1
|
Netherton TJ, Duprez D, Patel T, Cifter G, Court LE, Trauernicht C, Aggarwal A. External validation of an algorithm to detect vertebral level mislabeling and autocontouring errors. Phys Imaging Radiat Oncol 2025; 34:100738. [PMID: 40129727 PMCID: PMC11932639 DOI: 10.1016/j.phro.2025.100738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Revised: 02/12/2025] [Accepted: 02/24/2025] [Indexed: 03/26/2025] Open
Abstract
Background and Purpose This work performs external validation of a previously developed vertebral body autocontouring tool and investigates a post-processing method to increase performance to clinically acceptable levels. Materials and Methods Vertebral bodies within CT scans from two separate institutions (40 from institution A and 41 from institution B) were automatically 1) localized and enumerated, 2) contoured, and 3) screened as a means of quality assurance (QA) for errors. Identification rate, contour acceptability rate, and QA accuracy were calculated to assess the tool's performance. These metrics were compared to those calculated on CTs from the model's original training dataset, and a post-processing technique was developed to increase the tool's accuracy. Results When testing the model without post-processing on external datasets A and B, accurate identification rates of 83 % and 92 % were achieved for vertebral bodies (C1-L5). Identification rate, contour acceptability rate and QA accuracy were reduced on both datasets compared to accuracies and rates measured on the model's orginal testing dataset. After algorithm adjustment, identification rate across all vertebrae increased on average by 4 % (p < 0.01) for dataset A and also 4 % on the dataset B (p = 0.01). Conclusions A post-processing adjustment within the machine learning pipeline increased performance of vertebral body localization accuracy to acceptable levels for clinical use. External validation of machine learning and deep learning tools is essential to perform before deployment to different insitutions.
Collapse
Affiliation(s)
- Tucker J. Netherton
- Department of Radiation Physics, Division of Radiation Oncology, University of Texas MD Anderson Cancer Center, United States
| | - Didier Duprez
- Division of Medical Physics, Tygerberg Hospital and Stellenbosch University, South Africa
| | - Tina Patel
- Department of Radiotherapy Guy’s & St Thomas NHS Foundation Trust London, the United Kingdom of Great Britain and Northern Ireland
| | - Gizem Cifter
- Department of Radiation Physics, Division of Radiation Oncology, University of Texas MD Anderson Cancer Center, United States
| | - Laurence E. Court
- Department of Radiation Physics, Division of Radiation Oncology, University of Texas MD Anderson Cancer Center, United States
| | - Christoph Trauernicht
- Division of Medical Physics, Tygerberg Hospital and Stellenbosch University, South Africa
| | - Ajay Aggarwal
- Department of Radiotherapy Guy’s & St Thomas NHS Foundation Trust London, the United Kingdom of Great Britain and Northern Ireland
- Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, the United Kingdom of Great Britain and Northern Ireland
| |
Collapse
|
2
|
Keil F, Hagemes F, Setzer M, Behmanesh B, Marquardt G, Hattingen E, Prinz V, Czabanka M, Bruder M. Minimal Invasive Pre-Op CT-Guided Gold-Fiducials in Local Anesthesia for Easy Level Localization in Thoracic Spine Surgery. J Clin Med 2024; 13:5690. [PMID: 39407750 PMCID: PMC11476588 DOI: 10.3390/jcm13195690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2024] [Revised: 09/06/2024] [Accepted: 09/21/2024] [Indexed: 10/20/2024] Open
Abstract
Background: The accurate identification of intraoperative levels is of paramount importance in spinal surgery, particularly in cases of obesity or anatomical anomalies affecting the thoracic spine. The aim of this work was to clarify whether the preoperative percutaneous placement of fiducial markers under local anesthesia only, with minimal discomfort to the patient, can be performed safely and efficiently. Methods: Patients treated at our institution between June 2019 and June 2020 for thoracic intraspinal lesions with preoperative percutaneous gold fiducial placement were analyzed. A total of 10 patients underwent CT-guided gold fiducial placement 2-48 h prior to surgery on an outpatient or inpatient basis. Patient characteristics, CT intervention time, and perioperative complications were recorded. Results: In all cases, the gold markers were placed under local anesthesia alone and were easily visualized intraoperatively with fluoroscopy. There was no preoperative dislocation or malposition. The procedure was performed without X-ray exposure to the neuroradiology interventionalist. The average CT intervention time from the planning scout to the final control time was 14.3 min. The percentage of anatomical norm variants in our observation group was high, as 2 of the 10 patients had lumbarization of the first sacral vertebra, resulting in a six-link lumbar spine. Conclusions: Preoperative CT-guided transcutaneous submuscular placement of gold markers under local anesthesia is a practical and safe method for rapid and accurate intraoperative level determination in thoracic spine surgery in a time-saving minimally invasive manner. The virtually painless procedure can be performed either preoperatively on an outpatient basis or as an inpatient procedure.
