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Shen A, Wang F, Paul S, Bhuvanapalli D, Alayof J, Farris AB, Teodoro G, Brat DJ, Kong J. An integrative web-based software tool for multi-dimensional pathology whole-slide image analytics. Phys Med Biol 2022; 67:10.1088/1361-6560/ac8fde. [PMID: 36067783 PMCID: PMC10039615 DOI: 10.1088/1361-6560/ac8fde] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 09/06/2022] [Indexed: 11/12/2022]
Abstract
Objective.In the era of precision medicine, human tumor atlas-oriented studies have been significantly facilitated by high-resolution, multi-modal tissue based microscopic pathology image analytics. To better support such tissue-based investigations, we have developed Digital Pathology Laboratory (DPLab), a publicly available web-based platform, to assist biomedical research groups, non-technical end users, and clinicians for pathology whole-slide image visualization, annotation, analysis, and sharing via web browsers.Approach.A major advancement of this work is the easy-to-follow methods to reconstruct three-dimension (3D) tissue image volumes by registering two-dimension (2D) whole-slide pathology images of serial tissue sections stained by hematoxylin and eosin (H&E), and immunohistochemistry (IHC). The integration of these serial slides stained by different methods provides cellular phenotype and pathophysiologic states in the context of a 3D tissue micro-environment. DPLab is hosted on a publicly accessible server and connected to a backend computational cluster for intensive image analysis computations, with results visualized, downloaded, and shared via a web interface.Main results.Equipped with an analysis toolbox of numerous image processing algorithms, DPLab supports continued integration of community-contributed algorithms and presents an effective solution to improve the accessibility and dissemination of image analysis algorithms by research communities.Significance.DPLab represents the first step in making next generation tissue investigation tools widely available to the research community, enabling and facilitating discovery of clinically relevant disease mechanisms in a digital 3D tissue space.
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Affiliation(s)
- Alice Shen
- School of Medicine, University of California at San Diego, San Diego, CA USA
| | - Fusheng Wang
- Department of Computer Science, Stony Brook University, Stony Brook, NY USA
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY USA
| | - Saptarshi Paul
- Department of Computer Science, Georgia State University, Atlanta, GA USA
| | - Divya Bhuvanapalli
- Department of Computer Science, Georgia State University, Atlanta, GA USA
| | | | - Alton B. Farris
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA USA
| | - George Teodoro
- Department of Computer Science in University of Brasilia, Brasília, DF Brazil
| | - Daniel J. Brat
- Department of Pathology, Northwestern University, Chicago, IL USA
| | - Jun Kong
- Department of Computer Science, Georgia State University, Atlanta, GA USA
- Department of Mathematics and Statistics, Georgia State University, Atlanta, GA USA
- Winship Cancer Institute, Emory University, Atlanta, GA USA
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Shetty S, Al-Bayatti S, Alam MK, Al-Rawi NH, Kamath V, Tippu SR, Narasimhan S, Al Kawas S, Elsayed W, Rao K, Castelino R. Analysis of inferior nasal turbinate volume in subjects with nasal septum deviation: a retrospective cone beam tomography study. PeerJ 2022; 10:e14032. [PMID: 36172494 PMCID: PMC9511997 DOI: 10.7717/peerj.14032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 08/17/2022] [Indexed: 01/19/2023] Open
Abstract
Background The association of the linear dimensions of the inferior turbinate hypertrophy with nasal septal deviation has been studied recently. However, the volumetric dimensions provide a more accurate status of the turbinate hypertrophy compared to linear measurements. The aim of this study was to analyze the association of inferior nasal turbinate volume with the degree of nasal septal deviation (NSD). Methods A retrospective evaluation of the cone beam computed tomography (CBCT) scans of 412 patients was carried out to obtain 150 scans which were included in the study. The scans were categorized into three groups. Group 1 comprised of 50 scans of patients with no inferior turbinate hypertrophy (ITH) and no nasal septal deviation. Group 2 comprised of 50 scans of patients with ITH and no NSD; whereas Group 3 included 50 scans of patients with ITH and NSD. The total turbinate volume of inferior turbinates (bilateral) were determined by using Vesalius 3D software (PS-Medtech, Amsterdam, Netherlands). Results The intraclass correlation coefficient (ICC) between the volumetric estimations performed by the two radiologists was 0.82. There were no significant age and gender related changes in the total turbinate volume. Patients in Group 3 had significantly higher (p = 0.001) total turbinate volume compared to Group 2 and Group 1. There was a positive and significant correlation (r = 0.52, p = 0.002) between the degree of septal deviation and total turbinate volume. When the total turbinate volume of the patients with different types of septal deviation was compared in Group 3, a statistically significant difference (p = 0.001) was observed. Regression analysis revealed that the septal deviation angle (SDA) (p = 0.001) had a relationship with total turbinate volume. From the results of the study we can conclude that the total turbinate volume is higher in patients with nasal septal deviation. It can also be concluded that the septal deviation angle has a positive correlation with total turbinate volume. The data obtained from the study can be useful in post-surgical follow up and evaluation of patients with nasal septal deviation and hypertrophied inferior nasal turbinate.
