ABSTRACT
BACKGROUND: Mammographic density (MD) has been shown to be a strong and independent risk factor for breast cancer in women of European and Asian descent. However, the majority of Asian studies to date have used BI-RADS as the scoring method and none have evaluated area and volumetric densities in the same cohort of women. This study aims to compare the association of MD measured by two automated methods with the risk of breast cancer in Asian women, and to investigate if the association is different for premenopausal and postmenopausal women. METHODS: In this case-control study of 531 cases and 2297 controls, we evaluated the association of area-based MD measures and volumetric-based MD measures with breast cancer risk in Asian women using conditional logistic regression analysis, adjusting for relevant confounders. The corresponding association by menopausal status were assessed using unconditional logistic regression. RESULTS: We found that both area and volume-based MD measures were associated with breast cancer risk. Strongest associations were observed for percent densities (OR (95% CI) was 2.06 (1.42-2.99) for percent dense area and 2.21 (1.44-3.39) for percent dense volume, comparing women in highest density quartile with those in the lowest quartile). The corresponding associations were significant in postmenopausal but not premenopausal women (premenopausal versus postmenopausal were 1.59 (0.95-2.67) and 1.89 (1.22-2.96) for percent dense area and 1.24 (0.70-2.22) and 1.96 (1.19-3.27) for percent dense volume). However, the odds ratios were not statistically different by menopausal status [p difference = 0.782 for percent dense area and 0.486 for percent dense volume]. CONCLUSIONS: This study confirms the associations of mammographic density measured by both area and volumetric methods and breast cancer risk in Asian women. Stronger associations were observed for percent dense area and percent dense volume, and strongest effects were seen in postmenopausal individuals.
Subject(s)
Asian People , Breast Density , Breast Neoplasms , Mammography , Humans , Female , Breast Neoplasms/epidemiology , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/pathology , Breast Neoplasms/etiology , Case-Control Studies , Middle Aged , Adult , Risk Factors , Mammography/methods , Aged , Postmenopause , Premenopause , Odds Ratio , Mammary Glands, Human/abnormalities , Mammary Glands, Human/diagnostic imaging , Mammary Glands, Human/pathologyABSTRACT
PURPOSE: Mammographic density (MD), after accounting for age and body mass index (BMI), is a strong heritable risk factor for breast cancer. Genome-wide association studies (GWAS) have identified 64 SNPs in 55 independent loci associated with MD in women of European ancestry. Their associations with MD in Asian women, however, are largely unknown. METHOD: Using linear regression adjusting for age, BMI, and ancestry-informative principal components, we evaluated the associations of previously reported MD-associated SNPs with MD in a multi-ethnic cohort of Asian ancestry. Area and volumetric mammographic densities were determined using STRATUS (N = 2450) and Volpara™ (N = 2257). We also assessed the associations of these SNPs with breast cancer risk in an Asian population of 14,570 cases and 80,870 controls. RESULTS: Of the 61 SNPs available in our data, 21 were associated with MD at a nominal threshold of P value < 0.05, all in consistent directions with those reported in European ancestry populations. Of the remaining 40 variants with a P-value of association > 0.05, 29 variants showed consistent directions of association as those previously reported. We found that nine of the 21 MD-associated SNPs in this study were also associated with breast cancer risk in Asian women (P < 0.05), seven of which showed a direction of associations that was consistent with that reported for MD. CONCLUSION: Our study confirms the associations of 21 SNPs (19/55 or 34.5% out of all known MD loci identified in women of European ancestry) with area and/or volumetric densities in Asian women, and further supports the evidence of a shared genetic basis through common genetic variants for MD and breast cancer risk.
Subject(s)
Breast Density , Breast Neoplasms , Female , Humans , Breast Density/genetics , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/genetics , Breast Neoplasms/epidemiology , Genome-Wide Association Study , Polymorphism, Single Nucleotide , Risk Factors , Asia, Eastern , MammographyABSTRACT
BACKGROUND: Rare protein-truncating variants (PTVs) in partner and localiser of BRCA2 (PALB2) confer increased risk to breast cancer, but relatively few studies have reported the prevalence in South-East Asian populations. Here, we describe the prevalence of rare variants in PALB2 in a population-based study of 7840 breast cancer cases and 7928 healthy Chinese, Malay and Indian women from Malaysia and Singapore, and describe the functional impact of germline missense variants identified in this population. METHODS: Mutation testing was performed on germline DNA (n=15 768) using targeted sequencing panels. The functional impact of missense variants was tested in mouse embryonic stem cell based functional assays. RESULTS: PTVs in PALB2 were found in 0.73% of breast cancer patients and 0.14% of healthy individuals (OR=5.44; 95% CI 2.85 to 10.39, p<0.0001). In contrast, rare missense variants in PALB2 were not associated with increased risk of breast cancer. Whereas PTVs were associated with later stage of presentation and higher-grade tumours, no significant association was observed with missense variants in PALB2. However, two novel rare missense variants (p.L1027R and p.G1043V) produced unstable proteins and resulted in a decrease in homologous recombination-mediated repair of DNA double-strand breaks. CONCLUSION: Despite genetic and lifestyle differences between Asian and other populations, the population prevalence of PALB2 PTVs and associated relative risk of breast cancer, are similar to those reported in European populations.