Collapse
Affiliation(s)
- Fee Keil
- Institute of Neuroradiology, University hospital Frankfurt, 60528 Frankfurt am Main, Germany;
| | - Frank Hagemes
- Department of Neurosurgery, University hospital Frankfurt, 60528 Frankfurt am Main, Germany (M.S.); (B.B.); (G.M.); (V.P.); (M.C.)
| | - Matthias Setzer
- Department of Neurosurgery, University hospital Frankfurt, 60528 Frankfurt am Main, Germany (M.S.); (B.B.); (G.M.); (V.P.); (M.C.)
| | - Bedjan Behmanesh
- Department of Neurosurgery, University hospital Frankfurt, 60528 Frankfurt am Main, Germany (M.S.); (B.B.); (G.M.); (V.P.); (M.C.)
| | - Gerhard Marquardt
- Department of Neurosurgery, University hospital Frankfurt, 60528 Frankfurt am Main, Germany (M.S.); (B.B.); (G.M.); (V.P.); (M.C.)
| | - Elke Hattingen
- Institute of Neuroradiology, University hospital Frankfurt, 60528 Frankfurt am Main, Germany;
| | - Vincent Prinz
- Department of Neurosurgery, University hospital Frankfurt, 60528 Frankfurt am Main, Germany (M.S.); (B.B.); (G.M.); (V.P.); (M.C.)
| | - Marcus Czabanka
- Department of Neurosurgery, University hospital Frankfurt, 60528 Frankfurt am Main, Germany (M.S.); (B.B.); (G.M.); (V.P.); (M.C.)
| | - Markus Bruder
- Department of Neurosurgery, Kantonspital Aarau, 5001 Aarau, Switzerland;
| |
Collapse
|
3
|
Hong W, Huang X, Li T, Luo J, Liu Y, Huang S, Chen Z, He B, Wen Y, Lin Y. A Self-Developed Mobility Augmented Reality System Versus Conventional X-rays for Spine Positioning in Intraspinal Tumor Surgery: A Case-Control Study. Neurospine 2024; 21:984-993. [PMID: 39363474 PMCID: PMC11456929 DOI: 10.14245/ns.2448188.094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 06/15/2024] [Accepted: 06/17/2024] [Indexed: 10/05/2024] Open
Abstract
OBJECTIVE To evaluate the efficacy of a self-developed mobile augmented reality navigation system (MARNS) in guiding spinal level positioning during intraspinal tumor surgery based on a dual-error theory. METHODS This retrospective study enrolled patients diagnosed with intraspinal tumors admitted to Fujian Provincial Hospital between May and November 2023. The participants were divided into conventional x-rays and self-developed MARNS groups according to the localization methods they received. Position time, length of intraoperative incision variation, and location accuracy were systematically compared. RESULTS A total of 41 patients (19 males) with intraspinal tumors were included, and MARNS was applied to 21 patients. MARNS achieved successful lesion localization in all patients with an error of 0.38±0.12 cm. Compared to x-rays, MARNS significantly reduced positioning time (129.00±13.03 seconds vs. 365.00±60.43 seconds, p<0.001) and length of intraoperative incision variation (0.14 cm vs. 0.67 cm, p=0.009). CONCLUSION The self-developed MARNS, based on augmented reality technology for lesion visualization and perpendicular projection, offers a radiation-free complement to conventional x-rays.