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Affiliation(s)
- Shishir Shetty
- Department of Oral and Craniofacial Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
| | - Saad Al-Bayatti
- Department of Oral and Craniofacial Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
| | | | - Natheer H. Al-Rawi
- Department of Oral and Craniofacial Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
| | - Vinayak Kamath
- Department of Public Health Dentistry, Goa Dental College, Goa, India
| | - Shoaib Rahman Tippu
- Department of Diagnostic and Surgical Dental Sciences, Gulf Medical University, Ajman, United Arab Emirates
| | - Sangeetha Narasimhan
- Department of Oral and Craniofacial Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
| | - Sausan Al Kawas
- Department of Oral and Craniofacial Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
| | - Walid Elsayed
- College of Dentistry, Gulf Medical University, Ajman, United Arab Emirates
| | - Kumuda Rao
- Department of Oral Medicine and Radiology, Nitte (Deemed to be University), Mangalore, India
| | - Renita Castelino
- Department of Oral Medicine and Radiology, Nitte (Deemed to be University), Mangalore, India
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Murakami W, Won Choi H, Joines MM, Hoyt A, Doepke L, McCann KE, Salamon N, Sayre J, Lee-Felker S. Quantitative Predictors of Response to Neoadjuvant Chemotherapy on Dynamic Contrast-enhanced 3T Breast MRI. JOURNAL OF BREAST IMAGING 2022; 4:168-176. [PMID: 38422427 DOI: 10.1093/jbi/wbab095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Indexed: 03/02/2024]
Abstract
OBJECTIVE To assess whether changes in quantitative parameters on breast MRI better predict pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer than change in volume. METHODS This IRB-approved retrospective study included women with newly diagnosed breast cancer who underwent 3T MRI before and during NAC from January 2013 to December 2019 and underwent surgery at our institution. Clinical data such as age, histologic diagnosis and grade, biomarker status, clinical stage, maximum index cancer dimension and volume, and surgical pathology (presence or absence of in-breast pCR) were collected. Quantitative parameters were calculated using software. Correlations between clinical features and MRI quantitative measures in pCR and non-pCR groups were assessed using univariate and multivariate logistic regression. RESULTS A total of 182 women with a mean age of 52 years (range, 26-79 years) and 187 cancers were included. Approximately 45% (85/182) of women had pCR at surgery. Stepwise multivariate regression analysis showed statistical significance for changes in quantitative parameters (increase in time to peak and decreases in peak enhancement, wash out, and Kep [efflux rate constant]) for predicting pCR. These variables in combination predicted pCR with 81.2% accuracy and an area under the curve (AUC) of 0.878. The AUCs of change in index cancer volume and maximum dimension were 0.767 and 0.613, respectively. CONCLUSION Absolute changes in quantitative MRI parameters between pre-NAC MRI and intra-NAC MRI could help predict pCR with excellent accuracy, which was greater than changes in index cancer volume and maximum dimension.
