION: We demonstrated that by age 40 years survivors of childhood cancer treated with ART already have a similar risk of CRC as those age 50 years in the general population for whom population-based CRC screening begins in many countries. This information should be used in the development of survivorship guidelines for the risk stratification of survivors concerning CRC risk.

Surveillance after childhood cancer: are survivors with an increased risk for cardiomyopathy regularly followed-up?

BACKGROUND: We aimed to study adherence to cardiac screening in long-term childhood cancer survivors (CCS) at high risk of cardiomyopathy. METHODS: This study involved 976 5-year CCS at high risk for cardiomyopathy from the French Childhood Cancer Survivor Study. Determinants of adherence to recommended surveillance were studied using multivariable logistic regression models. Association of attendance to a long-term follow-up (LTFU) visit with completion of an echocardiogram was estimated using a Cox regression model. RESULTS: Among participants, 32% had an echocardiogram within the 5 previous years. Males (adjusted RR [aRR] 0.71, 95% CI 0.58-0.86), survivors aged 36-49 (aRR 0.79, 95% CI 0.64-0.98), Neuroblastoma (aRR 0.53, 95% CI 0.30-0.91) and CNS tumour survivors (aRR 0.43, 95% CI 0.21-0.89) were less likely to adhere to recommended surveillance. Attendance to an LTFU visit was associated with completion of an echocardiogram in patients who were not previously adherent to recommendations (HR 8.20, 95% CI 5.64-11.93). CONCLUSIONS: The majority of long-term survivors at high risk of cardiomyopathy did not adhere to the recommended surveillance. Attendance to an LTFU visit greatly enhanced the completion of echocardiograms, but further interventions need to be developed to reach more survivors.

Radiation exposure and leukaemia risk among cohorts of persons exposed to low and moderate doses of external ionising radiation in childhood.

BACKGROUND: Many high-dose groups demonstrate increased leukaemia risks, with risk greatest following childhood exposure; risks at low/moderate doses are less clear. METHODS: We conducted a pooled analysis of the major radiation-associated leukaemias (acute myeloid leukaemia (AML) with/without the inclusion of myelodysplastic syndrome (MDS), chronic myeloid leukaemia (CML), acute lymphoblastic leukaemia (ALL)) in ten childhood-exposed groups, including Japanese atomic bomb survivors, four therapeutically irradiated and five diagnostically exposed cohorts, a mixture of incidence and mortality data. Relative/absolute risk Poisson regression models were fitted. RESULTS: Of 365 cases/deaths of leukaemias excluding chronic lymphocytic leukaemia, there were 272 AML/CML/ALL among 310,905 persons (7,641,362 person-years), with mean active bone marrow (ABM) dose of 0.11 Gy (range 0-5.95). We estimated significant (P < 0.005) linear excess relative risks/Gy (ERR/Gy) for: AML (n = 140) = 1.48 (95% CI 0.59-2.85), CML (n = 61) = 1.77 (95% CI 0.38-4.50), and ALL (n = 71) = 6.65 (95% CI 2.79-14.83). There is upward curvature in the dose response for ALL and AML over the full dose range, although at lower doses (<0.5 Gy) curvature for ALL is downwards. DISCUSSION: We found increased ERR/Gy for all major types of radiation-associated leukaemia after childhood exposure to ABM doses that were predominantly (for 99%) <1 Gy, and consistent with our prior analysis focusing on <100 mGy.

Risk Factors for Primary Bone Cancer After Childhood Cancer: A PanCare Childhood and Adolescent Cancer Survivor Care and Follow-Up Studies Nested Case-Control Study.

PURPOSE: Radiation to the bone and exposure to alkylating agents increases the risk of bone cancer among survivors of childhood cancer, but there is uncertainty regarding the risks of bone tissue radiation doses below 10 Gy and the dose-response relationship for specific types of chemotherapy. METHODS: Twelve European countries contributed 228 cases and 228 matched controls to a nested case-control study within a cohort of 69,460 5-year survivors of childhood cancer. Odds ratios (ORs) of developing bone cancer for different levels of cumulative radiation exposure and cumulative doses of specific types of chemotherapy were calculated. Excess ORs were calculated to investigate the shape and extent of any dose-response relationship. RESULTS: The OR associated with bone tissue exposed to 1-4 Gy was 4.8-fold (95% CI, 1.2 to 19.6) and to 5-9 Gy was 9.6-fold (95% CI, 2.4 to 37.4) compared with unexposed bone tissue. The OR increased linearly with increasing dose of radiation (Ptrend < .001) up to 78-fold (95% CI, 9.2 to 669.9) for doses of ≥40 Gy. For cumulative alkylating agent doses of 10,000-19,999 and ≥20,000 mg/m2, the radiation-adjusted ORs were 7.1 (95% CI, 2.2 to 22.8) and 8.3 (95% CI, 2.8 to 24.4), respectively, with independent contributions from each of procarbazine, ifosfamide, and cyclophosphamide. Other cytotoxics were not associated with bone cancer. CONCLUSION: To our knowledge, we demonstrate-for the first time-that the risk of bone cancer is increased 5- to 10-fold after exposure of bone tissue to cumulative radiation doses of 1-9 Gy. Alkylating agents exceeding 10,000 mg/m2 increase the risk 7- to 8-fold, particularly following procarbazine, ifosfamide, and cyclophosphamide. These substantially elevated risks should be used to develop/update clinical follow-up guidelines and survivorship care plans.

Multi-Morbidity and Risk of Breast Cancer among Women in the UK Biobank Cohort.

(Multi-)Morbidity shares common biological mechanisms or risk factors with breast cancer. This study aimed to investigate the association between the number of morbidities and patterns of morbidity and the risk of female breast cancer. Among 239,436 women (40-69 years) enrolled in the UK Biobank cohort who had no cancer history at baseline, we identified 35 self-reported chronic diseases at baseline. We assigned individuals into morbidity patterns using agglomerative hierarchical clustering analysis. We fitted Cox models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for breast cancer risk. In total, 58.4% of women had at least one morbidity, and the prevalence of multi-morbidity was 25.8%. During a median 7-year follow-up, there was no association between breast cancer risk (5326 cases) and either the number of morbidities or the identified clinically relevant morbidity patterns: no-predominant morbidity (reference), psychiatric morbidities (HR = 1.04, 95%CI 0.94-1.16), respiratory/immunological morbidities (HR = 0.98, 95%CI 0.90-1.07), cardiovascular/metabolic morbidities (HR = 0.93, 95%CI 0.81-1.06), and unspecific morbidities (HR = 0.98, 95%CI 0.89-1.07), overall. Among women younger than 50 years of age only, however, there was a significant association with psychiatric morbidity patterns compared to the no-predominant morbidity pattern (HR = 1.25, 95%CI 1.02-1.52). The other associations did not vary when stratifying by age at baseline and adherence to mammography recommendations. In conclusion, multi-morbidity was not a key factor to help identify patients at an increased risk of breast cancer.