Collapse
Affiliation(s)
- Wenyao Hong
- The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
- Department of Neurosurgery, Fujian Provincial Hospital, Fuzhou, China
- Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
- Fujian Engineering Research Center of Joint Intelligent Medical Engineering, Fuzhou, China
| | - Xiaohua Huang
- The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Tian Li
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
- Department of Neurosurgery, Fujian Provincial Hospital, Fuzhou, China
- Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
| | - Juntao Luo
- Fujian Engineering Research Center of Joint Intelligent Medical Engineering, Fuzhou, China
- School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
| | - Yuqing Liu
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
- Department of Neurosurgery, Fujian Provincial Hospital, Fuzhou, China
- Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
- Fujian Engineering Research Center of Joint Intelligent Medical Engineering, Fuzhou, China
| | - Shengyue Huang
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
- Department of Neurosurgery, Fujian Provincial Hospital, Fuzhou, China
- Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
| | - Zhongyi Chen
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
- Department of Neurosurgery, Fujian Provincial Hospital, Fuzhou, China
- Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
- Fujian Engineering Research Center of Joint Intelligent Medical Engineering, Fuzhou, China
| | - Bingwei He
- Fujian Engineering Research Center of Joint Intelligent Medical Engineering, Fuzhou, China
- School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
| | - Yuxing Wen
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
- Department of Neurosurgery, Fujian Provincial Hospital, Fuzhou, China
- Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
| | - Yuanxiang Lin
- The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| |
Collapse
|
4
|
Charters JA, Luximon D, Petragallo R, Neylon J, Low DA, Lamb JM. Automated detection of vertebral body misalignments in orthogonal kV and MV guided radiotherapy: application to a comprehensive retrospective dataset. Biomed Phys Eng Express 2024; 10:025039. [PMID: 38382110 DOI: 10.1088/2057-1976/ad2baa] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 02/21/2024] [Indexed: 02/23/2024]
Abstract
Objective. In image-guided radiotherapy (IGRT), off-by-one vertebral body misalignments are rare but potentially catastrophic. In this study, a novel detection method for such misalignments in IGRT was investigated using densely-connected convolutional networks (DenseNets) for applications towards real-time error prevention and retrospective error auditing.Approach. A total of 4213 images acquired from 527 radiotherapy patients aligned with planar kV or MV radiographs were used to develop and test error-detection software modules. Digitally reconstructed radiographs (DRRs) and setup images were retrieved and co-registered according to the clinically applied alignment contained in the DICOM REG files. A semi-automated algorithm was developed to simulate patient positioning errors on the anterior-posterior (AP) and lateral (LAT) images shifted by one vertebral body. A DenseNet architecture was designed to classify either AP images individually or AP and LAT image pairs. Receiver-operator characteristic curves (ROC) and areas under the curves (AUC) were computed to evaluate the classifiers on test subsets. Subsequently, the algorithm was applied to the entire dataset in order to retrospectively determine the absolute off-by-one vertebral body error rate for planar radiograph guided RT at our institution from 2011-2021.Main results. The AUCs for the kV models were 0.98 for unpaired AP and 0.99 for paired AP-LAT. The AUC for the MV AP model was 0.92. For a specificity of 95%, the paired kV model achieved a sensitivity of 99%. Application of the model to the entire dataset yielded a per-fraction off-by-one vertebral body error rate of 0.044% [0.0022%, 0.21%] for paired kV IGRT including one previously unreported error.Significance. Our error detection algorithm was successful in classifying vertebral body positioning errors with sufficient accuracy for retrospective quality control and real-time error prevention. The reported positioning error rate for planar radiograph IGRT is unique in being determined independently of an error reporting system.