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Affiliation(s)
- Wakana Murakami
- University of California at Los Angeles David Geffen School of Medicine, Department of Radiological Sciences, Los Angeles, CA, USA
- Showa University Graduate School of Medicine, Department of Radiology, Shinagawa-ku, Tokyo, Japan
| | - Hyung Won Choi
- University of California at Los Angeles David Geffen School of Medicine, Department of Radiological Sciences, Los Angeles, CA, USA
| | - Melissa M Joines
- University of California at Los Angeles David Geffen School of Medicine, Department of Radiological Sciences, Los Angeles, CA, USA
| | - Anne Hoyt
- University of California at Los Angeles David Geffen School of Medicine, Department of Radiological Sciences, Los Angeles, CA, USA
| | - Laura Doepke
- University of California at Los Angeles David Geffen School of Medicine, Department of Radiological Sciences, Los Angeles, CA, USA
| | - Kelly E McCann
- University of California at Los Angeles David Geffen School of Medicine, Department of Medicine, Los Angeles, CA, USA
| | - Noriko Salamon
- University of California at Los Angeles David Geffen School of Medicine, Department of Radiological Sciences, Los Angeles, CA, USA
| | - James Sayre
- University of California at Los Angeles Fielding School of Public Health, Department of Biostatistics, Los Angeles, CA, USA
| | - Stephanie Lee-Felker
- University of California at Los Angeles David Geffen School of Medicine, Department of Radiological Sciences, Los Angeles, CA, USA
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Saadat S, Fritz C, Tran D, Parry N, Yuhan BT, Bolduan A, Thorpe E. A Systematic Review of Cervical Ganglioneuromas. OTO Open 2022. [DOI: 10.1177/2473974x221106784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Objective To perform a systematic review of the literature evaluating clinical characteristics and management of cervical ganglioneuromas (CGNs). Data Sources PubMed, Embase, and Cochrane Library databases were searched. Data such as patient demographics, imaging, and treatments were obtained. Review Methods Pertinent studies were downloaded, and the full text was reviewed by 4 authors (N.P., S.S., C.F., D.T.). Results were reported via the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-analyses). Results Fifty-two studies with 58 patients were identified in the literature. Of the 58 patients, 22 were adults and 36 were pediatric. The most common reported location of CGN was within the parapharyngeal space (76%), followed by the retropharyngeal (19%) and paravertebral/prevertebral (7%) spaces. The most common presenting symptoms included a nontender mass (29.3%), dysphagia (17.2%), and hoarseness (10.3%). Interestingly, the average tumor volume for patients with postoperative Horner’s syndrome was 183 mm3 (n = 21, 47.7%) vs 946 mm3 in patients without Horner’s syndrome (n = 23, 52.3%). This represents a statistically significant finding ( P = .018). There exists no significant difference in tumor volumes between adult and pediatric patients with Horner’s syndrome ( P = .645). Conclusion CGN is a rare tumor of the sympathetic nervous system. Management should involve complete surgical excision with biopsy. We found that patients with small-volume CGNs are significantly more likely to experience postoperative Horner’s syndrome. This finding is independent of age and should therefore be taken into consideration in any patient with suspected CGN.
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Affiliation(s)
- Saad Saadat
- Oakland University William Beaumont School of Medicine, Rochester Hills, Michigan, USA
| | - Christian Fritz
- Oakland University William Beaumont School of Medicine, Rochester Hills, Michigan, USA
| | - Deanna Tran
- Oakland University William Beaumont School of Medicine, Rochester Hills, Michigan, USA
| | - Nathan Parry
- Oakland University William Beaumont School of Medicine, Rochester Hills, Michigan, USA
| | - Brian T. Yuhan
- Oakland University William Beaumont School of Medicine, Rochester Hills, Michigan, USA
- Department of Otolaryngology–Head and Neck Surgery, Loyola University Medical Center, Maywood, Illinois, USA
| | - Alyssa Bolduan
- Department of Otolaryngology–Head and Neck Surgery, Loyola University Medical Center, Maywood, Illinois, USA
| | - Eric Thorpe
- Department of Otolaryngology–Head and Neck Surgery, Loyola University Medical Center, Maywood, Illinois, USA
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Barsoum I, Tawedrous E, Faragalla H, Yousef GM. Histo-genomics: digital pathology at the forefront of precision medicine. ACTA ACUST UNITED AC 2020; 6:203-212. [PMID: 30827078 DOI: 10.1515/dx-2018-0064] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Accepted: 09/28/2018] [Indexed: 12/26/2022]
Abstract
The toughest challenge OMICs face is that they provide extremely high molecular resolution but poor spatial information. Understanding the cellular/histological context of the overwhelming genetic data is critical for a full understanding of the clinical behavior of a malignant tumor. Digital pathology can add an extra layer of information to help visualize in a spatial and microenvironmental context the molecular information of cancer. Thus, histo-genomics provide a unique chance for data integration. In the era of a precision medicine, a four-dimensional (4D) (temporal/spatial) analysis of cancer aided by digital pathology can be a critical step to understand the evolution/progression of different cancers and consequently tailor individual treatment plans. For instance, the integration of molecular biomarkers expression into a three-dimensional (3D) image of a digitally scanned tumor can offer a better understanding of its subtype, behavior, host immune response and prognosis. Using advanced digital image analysis, a larger spectrum of parameters can be analyzed as potential predictors of clinical behavior. Correlation between morphological features and host immune response can be also performed with therapeutic implications. Radio-histomics, or the interface of radiological images and histology is another emerging exciting field which encompasses the integration of radiological imaging with digital pathological images, genomics, and clinical data to portray a more holistic approach to understating and treating disease. These advances in digital slide scanning are not without technical challenges, which will be addressed carefully in this review with quick peek at its future.