Subject(s)
Breast Neoplasms , Genetic Predisposition to Disease , Animals , Breast Neoplasms/epidemiology , Breast Neoplasms/genetics , Breast Neoplasms/pathology , Fanconi Anemia Complementation Group N Protein/genetics , Female , Germ-Line Mutation , Humans , Malaysia/epidemiology , Male , Mice , Singapore/epidemiologyABSTRACT
This study investigates the feasibility of using texture radiomics features extracted from mammography images to distinguish between benign and malignant breast lesions and to classify benign lesions into different categories and determine the best machine learning (ML) model to perform the tasks. Six hundred and twenty-two breast lesions from 200 retrospective patient data were segmented and analysed. Three hundred fifty radiomics features were extracted using the Standardized Environment for Radiomics Analysis (SERA) library, one of the radiomics implementations endorsed by the Image Biomarker Standardisation Initiative (IBSI). The radiomics features and selected patient characteristics were used to train selected machine learning models to classify the breast lesions. A fivefold cross-validation was used to evaluate the performance of the ML models and the top 10 most important features were identified. The random forest (RF) ensemble gave the highest accuracy (89.3%) and positive predictive value (66%) and likelihood ratio of 13.5 in categorising benign and malignant lesions. For the classification of benign lesions, the RF model again gave the highest likelihood ratio of 3.4 compared to the other models. Morphological and textural radiomics features were identified as the top 10 most important features from the random forest models. Patient age was also identified as one of the significant features in the RF model. We concluded that machine learning models trained against texture-based radiomics features and patient features give reasonable performance in differentiating benign versus malignant breast lesions. Our study also demonstrated that the radiomics-based machine learning models were able to emulate the visual assessment of mammography lesions, typically used by radiologists, leading to a better understanding of how the machine learning model arrive at their decision.
Subject(s)
Breast , Mammography , Humans , Retrospective Studies , Breast/diagnostic imaging , Mammography/methods , Machine Learning , Random ForestABSTRACT
BACKGROUND: Family history, and genetic and non-genetic risk factors can stratify women according to their individual risk of developing breast cancer. The extent of overlap between these risk predictors is not clear. METHODS: In this case-only analysis involving 7600 Asian breast cancer patients diagnosed between age 30 and 75 years, we examined identification of high-risk patients based on positive family history, the Gail model 5-year absolute risk [5yAR] above 1.3%, breast cancer predisposition genes (protein-truncating variants [PTV] in ATM, BRCA1, BRCA2, CHEK2, PALB2, BARD1, RAD51C, RAD51D, or TP53), and polygenic risk score (PRS) 5yAR above 1.3%. RESULTS: Correlation between 5yAR (at age of diagnosis) predicted by PRS and the Gail model was low (r=0.27). Fifty-three percent of breast cancer patients (n=4041) were considered high risk by one or more classification criteria. Positive family history, PTV carriership, PRS, or the Gail model identified 1247 (16%), 385 (5%), 2774 (36%), and 1592 (21%) patients who were considered at high risk, respectively. In a subset of 3227 women aged below 50 years, the four models studied identified 470 (15%), 213 (7%), 769 (24%), and 325 (10%) unique patients who were considered at high risk, respectively. For younger women, PRS and PTVs together identified 745 (59% of 1276) high-risk individuals who were not identified by the Gail model or family history. CONCLUSIONS: Family history and genetic and non-genetic risk stratification tools have the potential to complement one another to identify women at high risk.
Subject(s)
Breast Neoplasms , Asian People , Breast Neoplasms/diagnosis , Breast Neoplasms/epidemiology , Breast Neoplasms/genetics , Female , Genetic Predisposition to Disease/genetics , Humans , Male , Risk AssessmentABSTRACT
PURPOSE: Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups. METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases). RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk. CONCLUSION: PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.