Collapse
Affiliation(s)
- John A Charters
- Department of Radiation Oncology, University of California, Los Angeles, CA 90095, United States of America
| | - Dishane Luximon
- Department of Radiation Oncology, University of California, Los Angeles, CA 90095, United States of America
| | - Rachel Petragallo
- Department of Radiation Oncology, University of California, Los Angeles, CA 90095, United States of America
| | - Jack Neylon
- Department of Radiation Oncology, University of California, Los Angeles, CA 90095, United States of America
| | - Daniel A Low
- Department of Radiation Oncology, University of California, Los Angeles, CA 90095, United States of America
| | - James M Lamb
- Department of Radiation Oncology, University of California, Los Angeles, CA 90095, United States of America
| |
Collapse
|
5
|
Kehayias CE, Yan Y, Bontempi D, Quirk S, Bitterman DS, Bredfeldt JS, Aerts HJWL, Mak RH, Guthier CV. Prospective deployment of an automated implementation solution for artificial intelligence translation to clinical radiation oncology. Front Oncol 2024; 13:1305511. [PMID: 38239639 PMCID: PMC10794768 DOI: 10.3389/fonc.2023.1305511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 12/11/2023] [Indexed: 01/22/2024] Open
Abstract
Introduction Artificial intelligence (AI)-based technologies embody countless solutions in radiation oncology, yet translation of AI-assisted software tools to actual clinical environments remains unrealized. We present the Deep Learning On-Demand Assistant (DL-ODA), a fully automated, end-to-end clinical platform that enables AI interventions for any disease site featuring an automated model-training pipeline, auto-segmentations, and QA reporting. Materials and methods We developed, tested, and prospectively deployed the DL-ODA system at a large university affiliated hospital center. Medical professionals activate the DL-ODA via two pathways (1): On-Demand, used for immediate AI decision support for a patient-specific treatment plan, and (2) Ambient, in which QA is provided for all daily radiotherapy (RT) plans by comparing DL segmentations with manual delineations and calculating the dosimetric impact. To demonstrate the implementation of a new anatomy segmentation, we used the model-training pipeline to generate a breast segmentation model based on a large clinical dataset. Additionally, the contour QA functionality of existing models was assessed using a retrospective cohort of 3,399 lung and 885 spine RT cases. Ambient QA was performed for various disease sites including spine RT and heart for dosimetric sparing. Results Successful training of the breast model was completed in less than a day and resulted in clinically viable whole breast contours. For the retrospective analysis, we evaluated manual-versus-AI similarity for the ten most common structures. The DL-ODA detected high similarities in heart, lung, liver, and kidney delineations but lower for esophagus, trachea, stomach, and small bowel due largely to incomplete manual contouring. The deployed Ambient QAs for heart and spine sites have prospectively processed over 2,500 cases and 230 cases over 9 months and 5 months, respectively, automatically alerting the RT personnel. Discussion The DL-ODA capabilities in providing universal AI interventions were demonstrated for On-Demand contour QA, DL segmentations, and automated model training, and confirmed successful integration of the system into a large academic radiotherapy department. The novelty of deploying the DL-ODA as a multi-modal, fully automated end-to-end AI clinical implementation solution marks a significant step towards a generalizable framework that leverages AI to improve the efficiency and reliability of RT systems.
Collapse
Affiliation(s)
- Christopher E. Kehayias
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
| | - Yujie Yan
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
| | - Dennis Bontempi
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, United States
- Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, Netherlands
| | - Sarah Quirk
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
| | - Danielle S. Bitterman
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
| | - Jeremy S. Bredfeldt
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
| | - Hugo J. W. L. Aerts
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, United States
- Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, Netherlands
| | - Raymond H. Mak
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, United States
| | - Christian V. Guthier
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, United States
| |
Collapse
|
6
|
Siminski CP, Carr CM, Kallmes DF, Oien MP, Atkinson JLD, Benson JC, Diehn FE, Kim DK, Liebo GB, Lehman VT, Madhavan AA, Mark IT, Morris PP, Shlapak DP, Verdoorn JT, Morris JM. Fluoroscopy- and CT-Guided Gold Fiducial Marker Placement for Intraoperative Localization during Spinal Surgery: Review of 179 Cases at a Single Institution-Technique and Safety Profile. AJNR Am J Neuroradiol 2023; 44:618-622. [PMID: 37080723 PMCID: PMC10171395 DOI: 10.3174/ajnr.a7854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/16/2023] [Indexed: 04/22/2023]
Abstract
BACKGROUND AND PURPOSE Wrong-level spinal surgery, especially in the thoracic spine, remains a challenge for a variety of reasons related to visualization, such as osteopenia, large body habitus, severe kyphosis, radiographic misinterpretation, or anatomic variation. Preoperative fiducial marker placement performed in a dedicated imaging suite has been proposed to facilitate identification of thoracic spine vertebral levels. In this current study, we report our experience using image-guided percutaneous gold fiducial marker placement to enhance the accuracy and safety of thoracic spinal surgical procedures. MATERIALS AND METHODS A retrospective review was performed of all fluoroscopy- or CT-guided gold fiducial markers placed at our institution between January 3, 2019, and March 16, 2022. A chart review of 179 patients was performed detailing the procedural approach and clinical information. In addition, the method of gold fiducial marker placement (fluoroscopy/CT), procedure duration, spinal level of the gold fiducial marker, radiation dose, fluoroscopy time, surgery date, and complications (including whether wrong-level surgery occurred) were recorded. RESULTS A total of 179 patients (104 female) underwent gold fiducial marker placement. The mean age was 57 years (range, 12-96 years). Fiducial marker placement was performed by 13 different neuroradiologists. All placements were technically successful without complications. All 179 (100%) operations were performed at the correct level. Most fiducial markers (143) were placed with fluoroscopy with the most common location at T6-T8. The most common location for placement in CT was at T3 and T4. CONCLUSIONS All operations guided with gold fiducial markers were performed at the correct level. There were no complications of fiducial marker placement.