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Affiliation(s)
- Ivraym Barsoum
- Department of Pathology and Molecular Medicine, Faculty of Health Sciences, Queen's University, Kingston, Ontario, Canada
| | - Eriny Tawedrous
- Department of Laboratory Medicine, and the Keenan Research Centre for Biomedical Science at the Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada
| | - Hala Faragalla
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
| | - George M Yousef
- Department of Laboratory Medicine, and the Keenan Research Centre for Biomedical Science at the Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada.,Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, 555 University Avenue, Toronto, ON M5G 1X8, Canada
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Tot T, Gere M, Hofmeyer S, Bauer A, Pellas U. The subgross morphology of breast carcinomas: a single-institution series of 2033 consecutive cases documented in large-format histology slides. Virchows Arch 2019; 476:373-381. [PMID: 31410558 DOI: 10.1007/s00428-019-02641-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 07/22/2019] [Accepted: 07/30/2019] [Indexed: 10/26/2022]
Abstract
A large-format histology technique represents the most convenient method for documenting and assessing the subgross morphological prognostic parameters of breast cancer (i.e., the distribution of the tumor's invasive and in situ components, disease extent, and tumor size), especially when used in conjunction with systematic radiological-pathological correlation. Here we report a consecutive series of 2033 breast carcinomas operated on in Dalarna, Sweden, with a particular focus on these subgross parameters. We separately analyzed the distributions of the in situ and invasive components of the tumors and then combined these into an aggregate pattern when both components were present. We found that 40% of breast carcinomas had a simple (unifocal) subgross morphology, while 60% had a complex morphology presenting with multifocal or diffuse components. Extensive tumors (occupying a total volume of breast tissue with the greatest dimension being ≥ 40 mm) were more common in complex cases, occurring in 66% of multifocal cases and 88% of diffuse cases, compared with only 5% of unifocal cases. Compared with luminal A-like tumors, HER2-expressing tumors exhibited a significantly larger extent. Triple-negative and basal-like carcinomas tended to have a larger tumor size (based on the largest dimension of the largest invasive focus). In this report, we discuss the prognostic impact of these parameters and the necessity of their correct assessment in the diagnostic routine.
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Affiliation(s)
- Tibor Tot
- Pathology & Cytology Dalarna, County Hospital Falun, Falun, Sweden.