Subject(s)
Breast Neoplasms , Bayes Theorem , Breast Neoplasms/epidemiology , Breast Neoplasms/genetics , Female , Genetic Predisposition to Disease , Genome-Wide Association Study , Humans , Multifactorial Inheritance/genetics , Polymorphism, Single Nucleotide/genetics , Prospective Studies , Risk FactorsABSTRACT
BACKGROUND: Charcot-Marie-Tooth (CMT) disease is diagnosed through clinical findings and genetic testing. While there are neurophysiological tools and clinical functional scales in CMT, objective disease biomarkers that can facilitate in monitoring disease progression are limited. PURPOSE: To investigate the utility of diffusion tensor imaging (DTI) in determining the microstructural integrity of sciatic and peroneal nerves and its correlation with the MRI grading of muscle atrophy severity and clinical function in CMT as determined by the CMT neuropathy score (CMTNS). STUDY TYPE: Prospective case-control. SUBJECTS: Nine CMT patients and nine age-matched controls. FIELD STRENGTH/SEQUENCE: 3 T T1 -weighted in-/out-of phase spoiled gradient recalled echo (SPGR) and DTI sequences. ASSESSMENT: Fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) values for sciatic and peroneal nerves were obtained from DTI. Muscle atrophy was graded according to the Goutallier classification using in-/out-of phase SPGRs. DTI parameters and muscle atrophy grades were compared between CMT and controls, and the relationship between DTI parameters, muscle atrophy grades, and CMTNS were assessed. STATISTICAL TESTS: The Wilcoxon Signed Ranks test was used to compare DTI parameters between CMT and controls. The relationship between DTI parameters, muscle atrophy grades, and CMTNS were analyzed using the Spearman correlation. Receiver operating characteristic (ROC) analyses of DTI parameters that can differentiate CMT from healthy controls were done. RESULTS: There was a significant reduction in FA and increase in RD of both nerves (P < 0.05) in CMT, with significant correlations between FA (negative; P < 0.05) and RD (positive; P < 0.05) with muscle atrophy grade. In the sciatic nerve, there was significant correlation between FA and CMTNS (r = -0.795; P < 0.05). FA and RD could discriminate CMT from controls with high sensitivity (77.8-100%) and specificity (88.9-100%). DATA CONCLUSION: There were significant differences of DTI parameters between CMT and controls, with significant correlations between DTI parameters, muscle atrophy grade, and CMTNS. Level of Evidence 2 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2021;53:437-444.
Subject(s)
Charcot-Marie-Tooth Disease , Diffusion Tensor Imaging , Anisotropy , Charcot-Marie-Tooth Disease/diagnostic imaging , Humans , Magnetic Resonance Imaging , Peripheral Nerves/diagnostic imaging , Prospective StudiesABSTRACT
BACKGROUND & AIMS: HepaFat-Scan is a magnetic resonance imaging-based method for quantification of hepatic steatosis by volumetric liver fat fraction (VLFF) measurement. We aimed to validate VLFF and to compare it with controlled attenuation parameter (CAP) for determination of hepatic steatosis grade in patients with NAFLD, using histopathology and stereologic analyses of biopsies as the reference standard. METHODS: We performed a prospective study of consecutive adults with NAFLD who were scheduled for a liver biopsy at a tertiary hospital in Malaysia. Patients underwent VLFF and CAP measurements on the same day as their liver biopsy. Histopathology analyses of liver biopsy specimens were reported according to the Nonalcoholic Steatohepatitis Clinical Research Network scoring system. Stereologic analysis was performed using grid-point counting method combined with the Delesse principle. RESULTS: We analyzed data from 97 patients (mean age 57.0 ± 10.1 years; 44.33% male; 91.8% obese; 95.9% centrally obese). Based on histopathology analysis, the area under receiver operating characteristic curve (AUROC) for VLFF in detection of steatosis grade ≥S2 was 0.92 and for CAP the AUROC was 0.65 (P < .001). Based on stereological analysis, the AUROC for VLFF for detection of steatosis grade ≥S2 was 0.92 and for CAP the AUROC was 0.63, (P = .002); for identification of steatosis grade S3, the AUROC for VLFF was 0.92 and for CAP the AUROC was 0.68 (P < .001). CONCLUSIONS: In a prospective study of patients with NAFLD undergoing liver biopsy analysis, we found VLFF to more accurately determine grade of hepatic steatosis than CAP.