Collapse
Affiliation(s)
- C P Siminski
- From the Mayo Clinic Alix School of Medicine (C.P.S.)
| | - C M Carr
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - D F Kallmes
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - M P Oien
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | | | - J C Benson
- Department of Neuroradiology (J.L.D.A., J.C.B.)
| | - F E Diehn
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - D K Kim
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - G B Liebo
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - V T Lehman
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - A A Madhavan
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - I T Mark
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - P P Morris
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - D P Shlapak
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - J T Verdoorn
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| | - J M Morris
- Department of Radiology (C.M.C., D.F.K., M.P.O., F.E.D., D.K.K., G.B.L., V.T.L., A.A.M., I.T.M., P.P.M., D.P.S., J.T.V., J.M.M.), Mayo Clinic, Rochester, Minnesota
| |
Collapse
|
7
|
Abul K, Özmen BB, Yücekul A, Zulemyan T, Yılgör Ç, Alanay A. If you look this way, you will see it: cranial shift in adolescent idiopathic scoliosis. Spine Deform 2023; 11:105-114. [PMID: 35921040 DOI: 10.1007/s43390-022-00560-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 07/23/2022] [Indexed: 10/16/2022]
Abstract
INTRODUCTION Anatomical variations in the spine can be seen in each transitional border, either toward the skull as 'cranial shifts' or away as caudal shifts. Cranial shifting (CS) occurs when there is presence of occipitalization, C7 cervical costae or prominent transverse processes, thoracolumbar transitional vertebrae (TLTV) at T12 level, L5 sacralization, and sacrococcygeal fusion. We termed the coexistence of sacralization of L5 and absence or remarkable reduction of T12 rib size in AIS as Abul cranial shift (ACS). In this descriptive clinical study, primary aim was to investigate the incidence of ACS in AIS. METHODS Retrospective analysis of 187 surgically treated AIS cases was performed. Demographic data were recorded. The incidence of the specific set of anatomic variations including lumbosacral transitional vertebrae, TLTV, transverse process changes in C7 vertebrae, and posterior lumbosacral neural arch cleft formations (NACf) were evaluated in the radiological images. RESULTS 36 (19%) of 187 cases had ACS. ACS was detected in only 1 of 19 male cases (5%), while in 35 of 168 female cases (21%). Forty-one cases had sacralization of L5 (22%). There were only eleven pair of ribs in 14 (7%) of 187 cases and 10 (28%) of 36 ACS cases. Forty cases had NACf (21%). ACS and NACf coexistence were observed in 8 (22%) of 36 ACS cases. CONCLUSION Accurate spinal column assessment is critical in adolescent idiopathic scoliosis (AIS). ACS may be observed in up to one in five AIS cases and its presence should not be neglected to avoid wrong level surgery.
Collapse
Affiliation(s)
- Kadir Abul
- Department of Orthopedics and Traumatology, Başaksehir Çam and Sakura City Hospital, Istanbul, Turkey.