| | - Maria Gere
- Pathology & Cytology Dalarna, County Hospital Falun, Falun, Sweden
| | - Syster Hofmeyer
- Pathology & Cytology Dalarna, County Hospital Falun, Falun, Sweden
| | - Annette Bauer
- Pathology & Cytology Dalarna, County Hospital Falun, Falun, Sweden
| | - Ulrika Pellas
- Pathology & Cytology Dalarna, County Hospital Falun, Falun, Sweden.,Center for Clinical Research Dalarna, Falun, Sweden
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Clarke GM, Holloway CMB, Zubovits JT, Nofech-Mozes S, Murray M, Liu K, Wang D, Kiss A, Yaffe MJ. Three-dimensional tumor visualization of invasive breast carcinomas using whole-mount serial section histopathology: implications for tumor size assessment. Breast Cancer Res Treat 2019; 174:669-677. [PMID: 30612274 DOI: 10.1007/s10549-018-05122-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Accepted: 12/26/2018] [Indexed: 12/30/2022]
Abstract
PURPOSE Linear tumor size (T-size) estimated with conventional histology informs breast cancer management. Previously we demonstrated significant differences in margin and focality estimates using conventional histology versus digital whole-mount serial sections (WMSS). Using WMSS we can measure T-size or volume. Here, we compare WMSS T-size with volume, and with T-size measured conventionally. We also compare the ellipsoid model for calculating tumor volume to direct, WMSS measurement. METHODS Two pathologists contoured regions of invasive carcinoma and measured T-size from both WMSS and (simulated) conventional sections in 55 consecutive lumpectomy specimens. Volume was measured directly from the contours. Measurements were compared using the paired t-test or Spearman's rank-order correlation. A five-point 'border index' was devised and assigned to each case to parametrize tumor shape considering 'compactness' or cellularity. Tumor volumes calculated assuming ellipsoid geometry were compared with direct, WMSS measurements. RESULTS WMSS reported significantly larger T-size than conventional histology in the majority of cases [61.8%, 34/55; means = (2.34 cm; 1.99 cm), p < 0.001], with a 16.4% (9/55) rate of 'upstaging'. The majority of discordances were due to undersampling. T-size and volume were strongly correlated (r = 0.838, p < 0.001). Significantly lower volume was obtained with WMSS versus ellipsoid modeling [means = (1.18 cm3; 1.45 cm3), p < 0.001]. CONCLUSIONS Significantly larger T-size is measured with WMSS than conventionally, due primarily to undersampling in the latter. Volume and linear size are highly correlated. Diffuse tumors interspersed with normal or non-invasive elements may be sampled less extensively than more localized masses. The ellipsoid model overestimates tumor volume.
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Affiliation(s)
- G M Clarke
- Physical Sciences Platform, Sunnybrook Research Institute, Room C7-27c 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
| | - C M B Holloway
- Department of Surgery, Faculty of Medicine, University of Toronto, Toronto, Canada
- Department of Surgery, Sunnybrook Health Sciences Centre, Room T2-015 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
| | - J T Zubovits
- Department of Laboratory Medicine and Pathobiology, Faculty of Medicine, University of Toronto, Toronto, Canada
- Department of Pathology, Scarborough and Rouge Hospital, 3030 Birchmount Road, Toronto, ON, M1W 3W3, Canada
| | - S Nofech-Mozes
- Department of Laboratory Medicine and Pathobiology, Faculty of Medicine, University of Toronto, Toronto, Canada
- Sunnybrook Health Sciences Centre, Room E423a 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
| | - M Murray
- Physical Sciences Platform, Sunnybrook Research Institute, Room C7-48a 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
| | - K Liu
- Physical Sciences Platform, Sunnybrook Research Institute, Room C7-27a 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
| | - D Wang
- Physical Sciences Platform, Sunnybrook Research Institute, Room C7-27a 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
| | - A Kiss
- Research Design and Biostatistics, Sunnybrook Research Institute, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Room G106 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
| | - M J Yaffe
- Departments of Medical Biophysics and Medical Imaging, Faculty of Medicine, University of Toronto, Toronto, Canada.
- Physical Sciences Platform, Sunnybrook Research Institute, Room S6-57 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
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Yaffe MJ. Emergence of "Big Data" and Its Potential and Current Limitations in Medical Imaging. Semin Nucl Med 2018; 49:94-104. [PMID: 30819400 DOI: 10.1053/j.semnuclmed.2018.11.010] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Although electronic imaging was performed in the early 1950s in nuclear medicine, it was the introduction of computed tomography in 1972 that caused a revolution in medical imaging in that it marked the beginning of the inevitable transformation to digital imaging. This transformation is now more or less complete. While initially these CT images were relatively small, comprised of only about 6400 pixels per slice, the steady move toward higher spatial resolution, multislice imaging, digital radiography, and fluoroscopy rapidly increased the size of images and the amount of data required to be stored, processed, displayed, and moved about in a medical imaging department. The more recent introduction of digital pathology with submicron-sized pixels and the need for color further increases these demands. Rising work volumes in hospital, a push for cost containment, and a move toward greater precision in diagnosis and treatment of disease all work together to motivate the development of automated image analysis algorithms and techniques to improve efficiencies in in vivo imaging and pathology. This may require bringing together information from different imaging and nonimaging sources within the institution. While technological development has provided practical means for storage of the burgeoning data load and the use of multiple processors and high-speed networks has enabled more sophisticated analysis locally or in the cloud, challenges remain in terms of the ability to integrate data from different systems, the development of appropriately annotated image bases for training and testing of algorithms, and issues around privacy and ownership in obtaining access to patient-related data.