Subject(s)
Elasticity Imaging Techniques , Non-alcoholic Fatty Liver Disease , Adult , Area Under Curve , Biopsy , Female , Humans , Liver/diagnostic imaging , Male , Middle Aged , Non-alcoholic Fatty Liver Disease/diagnostic imaging , Prospective Studies , ROC CurveABSTRACT
BACKGROUND AND AIM: Transient elastography (TE) and point shear wave elastography (pSWE) are noninvasive methods to diagnose fibrosis stage in patients with chronic liver disease. The aim of this study is to compare the accuracy of the two methods to diagnose fibrosis stage in non-alcoholic fatty liver disease (NAFLD) and to study the intra-observer and inter-observer variability when the examinations were performed by healthcare personnel of different backgrounds. METHODS: Consecutive NAFLD patients who underwent liver biopsy were enrolled in this study and had two sets each of pSWE and TE examinations by a nurse and a doctor on the same day of liver biopsy procedure. The medians of the four sets of pSWE and TE were used for evaluation of diagnostic accuracy using area under receiver operating characteristic curve (AUROC). Intra-observer and inter-observer variability was analyzed using intraclass correlation coefficients. RESULTS: Data for 100 NAFLD patients (mean age 57.1 ± 10.2 years; male 46.0%) were analyzed. The AUROC of TE for diagnosis of fibrosis stage ≥ F1, ≥ F2, ≥ F3, and F4 was 0.89, 0.83, 0.83, and 0.89, respectively. The corresponding AUROC of pSWE was 0.80, 0.72, 0.69, and 0.79, respectively. TE was significantly better than pSWE for the diagnosis of fibrosis stages ≥ F2 and ≥ F3. The intra-observer and inter-observer variability of TE and pSWE measurements by the nurse and doctor was excellent with intraclass correlation coefficient > 0.96. CONCLUSION: Transient elastography was significantly better than pSWE for the diagnosis of fibrosis stage ≥ F2 and ≥ F3. Both TE and pSWE had excellent intra-observer and inter-observer variability when performed by healthcare personnel of different backgrounds.
Subject(s)
Elasticity Imaging Techniques/methods , Non-alcoholic Fatty Liver Disease/diagnostic imaging , Non-alcoholic Fatty Liver Disease/pathology , Female , Fibrosis , Humans , Male , Middle AgedABSTRACT
Benign cystic or solid lumps frequently occur in the breasts of young women, and consequently can also be seen during pregnancy and lactation. Simple cysts do not increase the risk of malignancy. The current management is routine follow-up. Complex cysts are thick walled or contain a mass, and should be followed by a US-guided biopsy and then treated similar to any non-gravid, non-lactating patient.Galactoceles can be detected during the last trimester of pregnancy and during or after stopping lactation. Aspiration can be done to confirm the content. Co-existence of galactocele and malignancy is extremely rare, and the key is to follow up until it resolves.Fibroadenoma is the most frequent lesion found during pregnancy and lactation. Management is usually conservative after triple assessment. Surgery is usually not recommended in pregnant and lactating women unless rapid increase in size occurs or there is discordance in the triple assessment.Lactating adenomas are sometimes interpreted as a variant of fibroadenoma . They can naturally disappear at the end of pregnancy or lactation. Management is usually conservative, and an excisional biopsy is only mandated if it is rapidly enlarging or if there is discordance in the triple assessment.Gestational gigantomastia is a rare condition consisting of diffuse severe hypertrophy of both breasts during pregnancy . Mastectomy and reconstruction may rarely be required in such cases.
Subject(s)
Breast Diseases , Lactation , Pregnancy Complications , Breast , Breast Cyst , Female , Fibroadenoma , Humans , Mastectomy , PregnancyABSTRACT
PURPOSE: Mammographic density is a measurable and modifiable biomarker that is strongly and independently associated with breast cancer risk. Paradoxically, although Asian women have lower risk of breast cancer, studies of minority Asian women in predominantly Caucasian populations have found that Asian women have higher percent density. In this cross-sectional study, we compared the distribution of mammographic density for a matched cohort of Asian women from Malaysia and Caucasian women from Sweden, and determined if variations in mammographic density could be attributed to population differences in breast cancer risk factors. METHODS: Volumetric mammographic density was compared for 1501 Malaysian and 4501 Swedish healthy women, matched on age and body mass index. We used multivariable log-linear regression to determine the risk factors associated with mammographic density and mediation analysis to identify factors that account for differences in mammographic density between the two cohorts. RESULTS: Compared to Caucasian women, percent density was 2.0% higher among Asian women (p < 0.001), and dense volume was 5.7 cm3 higher among pre-menopausal Asian women (p < 0.001). Dense volume was 3.0 cm3 lower among post-menopausal Asian women (p = 0.009) compared to post-menopausal Caucasian women, and this difference was attributed to population differences in height, weight, and parity (p < 0.001). CONCLUSIONS: Our analysis suggests that among post-menopausal women, population differences in mammographic density and risk to breast cancer may be accounted for by height, weight, and parity. Given that pre-menopausal Asian and Caucasian women have similar population risk to breast cancer but different dense volume, development of more appropriate biomarkers of risk in pre-menopausal women is required.
