A paediatric bone index derived by automated radiogrammetry

Hand radiographs are obtained routinely to determine bone age of children. This paper presents a method that determines a Paediatric Bone Index automatically from such radiographs. The Paediatric Bone Index is designed to have minimal relative standard deviation (7.5%), and the precision is determined to be 1.42%. Introduction We present a computerised method to determine bone mass of children based on hand radiographs, including a reference database for normal Caucasian children. Methods Normal Danish subjects (1,867), of ages 7-17, and 531 normal Dutch subjects of ages 5-19 were included. Historically, three different indices of bone mass have been used in radiogrammetry all based on A = pi TW(1 - T/W), where T is the cortical thickness and W the bone width. The indices are the metacarpal index A/W-2, DXR-BMD=A/W, and Exton-Smith's index A/(WL), where L is the length of the bone. These indices are compared with new indices of the form A/((WLb)-L-a), and it is argued that the preferred index has minimal SD relative to the mean value at each bone age and sex. Finally, longitudinal series of X-rays of 20 Japanese children are used to derive the precision of the measurements. Results The preferred index is A/((WL0.33)-L-1.33), which is named the Paediatric Bone Index, PBI. It has mean relative SD 7.5% and precision 1.42%. Conclusions As part of the BoneXpert method for automated bone age determination, our method facilitates retrospective research studies involving validation of the proposed index against fracture incidence and adult bone mineral densit

Automatic determination of Greulich and Pyle bone age in healthy Dutch children

Background: Bone age (BA) assessment is a routine procedure in paediatric radiology, for which the Greulich and Pyle (GP) atlas is mostly used. There is rater variability, but the advent of automatic BA determination eliminates this. Objective: To validate the BoneXpert method for automatic determination of skeletal maturity of healthy children against manual GP BA ratings. Materials and methods: Two observers determined GP BA with knowledge of the chronological age (CA). A total of 226 boys with a BA of 3-17 years and 179 girls with a BA of 3-15 years were included in the study. BoneXpert's estimate of GP BA was calibrated to agree on average with the manual ratings based on several studies, including the present study. Results: Seven subjects showed a deviation between manual and automatic BA in excess of 1.9 years. They were re-rated blindly by two raters. After correcting these seven ratings, the root mean square error between manual and automatic rating in the 405 subjects was 0.71 years (range 0.66-0.76 years, 95% CI). BoneXpert's GP BA is on average 0.28 and 0.20 years behind the CA for boys and girls, respectively. Conclusion: BoneXpert is a robust method for automatic determination of BA

Prototypes for Content-Based Image Retrieval in Clinical Practice

Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice

Germline variants at SOHLH2 influence multiple myeloma risk

Funding Information: This work was supported by grants from the Knut and Alice Wallenberg Foundation (2012.0193 and 2017.0436), the Swedish Research Council (2017-02023), the Swedish Cancer Society (2017/265), Stiftelsen Borås Forsknings-och Utvecklingsfond mot Cancer, the Nordic Cancer Union (R217-A13329-18-S65), EU-MSCA-COFUND 754299 CanFaster, the Myeloma UK and Cancer Research UK (C1298/A8362), a Jacquelin Forbes-Nixon Fellowship, and Mr. Ralph Stockwell. We thank Ellinor Johnsson and Anna Collin for their assistance. We are indebted to the clinicians and patients who contributed samples. Open access funding provided by Lund University. Publisher Copyright: © 2021, The Author(s).Multiple myeloma (MM) is caused by the uncontrolled, clonal expansion of plasma cells. While there is epidemiological evidence for inherited susceptibility, the molecular basis remains incompletely understood. We report a genome-wide association study totalling 5,320 cases and 422,289 controls from four Nordic populations, and find a novel MM risk variant at SOHLH2 at 13q13.3 (risk allele frequency = 3.5%; odds ratio = 1.38; P = 2.2 × 10−14). This gene encodes a transcription factor involved in gametogenesis that is normally only weakly expressed in plasma cells. The association is represented by 14 variants in linkage disequilibrium. Among these, rs75712673 maps to a genomic region with open chromatin in plasma cells, and upregulates SOHLH2 in this cell type. Moreover, rs75712673 influences transcriptional activity in luciferase assays, and shows a chromatin looping interaction with the SOHLH2 promoter. Our work provides novel insight into MM susceptibility.Peer reviewe

Functional dissection of inherited non-coding variation influencing multiple myeloma risk

Funding Information: This work was supported by grants from the Knut and Alice Wallenberg Foundation (2012.0193 and 2017.0436), the Swedish Research Council (2017-02023 and 2018-00424), the Swedish Cancer Society (2017/265), the Nordic Cancer Union (R217-A13329-18-S65), Arne and Inga-Britt Lundberg’s Stiftelse (2017-0055), European Research Council (EU-MSCA-COFUND 754299 CanFaster), Myeloma UK and Cancer Research UK (C1298/A8362), The National Institute of Health (R01 DK103794 and R01HL146500), the New York Stem Cell Foundation, a gift from the Lodish Family to Boston Children’s Hospital, and Mr. Ralph Stockwell. We thank Ellinor Johnsson for her assistance between 2011 and 2020. We are indebted to the patients who participated in the study. Publisher Copyright: © 2022, The Author(s).Thousands of non-coding variants have been associated with increased risk of human diseases, yet the causal variants and their mechanisms-of-action remain obscure. In an integrative study combining massively parallel reporter assays (MPRA), expression analyses (eQTL, meQTL, PCHiC) and chromatin accessibility analyses in primary cells (caQTL), we investigate 1,039 variants associated with multiple myeloma (MM). We demonstrate that MM susceptibility is mediated by gene-regulatory changes in plasma cells and B-cells, and identify putative causal variants at six risk loci (SMARCD3, WAC, ELL2, CDCA7L, CEP120, and PREX1). Notably, three of these variants co-localize with significant plasma cell caQTLs, signaling the presence of causal activity at these precise genomic positions in an endogenous chromosomal context in vivo. Our results provide a systematic functional dissection of risk loci for a hematologic malignancy.Peer reviewe