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Affiliation(s)
- Martin J Yaffe
- Physical Sciences Program, Sunnybrook Health Sciences Centre and The University of Toronto, Toronto, ON, Canada.
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Ogunleke A, Recur B, Balacey H, Chen HH, Delugin M, Hwu Y, Javerzat S, Petibois C. 3D chemical imaging of the brain using quantitative IR spectro-microscopy. Chem Sci 2018; 9:189-198. [PMID: 29629087 PMCID: PMC5869290 DOI: 10.1039/c7sc03306k] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2017] [Accepted: 10/13/2017] [Indexed: 01/14/2023] Open
Abstract
Three-dimensional (3D) histology is the next frontier for modern anatomo-pathology. Characterizing abnormal parameters in a tissue is essential to understand the rationale of pathology development. However, there is no analytical technique, in vivo or histological, that is able to discover such abnormal features and provide a 3D distribution at microscopic resolution. Here, we introduce a unique high-throughput infrared (IR) microscopy method that combines automated image correction and subsequent spectral data analysis for 3D-IR image reconstruction. We performed spectral analysis of a complete organ for a small animal model, a mouse brain with an implanted glioma tumor. The 3D-IR image is reconstructed from 370 consecutive tissue sections and corrected using the X-ray tomogram of the organ for an accurate quantitative analysis of the chemical content. A 3D matrix of 89 × 106 IR spectra is generated, allowing us to separate the tumor mass from healthy brain tissues based on various anatomical, chemical, and metabolic parameters. We demonstrate that quantitative metabolic parameters can be extracted from the IR spectra for the characterization of the brain vs. tumor metabolism (assessing the Warburg effect in tumors). Our method can be further exploited by searching for the whole spectral profile, discriminating tumor vs. healthy tissue in a non-supervised manner, which we call 'spectromics'.
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Affiliation(s)
- Abiodun Ogunleke
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
| | - Benoit Recur
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
| | - Hugo Balacey
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
| | - Hsiang-Hsin Chen
- Academia Sinica , Institute of Physics , 128 Sec. 2, Academia Rd., Nankang , Taipei 11529 , Taiwan , Republic of China
| | - Maylis Delugin
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
| | - Yeukuang Hwu
- Academia Sinica , Institute of Physics , 128 Sec. 2, Academia Rd., Nankang , Taipei 11529 , Taiwan , Republic of China
| | - Sophie Javerzat
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
| | - Cyril Petibois
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
- Academia Sinica , Institute of Physics , 128 Sec. 2, Academia Rd., Nankang , Taipei 11529 , Taiwan , Republic of China
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3D Quantitative Chemical Imaging of Tissues by Spectromics. Trends Biotechnol 2017; 35:1194-1207. [DOI: 10.1016/j.tibtech.2017.08.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Revised: 07/31/2017] [Accepted: 08/04/2017] [Indexed: 12/14/2022]
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Mertzanidou T, Hipwell JH, Reis S, Hawkes DJ, Ehteshami Bejnordi B, Dalmis M, Vreemann S, Platel B, van der Laak J, Karssemeijer N, Hermsen M, Bult P, Mann R. 3D volume reconstruction from serial breast specimen radiographs for mapping between histology and 3D whole specimen imaging. Med Phys 2017; 44:935-948. [PMID: 28064435 PMCID: PMC6849622 DOI: 10.1002/mp.12077] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2016] [Revised: 11/10/2016] [Accepted: 12/18/2016] [Indexed: 11/11/2022] Open
Abstract
PURPOSE In breast imaging, radiological in vivo images, such as x-ray mammography and magnetic resonance imaging (MRI), are used for tumor detection, diagnosis, and size determination. After excision, the specimen is typically sliced into slabs and a small subset is sampled. Histopathological imaging of the stained samples is used as the gold standard for characterization of the tumor microenvironment. A 3D volume reconstruction of the whole specimen from the 2D slabs could facilitate bridging the gap between histology and in vivo radiological imaging. This task is challenging, however, due to the large deformation that the breast tissue undergoes after surgery and the significant undersampling of the specimen obtained in histology. In this work, we present a method to reconstruct a coherent 3D volume from 2D digital radiographs of the specimen slabs. METHODS To reconstruct a 3D breast specimen volume, we propose the use of multiple target neighboring slices, when deforming each 2D slab radiograph in the volume, rather than performing pairwise registrations. The algorithm combines neighborhood slice information with free-form deformations, which enables a flexible, nonlinear deformation to be computed subject to the constraint that a coherent 3D volume is obtained. The neighborhood information provides adequate constraints, without the need for any additional regularization terms. RESULTS The volume reconstruction algorithm is validated on clinical mastectomy samples using a quantitative assessment of the volume reconstruction smoothness and a comparison with a whole specimen 3D image acquired for validation before slicing. Additionally, a target registration error of 5 mm (comparable to the specimen slab thickness of 4 mm) was obtained for five cases. The error was computed using manual annotations from four observers as gold standard, with interobserver variability of 3.4 mm. Finally, we illustrate how the reconstructed volumes can be used to map histology images to a 3D specimen image of the whole sample (either MRI or CT). CONCLUSIONS Qualitative and quantitative assessment has illustrated the benefit of using our proposed methodology to reconstruct a coherent specimen volume from serial slab radiographs. To our knowledge, this is the first method that has been applied to clinical breast cases, with the goal of reconstructing a whole specimen sample. The algorithm can be used as part of the pipeline of mapping histology images to ex vivo and ultimately in vivo radiological images of the breast.