Subject(s)
Asian People , Breast Density , Breast Neoplasms/epidemiology , White People , Breast Neoplasms/etiology , Cross-Sectional Studies , Female , Humans , Malaysia/epidemiology , Mammography , Middle Aged , Population Surveillance , Risk Factors , Sweden/epidemiologyABSTRACT
OBJECTIVE: To compare the metabolite concentration of optic radiation in glaucoma patients with that of healthy subjects using Proton Magnetic Resonance Spectroscopy (1H-MRS). METHODS: 1H-MRS utilising the Single-Voxel Spectroscopy (SVS) technique was performed using a 3.0Tesla MRI on 45 optic radiations (15 from healthy subjects, 15 from mild glaucoma patients, and 15 from severe glaucoma patients). A standardised Volume of Interest (VOI) of 20 × 20 × 20 mm was placed in the region of optic radiation. Mild and severe glaucoma patients were categorised based on the Hodapp-Parrish-Anderson (HPA) classification. Mean and multiple group comparisons for metabolite concentration and metabolite concentration ratio between glaucoma grades and healthy subjects were obtained using one-way ANOVA. RESULTS: The metabolite concentration and metabolite concentration ratio between the optic radiations of glaucoma patients and healthy subjects did not demonstrate any significant difference (p > 0.05). CONCLUSION: Our findings show no significant alteration of metabolite concentration associated with neurodegeneration that could be measured by single-voxel 1H-MRS in optic radiation among glaucoma patients. KEY POINTS: ⢠Glaucoma disease has a neurodegenerative component. ⢠Metabolite changes have been observed in the neurodegenerative process in the brain. ⢠Using SVS, no metabolite changes in optic radiation were attributed to glaucoma.
Subject(s)
Biomarkers/metabolism , Glaucoma, Open-Angle/pathology , Proton Magnetic Resonance Spectroscopy/methods , Adult , Aged , Analysis of Variance , Aspartic Acid/analogs & derivatives , Aspartic Acid/metabolism , Choline/metabolism , Creatine/metabolism , Cross-Sectional Studies , Female , Glutamic Acid/metabolism , Glutamine/metabolism , Humans , Magnetic Resonance Spectroscopy/methods , Male , Middle Aged , Nerve Fibers/metabolism , Nerve Fibers/pathology , Optic Nerve/metabolism , Radiation Dosage , Young AdultABSTRACT
OBJECTIVES: We evaluated the feasibility of using chemical shift gradient-echo (GE) in- and opposed-phase (IOP) imaging to grade glioma. METHODS: A phantom study was performed to investigate the correlation of (1)H MRS-visible lipids with the signal loss ratio (SLR) obtained using IOP imaging. A cross-sectional study approved by the institutional review board was carried out in 22 patients with different glioma grades. The patients underwent scanning using IOP imaging and single-voxel spectroscopy (SVS) using 3T MRI. The brain spectra acquisitions from solid and cystic components were obtained and correlated with the SLR for different grades. RESULTS: The phantom study showed a positive linear correlation between lipid quantification at 0.9 parts per million (ppm) and 1.3 ppm with SLR (r = 0.79-0.99, p < 0.05). In the clinical study, we found that SLR at the solid portions was the best measure for differentiating glioma grades using optimal cut-points of 0.064 and 0.086 with classification probabilities for grade II (SII = 1), grade III (SIII = 0.50) and grade IV (SIV = 0.89). CONCLUSIONS: The results underscore the lipid quantification differences in grades of glioma and provide a more comprehensive characterization by using SLR in chemical shift GE IOP imaging. SLR in IOP sequence demonstrates good performance in glioma grading. KEY POINTS: ⢠Strong correlation was seen between lipid concentration and SLR obtained using IOP ⢠IOP sequence demonstrates significant differences in signal loss within the glioma grades ⢠SLR at solid tumour portions was the best measure for differentiation ⢠This sequence is applicable in a research capacity for glioma staging armamentarium.