| | - Berk Barış Özmen
- Acibadem Mehmet Ali Aydinlar University School of Medicine, Istanbul, Turkey
| | - Altuğ Yücekul
- Department of Orthopedics and Traumatology, Acibadem Mehmet Ali Aydinlar University School of Medicine, Istanbul, Turkey
| | - Tais Zulemyan
- Comprehensive Spine Center, Acibadem University Maslak Hospital, Istanbul, Turkey
| | - Çağlar Yılgör
- Department of Orthopedics and Traumatology, Acibadem Mehmet Ali Aydinlar University School of Medicine, Istanbul, Turkey
| | - Ahmet Alanay
- Department of Orthopedics and Traumatology, Acibadem Mehmet Ali Aydinlar University School of Medicine, Istanbul, Turkey
| |
Collapse
|
8
|
Naznin RA, Haq MA, Sumi SA, Ahmad R, Haque M. A Semi-quantitative Evaluation of Out-to-Out Agenesis of Posterior Wall in a Dry Human Sacrum in Bangladesh. Cureus 2022; 14:e31163. [DOI: 10.7759/cureus.31163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/06/2022] [Indexed: 11/07/2022] Open
|
9
|
Porzionato A, Macchi V, Stecco C, Boscolo-Berto R, Loukas M, Tubbs RS, De Caro R. Clinical Anatomy and Medical Malpractice-A Narrative Review with Methodological Implications. Healthcare (Basel) 2022; 10:1915. [PMID: 36292362 PMCID: PMC9601975 DOI: 10.3390/healthcare10101915] [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: 08/28/2022] [Revised: 09/25/2022] [Accepted: 09/27/2022] [Indexed: 11/04/2022] Open
Abstract
Anatomical issues are intrinsically included in medico-legal methodology, however, higher awareness would be needed about the relevance of anatomy in addressing medico-legal questions in clinical/surgical contexts. Forensic Clinical Anatomy has been defined as "the practical application of Clinical Anatomy to the ascertainment and evaluation of medico-legal problems". The so-called individual anatomy (normal anatomy, anatomical variations, or anatomical modifications due to development, aging, para-physiological conditions, diseases, or surgery) may acquire specific relevance in medico-legal ascertainment and evaluation of cases of supposed medical malpractice. Here, we reviewed the literature on the relationships between anatomy, clinics/surgery, and legal medicine. Some methodological considerations were also proposed concerning the following issues: (1) relevant aspects of individual anatomy may arise from the application of methods of ascertainment, and they may be furtherly ascertained through specific anatomical methodology; (2) data about individual anatomy may help in the objective application of the criteria of evaluation (physio-pathological pathway, identification-evaluation of errors, causal value, damage estimation) and in final judgment about medical responsibility/liability. Awareness of the relevance of individual anatomy (risk of iatrogenic lesions, need for preoperative diagnostic procedures) should be one of the principles guiding the clinician; medico-legal analyses can also take advantage of its contribution in terms of ascertainment/evaluation.
Collapse
Affiliation(s)
- Andrea Porzionato
- Section of Anatomy, Department of Neuroscience, University of Padova, Via Gabelli, 65, 35127 Padova, Italy
| | - Veronica Macchi
- Section of Anatomy, Department of Neuroscience, University of Padova, Via Gabelli, 65, 35127 Padova, Italy
| | - Carla Stecco
- Section of Anatomy, Department of Neuroscience, University of Padova, Via Gabelli, 65, 35127 Padova, Italy
| | - Rafael Boscolo-Berto
- Section of Anatomy, Department of Neuroscience, University of Padova, Via Gabelli, 65, 35127 Padova, Italy
| | - Marios Loukas
- Department of Anatomical Sciences, True Blue Campus, St. George’s University, St. George 1473, Grenada
| | - Ronald Shane Tubbs
- Department of Anatomical Sciences, True Blue Campus, St. George’s University, St. George 1473, Grenada
- Department of Neurosurgery, Tulane University, New Orleans, LA 70112, USA
| | - Raffaele De Caro
- Section of Anatomy, Department of Neuroscience, University of Padova, Via Gabelli, 65, 35127 Padova, Italy
| |
Collapse
|
10
|
Naznin RA, Moniruzzaman M, Sumi SA, Benzir M, Jahan I, Ahmad R, Haque M. Sacralization of Coccygeal Vertebra: A Descriptive Observational Study in Bangladesh. Cureus 2022; 14:e27496. [PMID: 35919212 PMCID: PMC9339143 DOI: 10.7759/cureus.27496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/31/2022] [Indexed: 11/25/2022] Open
Abstract
Background: In the sacrococcygeal region, anatomical variation is due to the sacralization of the coccygeal vertebra, which is the due union of/fusion of the fifth sacral with the first coccygeal vertebra of five couples of sacral foramina under-detected or asymptomatic beyond radiological assessment. That is why it is challenging to know the cause of coccydynia, caudal block failure, the difficult second stage of labor, and perineal tears. The present study aims to improve knowledge about the anatomical variation of sacralization of the coccygeal vertebra. Additionally, to find the prevalence of sacralization of coccygeal vertebra in Sylhet, Bangladesh. Methods: This study was performed on 60 parched, totally calcified, typical sacra of mature-age individuals of undetermined sexes, fulfilling the inclusion criteria from the bone bank of the osteology museum of the Department of Anatomy, Sylhet MAG Osmani Medical College, Sylhet, Bangladesh, from July 2017 to June 2018. Sex determination of the collected unknown sacra was conducted using discriminant function analysis. It was found that 50% (30) were male and 50% (30%) were female. The unpaired t-tests and chi-square were utilized to determine the statistical significance. Results: Out of 60 sacra, eight (13.33%) samples presented with sacralization. This study found that males had significantly higher straight (p=0.05) and curved (p=0.05) lengths of sacrococcygeal vertebrae. The sacrococcygeal curvature index (SCI) showed statistically significant (p=0.05) differences between the sexes. Conclusion: Sacralization may exert an impact on the caudal block. It could extend the second stage of the labor process with perineal tears. Therefore, knowledge about the anatomical variation of the coccygeal vertebra is essential.