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Affiliation(s)
- Thomy Mertzanidou
- Centre for Medical Image ComputingUniversity College LondonWC1E 6BTLondonUK
| | - John H. Hipwell
- Centre for Medical Image ComputingUniversity College LondonWC1E 6BTLondonUK
| | - Sara Reis
- Centre for Medical Image ComputingUniversity College LondonWC1E 6BTLondonUK
| | - David J. Hawkes
- Centre for Medical Image ComputingUniversity College LondonWC1E 6BTLondonUK
| | | | - Mehmet Dalmis
- Diagnostic Image Analysis GroupRadboud University Medical Center6500 HBNijmegenThe Netherlands
| | - Suzan Vreemann
- Diagnostic Image Analysis GroupRadboud University Medical Center6500 HBNijmegenThe Netherlands
| | - Bram Platel
- Diagnostic Image Analysis GroupRadboud University Medical Center6500 HBNijmegenThe Netherlands
| | - Jeroen van der Laak
- Diagnostic Image Analysis GroupRadboud University Medical Center6500 HBNijmegenThe Netherlands
| | - Nico Karssemeijer
- Diagnostic Image Analysis GroupRadboud University Medical Center6500 HBNijmegenThe Netherlands
| | - Meyke Hermsen
- Department of PathologyRadboud University Medical Center6500 HBNijmegenThe Netherlands
| | - Peter Bult
- Department of PathologyRadboud University Medical Center6500 HBNijmegenThe Netherlands
| | - Ritse Mann
- Department of RadiologyRadboud University Medical Center6500 HBNijmegenThe Netherlands
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12
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Shojaii R, Martel AL. Optimized SIFTFlow for registration of whole-mount histology to reference optical images. J Med Imaging (Bellingham) 2016; 3:047501. [PMID: 27774494 DOI: 10.1117/1.jmi.3.4.047501] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Accepted: 09/28/2016] [Indexed: 11/14/2022] Open
Abstract
The registration of two-dimensional histology images to reference images from other modalities is an important preprocessing step in the reconstruction of three-dimensional histology volumes. This is a challenging problem because of the differences in the appearances of histology images and other modalities, and the presence of large nonrigid deformations which occur during slide preparation. This paper shows the feasibility of using densely sampled scale-invariant feature transform (SIFT) features and a SIFTFlow deformable registration algorithm for coregistering whole-mount histology images with blockface optical images. We present a method for jointly optimizing the regularization parameters used by the SIFTFlow objective function and use it to determine the most appropriate values for the registration of breast lumpectomy specimens. We demonstrate that tuning the regularization parameters results in significant improvements in accuracy and we also show that SIFTFlow outperforms a previously described edge-based registration method. The accuracy of the histology images to blockface images registration using the optimized SIFTFlow method was assessed using an independent test set of images from five different lumpectomy specimens and the mean registration error was [Formula: see text].