Subject(s)
Brain Neoplasms/diagnostic imaging , Glioma/diagnostic imaging , Lipids/administration & dosage , Magnetic Resonance Imaging/methods , Magnetic Resonance Spectroscopy/methods , Adolescent , Adult , Aged , Brain Neoplasms/classification , Brain Neoplasms/pathology , Child , Cross-Sectional Studies , Feasibility Studies , Female , Glioma/classification , Glioma/pathology , Humans , Male , Middle Aged , Phantoms, Imaging , Young AdultABSTRACT
BACKGROUND: Breast cancer is the leading cause of cancer deaths in women world-wide. In low and middle income countries, where there are no population-based mammographic screening programmes, late presentation is common, and because of inadequate access to optimal treatment, survival rates are poor. Mammographic screening is well-studied in high-income countries in western populations, and because it has been shown to reduce breast cancer mortality, it has become part of the healthcare systems in such countries. However the performance of mammographic screening in a developing country is largely unknown. This study aims to evaluate the performance of mammographic screening in Malaysia, a middle income country, and to compare the stage and surgical treatment of screen-detected and symptomatic breast cancer. METHODS: A retrospective review of 2510 mammograms performed from Jan to Dec 2010 in a tertiary medical centre is carried out. The three groups identified are the routine (opportunistic) screening group, the targeted (high risk) screening group and the diagnostic group. The performance indicators of each group is calculated, and stage at presentation and treatment between the screening and diagnostic group is analyzed. RESULTS: The cancer detection rate in the opportunistic screening group, targeted screening group, and the symptomatic group is 0.5 %, 1.25 % and 26 % respectively. The proportion of ductal carcinoma in situ is 23.1 % in the two screening groups compared to only 2.5 % in the diagnostic group. Among the opportunistic screening group, the cancer detection rate was 0.2 % in women below 50 years old compared to 0.65 % in women 50 years and above. The performance indicators are within international standards. Early-staged breast cancer (Stage 0-2) were 84.6 % in the screening groups compared to 61.1 % in the diagnostic group. CONCLUSION: From the results, in a setting with resource constraints, targeted screening of high risk individuals will give a higher yield, and if more resources are available, population-based screening of women 50 and above is effective. Opportunistic mammographic screening is feasible and effective in a middle income country with performance indicators within international standards. Waiting until women are symptomatic will lead to more advanced cancers.
Subject(s)
Breast Neoplasms/diagnosis , Breast Neoplasms/epidemiology , Delivery of Health Care , Early Detection of Cancer , Health Resources , Mammography , Mass Screening , Adult , Aged , Biopsy , Breast Neoplasms/surgery , Female , Humans , Malaysia/epidemiology , Malaysia/ethnology , Mammary Glands, Human/pathology , Middle Aged , Neoplasm Staging , Retrospective Studies , Tertiary Care CentersABSTRACT
AIM: To determine the correlation and agreement between Hertel exophthalmometry and computed tomography (CT) of the orbits in measuring proptosis. MATERIALS AND METHODS: 80 patients (40 normal and 40 with proptosis) were recruited for this study. Exophthalmometry were performed on all of them using the Hertel exophthalmometer and CT. Values and correlations between the modalities were analysed with unpaired t-tests, intraclass correlation coefficients (ICC), and Pearson correlation coefficients (PCC). The Bland-Altman method was used to analyse the agreement between the two modalities. RESULTS: Hertel exophthalmometer and CT measurements did not differ significantly (p > 0.05), although exophthalmometry measurements of the normal (14.5 ± 2.2 mm) and proptosis groups (20.5 ± 3.9 mm) were higher than those obtained from CT (13.9 ± 2.4 mm and 20.0 ± 3.7 mm, respectively). ICC for both the Hertel exophthalmometer and CT measurements were both 0.99, indicating high intra-observer reliability and reproducibility. PCC between Hertel exophthalmometer and CT measurements in both normal and proptosis groups were strongly correlated (r = 0.96 and 0.93, respectively, p = 0.01). The 95% limits of agreement (LOA) between Hertel exophthalmometer and CT measurements for the normal and proptosis groups were -0.70 to 1.78 mm and -2.36 to 3.33 mm, respectively. CONCLUSION: Although Hertel exophthalmometer and CT measurements are similar and strongly correlated, they do not agree well with each other in the presence of proptosis. The measurements should not be used interchangeably as the differences between them may lead to errors in clinical interpretation.