Collapse
|
11
|
Proks P, Johansen TM, Nývltová I, Komenda D, Černochová H, Vignoli M. Vertebral Formulae and Congenital Vertebral Anomalies in Guinea Pigs: A Retrospective Radiographic Study. Animals (Basel) 2021; 11:ani11030589. [PMID: 33668174 PMCID: PMC7995982 DOI: 10.3390/ani11030589] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 02/16/2021] [Accepted: 02/19/2021] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Guinea pigs are popular pets, but there is still a lack of information about their morphology. Variable morphology of the vertebral column can lead to incorrect localization of spinal diseases or the site of surgical intervention. This study aimed to determine the numerical variants of vertebral column and prevalence, localization, and type of congenital anomalies of the vertebral column. Vertebral column radiographs were reviewed in 240 guinea pigs, and nine numerical variants of the vertebral column were noticed. The most common vertebral formula, seven cervical, 13 thoracic, six lumbar, four sacral, and five to seven caudal vertebrae, was found in 75% of guinea pigs. Congenital anomalies were also found as incidental findings in 12.5% of guinea pigs, mostly in the thoracolumbar and lumbosacral regions. The most common congenital anomalies were a variable morphology of the last pair of ribs in the thoracolumbar region and transitional vertebra with a mixed morphological characteristic of lumbar and sacral vertebrae in the lumbosacral region. The cervical region was the least common region for congenital anomalies of the vertebral column. Our results contribute to the knowledge of clinical morphology in guinea pigs applicable in both, research and clinical practice. Abstract The objectives of this retrospective study of 240 guinea pigs (148 females and 92 males) were to determine the prevalence of different vertebral formulae and the type and anatomical localization of congenital vertebral anomalies (CVA). Radiographs of the cervical (C), thoracic (Th), lumbar (L), sacral (S), and caudal (Cd) part of the vertebral column were reviewed. Morphology and number of vertebrae in each segment of the vertebral column and type and localization of CVA were recorded. In 210/240 guinea pigs (87.50%) with normal vertebral morphology, nine vertebral formulae were found with constant number of C but variable number of Th, L, and S vertebrae: C7/Th13/L6/S4/Cd5-7 (75%), C7/Th13/L6/S3/Cd6-7 (4.17%), C7/Th13/L5/S4/Cd6-7 (2.50%), C7/Th13/L6/S5/Cd5-6 (1.67%), C7/Th12/L6/S4/Cd6 (1.25%), C7/Th13/L7/S4/Cd6 (1.25%), C7/Th13/L7/S3/Cd6-7 (0.83%), C7/Th12/L7/S4/Cd5 (0.42%), C7/Th13/L5/S5/Cd7 (0.42%). CVA were found in 30/240 (12.5%) of guinea pigs, mostly as a transitional vertebra (28/30), which represents 100% of single CVA localised in cervicothoracic (n = 1), thoracolumbar (n = 22) and lumbosacral segments (n = 5). Five morphological variants of thoracolumbar transitional vertebrae (TTV) were identified. Two (2/30) guinea pigs had a combination of CVA: cervical block vertebra and TTV (n = 1) and TTV and lumbosacral transitional vertebra (LTV) (n = 1). These findings suggest that guinea pigs’ vertebral column displays more morphological variants with occasional CVA predominantly transitional vertebrae.