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Affiliation(s)
- Rushin Shojaii
- University of Toronto , Department of Medical Biophysics, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada
| | - Anne L Martel
- University of Toronto, Department of Medical Biophysics, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada; Sunnybrook Research Institute, Physical Sciences, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada
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13
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The cost of accuracy: A budget impact analysis of whole-mount histopathology processing for patients with breast cancer undergoing breast conservation. J Cancer Policy 2016. [DOI: 10.1016/j.jcpo.2016.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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14
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Hong NJL, Clarke GM, Yaffe MJ, Holloway CMB. Cost-effectiveness analysis of whole-mount pathology processing for patients with early breast cancer undergoing breast conservation. ACTA ACUST UNITED AC 2016; 23:S23-31. [PMID: 26985143 DOI: 10.3747/co.23.2917] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Obtaining accurate histopathologic detail for breast lumpectomy specimens is challenging because of sampling and loss of three-dimensional conformational features with conventional processing. The whole-mount (wm) technique is a novel method of serial pathologic sectioning designed to optimize cross-sectional visualization of resected specimens and determination of margin status. METHODS Using a Markov chain cohort simulation cost-effectiveness model, we compared conventional processing with wm technique for breast lumpectomies. Cost-effectiveness was evaluated from the perspective of the Canadian health care system and compared using incremental cost-effectiveness ratios (icers) for cost per quality-adjusted life-year (qaly) over a 10-year time horizon. Deterministic and probabilistic sensitivity analyses were performed to test the robustness of the model with willingness-to-pay (wtp) thresholds of $0-$100,000. Costs are reported in adjusted 2014 Canadian dollars, discounted at a rate of 3%. RESULTS Compared with conventional processing, wm processing is more costly ($19,989 vs. $18,427) but generates 0.03 more qalys over 10 years. The icer is $45,414, indicating that this additional amount is required for each additional qaly obtained. The model was robust to all variance in parameters, with the prevalence of positive margins accounting for most of the model's variability. CONCLUSIONS After a wtp threshold of $45,414, wm processing becomes cost-effective and ultimately generates fewer recurrences and marginally more qalys over time. Excellent baseline outcomes for the current treatment of breast cancer mean that incremental differences in survival are small. However, the overall benefit of the wm technique should be considered in the context of achieving improved accuracy and not just enhancements in clinical effectiveness.
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Affiliation(s)
- N J Look Hong
- Division of Surgical Oncology, Sunnybrook Health Sciences Centre, Toronto, ON;; Department of Surgery, University of Toronto, Toronto, ON
| | - G M Clarke
- Sunnybrook Research Institute, Toronto, ON
| | - M J Yaffe
- Sunnybrook Research Institute, Toronto, ON
| | - C M B Holloway
- Division of Surgical Oncology, Sunnybrook Health Sciences Centre, Toronto, ON;; Department of Surgery, University of Toronto, Toronto, ON
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15
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Clarke GM, Holloway CMB, Zubovits JT, Nofech-Mozes S, Liu K, Murray M, Wang D, Yaffe MJ. Whole-mount pathology of breast lumpectomy specimens improves detection of tumour margins and focality. Histopathology 2016; 69:35-44. [DOI: 10.1111/his.12912] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Accepted: 11/27/2015] [Indexed: 11/26/2022]
Affiliation(s)
- Gina M Clarke
- Physical Sciences; Sunnybrook Research Institute; Toronto Ontario Canada
| | - Claire M B Holloway
- Department of Surgery; Sunnybrook Health Sciences Centre; Toronto Ontario Canada
- Department of Surgery; Faculty of Medicine; University of Toronto; Toronto Ontario Canada
| | - Judit T Zubovits
- Department of Pathology; The Scarborough Hospital; Toronto Ontario Canada
- Department of Laboratory Medicine and Pathobiology; University of Toronto; Toronto Ontario Canada
| | - Sharon Nofech-Mozes
- Department of Laboratory Medicine and Pathobiology; University of Toronto; Toronto Ontario Canada
- Department of Anatomic Pathology; Sunnybrook Health Sciences Centre; Toronto Ontario Canada
| | - Kela Liu
- Physical Sciences; Sunnybrook Research Institute; Toronto Ontario Canada
| | - Mayan Murray
- Physical Sciences; Sunnybrook Research Institute; Toronto Ontario Canada
| | - Dan Wang
- Physical Sciences; Sunnybrook Research Institute; Toronto Ontario Canada
| | - Martin J Yaffe
- Physical Sciences; Sunnybrook Research Institute; Toronto Ontario Canada
- Departments of Medical Biophysics and Medical Imaging; University of Toronto; Toronto Ontario Canada
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