Subject(s)
Diagnostic Techniques, Ophthalmological , Exophthalmos/diagnosis , Orbit/diagnostic imaging , Tomography, X-Ray Computed/methods , Adolescent , Adult , Aged , Aged, 80 and over , Diagnostic Techniques, Ophthalmological/instrumentation , Female , Humans , Male , Middle Aged , Observer Variation , Reproducibility of ResultsABSTRACT
PURPOSE: To measure optic nerve (ON) volume using 3 T magnetic resonance imaging (MRI), to correlate ON volume with retinal nerve fiber layer (RNFL) thickness, and to determine the viability of MRI as an objective tool in distinguishing glaucoma severity. METHODS: In this cross-sectional study, 30 severe glaucoma patients, 30 mild glaucoma patients and 30 age-matched controls were recruited. All subjects underwent standard automated perimetry, RNFL analysis and 3 T MRI examinations. Glaucoma patients were classified according to the Hodapp-Anderson-Parish classification. Pearson's correlation coefficient was used to correlate ON volume with RNFL, and receiver operating curve (ROC) analysis was performed to determine the sensitivity and specificity of ON volume in detecting glaucoma severity. RESULTS: Optic nerve volume was significantly lower in both the left and right eyes of the severe glaucoma group (168.70 ± 46.28 mm(3); 167.40 ± 45.36 mm(3)) than in the mild glaucoma group (264.03 ± 78.53 mm(3); 264.76 ± 78.88 mm(3)) and the control group (297.80 ± 71.45 mm(3); 296.56 ± 71.02 mm(3)). Moderate correlation was observed between: RNFL thickness and ON volume (r = 0.51, p <0.001), and in mean deviation of visual field and optic nerve volume (r = 0.60, p < 0.001). ON volume below 236 mm(3) was 96 % sensitive and 80 % specific for the detection of severe glaucoma. CONCLUSIONS: MRI measured optic nerve volume is a reliable method of assessing glaucomatous damage beyond the optic nerve head. A value of 236 mm(3) and below can be used to define severe glaucoma.
Subject(s)
Glaucoma, Angle-Closure/diagnosis , Glaucoma, Open-Angle/diagnosis , Magnetic Resonance Imaging , Nerve Fibers/pathology , Optic Nerve Diseases/diagnosis , Optic Nerve/pathology , Retinal Ganglion Cells/pathology , Aged , Aged, 80 and over , Cross-Sectional Studies , Glaucoma, Angle-Closure/classification , Glaucoma, Open-Angle/classification , Humans , Intraocular Pressure/physiology , Middle Aged , Observer Variation , Optic Disk/pathology , Optic Nerve Diseases/classification , Organ Size , Reproducibility of Results , Sensitivity and Specificity , Visual Fields/physiologyABSTRACT
OBJECTIVE: This study evaluates the effectiveness of artificial intelligence (AI) in mammography in a diverse population from a middle-income nation and compares it to traditional methods. METHODS: A retrospective study was conducted on 543 mammograms of 467 Malays, 48 Chinese, and 28 Indians in a middle-income nation. Three breast radiologists interpreted the examinations independently in two reading sessions (with and without AI support). Breast density and BI-RADS categories were assessed, comparing the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) results. RESULTS: Of 543 mammograms, 69.2% had lesions detected. Biopsies were performed on 25%(n=136), with 66(48.5%) benign and 70(51.5%) malignant. Substantial agreement in density assessment between the radiologist and AI software (κ =0.606, p < 0.001) and the BI-RADS category with and without AI (κ =0.74, p < 0.001). The performance of the AI software was comparable to the traditional methods. The sensitivity, specificity, PPV, and NPV or radiologists alone, radiologist + AI, and AI alone were 81.9%,90.4%,56.0%, and 97.1%; 81.0%, 93.1%,55.5%, and 97.0%; and 90.0%,76.5%,36.2%, and 98.1%, respectively. AI software enhances the accuracy of lesion diagnosis and reduces unnecessary biopsies, particularly for BI-RADS 4 lesions. The AI software results for synthetic were almost similar to the original 2D mammography, with AUC of 0.925 and 0.871, respectively. CONCLUSION: AI software may assist in the accurate diagnosis of breast lesions, enhancing the efficiency of breast lesion diagnosis in a mixed population of opportunistic screening and diagnostic patients. KEY MESSAGES: ⢠The use of artificial intelligence (AI) in mammography for population-based breast cancer screening has been validated in high-income nations, with reported improved diagnostic performance. Our study evaluated the usage of an AI tool in an opportunistic screening setting in a multi-ethnic and middle-income nation. ⢠The application of AI in mammography enhances diagnostic accuracy, potentially leading to reduced unnecessary biopsies. ⢠AI integration into the workflow did not disrupt the performance of trained breast radiologists, as there is a substantial inter-reader agreement for BI-RADS category assessment and breast density.