Collapse
Affiliation(s)
- Pavel Proks
- Small Animal Clinic, Faculty of Veterinary Medicine, University of Veterinary and Pharmaceutical Sciences Brno, 61242 Brno, Czech Republic; (T.M.J.); (I.N.); (D.K.)
- Central European Institute of Technology (CEITEC), University of Veterinary and Pharmaceutical Sciences Brno, 61242 Brno, Czech Republic
- Correspondence:
| | - Trude Maria Johansen
- Small Animal Clinic, Faculty of Veterinary Medicine, University of Veterinary and Pharmaceutical Sciences Brno, 61242 Brno, Czech Republic; (T.M.J.); (I.N.); (D.K.)
| | - Ivana Nývltová
- Small Animal Clinic, Faculty of Veterinary Medicine, University of Veterinary and Pharmaceutical Sciences Brno, 61242 Brno, Czech Republic; (T.M.J.); (I.N.); (D.K.)
| | - Dominik Komenda
- Small Animal Clinic, Faculty of Veterinary Medicine, University of Veterinary and Pharmaceutical Sciences Brno, 61242 Brno, Czech Republic; (T.M.J.); (I.N.); (D.K.)
| | - Hana Černochová
- Avian and Exotic Animal Clinic, Faculty of Veterinary Medicine, University of Veterinary and Pharmaceutical Sciences Brno, 61242 Brno, Czech Republic;
| | - Massimo Vignoli
- Faculty of Veterinary Medicine, University of Teramo, Piano D’Accio, 64100 Teramo, Italy;
| |
Collapse
|
12
|
Shah M, Halalmeh DR, Sandio A, Tubbs RS, Moisi MD. Anatomical Variations That Can Lead to Spine Surgery at the Wrong Level: Part III Lumbosacral Spine. Cureus 2020; 12:e9433. [PMID: 32864257 PMCID: PMC7450882 DOI: 10.7759/cureus.9433] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Spine surgery at the wrong level is an undesirable event and unique pitfall in spine surgery. It is detrimental to the relationship between the patient and the surgeon and typically results in profound medical and legal consequences. It falls under the wrong-site surgery sentinel events reporting system. This error is most frequently observed in lumbosacral spine. Several risk factors are implicated; however, anatomical variations of the lumbosacral spine are a major risk factor. The aim of this article was to provide a detailed description of these high-risk anatomical variations, including transitional vertebrae, lumbar ribs, butterfly vertebrae, hemivertebra, block/fused vertebrae, and spinal dysraphism. A literature review was performed in the database PubMed to obtain all relative English-only articles concerning these anatomical variations and their implication in the development of lumbosacral spine surgery at the wrong level. We also described patient characteristics that can lead to lumbosacral surgery at the wrong level such as tumors, infection, previous lumbosacral surgery, obesity, and osteoporosis. Certain techniques to prevent such incorrect surgery were explained. Lumbosacral spine anatomical variations are surgically significant. Awareness of their existence may provide better pre-operative planning and surgical intervention, leading to avoidance of incorrect-level surgery and potentially better clinical outcomes. In addition, collaboration with radiologists and careful examination of patient’s anatomy and characteristics should be exercised, especially in difficult cases.
Collapse
Affiliation(s)
- Manan Shah
- Neurosurgery, Wayne State University/Detroit Medical Center, Detroit, USA
| | - Dia R Halalmeh
- Neurosurgery, Wayne State University/Detroit Medical Center, Detroit, USA
| | - Aubin Sandio
- Neurosurgery, Wayne State University/Detroit Medical Center, Detroit, USA
| | - R Shane Tubbs
- Neurosurgery and Structural & Cellular Biology, Tulane University School of Medicine, New Orleans, USA.,Anatomical Sciences, St. George's University, St. George's, GRD.,Neurosurgery and Ochsner Neuroscience Institute, Ochsner Health System, New Orleans, USA
| | - Marc D Moisi
- Neurosurgery, Wayne State University/Detroit Medical Center, Detroit, USA
| |
Collapse
|