ABSTRACT
OBJECTIVES: Accurate subtyping of breast cancer is crucial for its diagnosis, management, and prognostication. This study aimed to determine the association of magnetic resonance imaging (MRI) breast features with the molecular subtype and aggressiveness of breast cancer in a multi-ethnic population. METHODS: Treatment-naive patients with invasive breast carcinoma were included in this retrospective study. Breast MRI features were recorded based on the American College of Radiology-Breast Imaging Reporting and Data System (ACR-BIRADS) criteria, with tumour size, and apparent diffusion coefficient value (ADC). The statistical association was tested with Pearson Chi-Square Test of Independence for categorical data or the Kruskal-Wallis/ Mann Whitney U test for numerical data between the MRI features and molecular subtype, receptor status, tumour grade, lymphovascular infiltration (LVI) and axillary lymph node (ALN). Multinomial logistic regression was used to test the predictive likelihood of the significant features. The breast cancer subtypes were determined via immunohistochemistry (IHC) and dual-color dual-hapten in-situ hybridization (D-DISH). The expression statuses of ER, PR, and HER-2, LVI, and ALN were obtained from the histopathology report. The ER / PR / HER-2 was evaluated according to the American Society of Clinical Oncology / College of American Pathologists. RESULTS: The study included 194 patients; 41.8% (n = 81) Chinese, 40.7% (n = 79) Malay, and 17.5% (n = 34) Indian, involving 71.6%(n = 139) luminal-like, 12.9%(n = 25) HER-2 enriched, and 15.5%(n = 30) Triple-negative breast cancer (TNBC). TNBC was associated with rim enhancement (p = 0.002) and peritumoral oedema (p = 0.004). HER-2 enriched tumour was associated with larger tumour size (p = 0.041). Luminal-like cancer was associated with irregular shape (p = 0.005) with circumscribed margin (p = 0.003). Other associations were ER-negative tumour with circumscribed margin (p = 0.002) and PR-negative with round shape (p = 0.001). Tumour sizes were larger in ER-negative (p = 0.044) and PR-negative (p = 0.022). Rim enhancement was significantly associated with higher grade (p = 0.001), and moderate peritumoral oedema with positive axillary lymph node (p = 0.002). CONCLUSION: Certain MRI features can be applied to differentiate breast cancer molecular subtypes, receptor status and aggressiveness, even in a multi-ethnic population.
Subject(s)
Breast Neoplasms , Magnetic Resonance Imaging , Humans , Female , Breast Neoplasms/pathology , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/genetics , Middle Aged , Magnetic Resonance Imaging/methods , Adult , Retrospective Studies , Aged , Receptors, Estrogen/metabolism , Receptor, ErbB-2/metabolism , Receptor, ErbB-2/genetics , Receptors, Progesterone/metabolism , EthnicityABSTRACT
OBJECTIVE: To develop a decision tree based on standard magnetic resonance imaging (MRI) and diffusion tensor imaging to differentiate multiple system atrophy (MSA) from Parkinson's disease (PD). METHODS: 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3. RESULTS: Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified. CONCLUSION: Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD. KEY POINTS: ⢠Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. ⢠Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. ⢠A decision tree is descriptive and predictive in differentiating between clinical entities. ⢠A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.
Subject(s)
Magnetic Resonance Imaging/methods , Multiple System Atrophy/diagnosis , Parkinson Disease/diagnosis , Aged , Anisotropy , Brain Mapping/methods , Decision Trees , Diagnosis, Differential , Diffusion Tensor Imaging/methods , Female , Humans , Male , Middle Aged , Observer Variation , Reproducibility of Results , Sensitivity and Specificity , Time FactorsABSTRACT
BACKGROUND: Intraventricular haemorrhage is the most common cause of hydrocephalus in a pre-term baby and may require surgical intervention depending on severity. CLINICAL CASE: This case illustrates foraminal septae as a subtle cause of progressive quadriventricular hydrocephalus in a child born pre-term with a history of grade III intraventricular haemorrhage. The septae within the fourth ventricular exits were clearly demonstrated with 3D-FIESTA (fast imaging employing steady-state acquisition) MRI acquisitions and assisted in differentiation from communicating hydrocephalus. This finding guided the decision to a successful endoscopic third ventriculostomy. CONCLUSION: 3D-FIESTA sequence is recommended for investigating children with hydrocephalus secondary to intraventricular haemorrhage due to its diagnostic potential and implications on surgical technique.