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Authors are the souls of any journal, and deserve much respect. To publish a journal manuscripts are needed from authors. Authors have a great responsibility for producing facts of their work in terms of number and results truthfully and an individual honesty is expected from authors in this regards. Both ways its true "No authors-No manuscripts-No journals" and "No journals–No manuscripts–No authors". Reviewing a manuscript is also a very responsible and important task of any peer-reviewed journal and to be taken seriously. It needs knowledge on the subject, sincerity, honesty and determination. Although the process of reviewing a manuscript is a time consuming task butit is expected to give one's best remarks within the time frame of the journal.
Salient features of the JCDR: It is a biomedical, multidisciplinary (including all medical and dental specialities), e-journal, with wide scope and extensive author support. At the same time, a free text of manuscript is available in HTML and PDF format. There is fast growing authorship and readership with JCDR as this can be judged by the number of articles published in it i e; in Feb 2007 of its first issue, it contained 5 articles only, and now in its recent volume published in April 2011, it contained 67 manuscripts. This e-journal is fulfilling the commitments and objectives sincerely, (as stated by Editor-in-chief in his preface to first edition) i e; to encourage physicians through the internet, especially from the developing countries who witness a spectrum of disease and acquire a wealth of knowledge to publish their experiences to benefit the medical community in patients care. I also feel that many of us have work of substance, newer ideas, adequate clinical materials but poor in medical writing and hesitation to submit the work and need help. JCDR provides authors help in this regards.
Timely publication of journal: Publication of manuscripts and bringing out the issue in time is one of the positive aspects of JCDR and is possible with strong support team in terms of peer reviewers, proof reading, language check, computer operators, etc. This is one of the great reasons for authors to submit their work with JCDR. Another best part of JCDR is "Online first Publications" facilities available for the authors. This facility not only provides the prompt publications of the manuscripts but at the same time also early availability of the manuscripts for the readers.
Indexation and online availability: Indexation transforms the journal in some sense from its local ownership to the worldwide professional community and to the public.JCDR is indexed with Embase & EMbiology, Google Scholar, Index Copernicus, Chemical Abstracts Service, Journal seek Database, Indian Science Abstracts, to name few of them. Manuscriptspublished in JCDR are available on major search engines ie; google, yahoo, msn.
In the era of fast growing newer technologies, and in computer and internet friendly environment the manuscripts preparation, submission, review, revision, etc and all can be done and checked with a click from all corer of the world, at any time. Of course there is always a scope for improvement in every field and none is perfect. To progress, one needs to identify the areas of one's weakness and to strengthen them.
It is well said that "happy beginning is half done" and it fits perfectly with JCDR. It has grown considerably and I feel it has already grown up from its infancy to adolescence, achieving the status of standard online e-journal form Indian continent since its inception in Feb 2007. This had been made possible due to the efforts and the hard work put in it. The way the JCDR is improving with every new volume, with good quality original manuscripts, makes it a quality journal for readers. I must thank and congratulate Dr Hemant Jain, Editor-in-Chief JCDR and his team for their sincere efforts, dedication, and determination for making JCDR a fast growing journal.
Every one of us: authors, reviewers, editors, and publisher are responsible for enhancing the stature of the journal. I wish for a great success for JCDR."
Thanking you
With sincere regards
Dr. Rajendra Kumar Ghritlaharey, M.S., M. Ch., FAIS
Associate Professor,
Department of Paediatric Surgery, Gandhi Medical College & Associated
Kamla Nehru & Hamidia Hospitals Bhopal, Madhya Pradesh 462 001 (India)
E-mail: drrajendrak1@rediffmail.com
On May 11,2011
Dr. Shankar P.R.
"On looking back through my Gmail archives after being requested by the journal to write a short editorial about my experiences of publishing with the Journal of Clinical and Diagnostic Research (JCDR), I came across an e-mail from Dr. Hemant Jain, Editor, in March 2007, which introduced the new electronic journal. The main features of the journal which were outlined in the e-mail were extensive author support, cash rewards, the peer review process, and other salient features of the journal.
Over a span of over four years, we (I and my colleagues) have published around 25 articles in the journal. In this editorial, I plan to briefly discuss my experiences of publishing with JCDR and the strengths of the journal and to finally address the areas for improvement.
My experiences of publishing with JCDR: Overall, my experiences of publishing withJCDR have been positive. The best point about the journal is that it responds to queries from the author. This may seem to be simple and not too much to ask for, but unfortunately, many journals in the subcontinent and from many developing countries do not respond or they respond with a long delay to the queries from the authors 1. The reasons could be many, including lack of optimal secretarial and other support. Another problem with many journals is the slowness of the review process. Editorial processing and peer review can take anywhere between a year to two years with some journals. Also, some journals do not keep the contributors informed about the progress of the review process. Due to the long review process, the articles can lose their relevance and topicality. A major benefit with JCDR is the timeliness and promptness of its response. In Dr Jain's e-mail which was sent to me in 2007, before the introduction of the Pre-publishing system, he had stated that he had received my submission and that he would get back to me within seven days and he did!
Most of the manuscripts are published within 3 to 4 months of their submission if they are found to be suitable after the review process. JCDR is published bimonthly and the accepted articles were usually published in the next issue. Recently, due to the increased volume of the submissions, the review process has become slower and it ?? Section can take from 4 to 6 months for the articles to be reviewed. The journal has an extensive author support system and it has recently introduced a paid expedited review process. The journal also mentions the average time for processing the manuscript under different submission systems - regular submission and expedited review.
Strengths of the journal: The journal has an online first facility in which the accepted manuscripts may be published on the website before being included in a regular issue of the journal. This cuts down the time between their acceptance and the publication. The journal is indexed in many databases, though not in PubMed. The editorial board should now take steps to index the journal in PubMed. The journal has a system of notifying readers through e-mail when a new issue is released. Also, the articles are available in both the HTML and the PDF formats. I especially like the new and colorful page format of the journal. Also, the access statistics of the articles are available. The prepublication and the manuscript tracking system are also helpful for the authors.
Areas for improvement: In certain cases, I felt that the peer review process of the manuscripts was not up to international standards and that it should be strengthened. Also, the number of manuscripts in an issue is high and it may be difficult for readers to go through all of them. The journal can consider tightening of the peer review process and increasing the quality standards for the acceptance of the manuscripts. I faced occasional problems with the online manuscript submission (Pre-publishing) system, which have to be addressed.
Overall, the publishing process with JCDR has been smooth, quick and relatively hassle free and I can recommend other authors to consider the journal as an outlet for their work."
Dr. P. Ravi Shankar
KIST Medical College, P.O. Box 14142, Kathmandu, Nepal.
E-mail: ravi.dr.shankar@gmail.com
On April 2011 Anuradha
Dear team JCDR, I would like to thank you for the very professional and polite service provided by everyone at JCDR. While i have been in the field of writing and editing for sometime, this has been my first attempt in publishing a scientific paper.Thank you for hand-holding me through the process.
Dr. Anuradha
E-mail: anuradha2nittur@gmail.com
On Jan 2020
Original article / research
Full Version
Brain Diffusion in Brainstem Infarctions and Lesion Segmentation using Fluid-attenuation Inversion Recovery: A Diagnostic Accuracy Study
Correspondence Address :
Dr. Noha Abdelfattah Ahmed Madkour,
Radiologist, Department of Diagnostic and Interventional Radiology, Kasr Alainy Hospital, Faculty of Medicine, Cairo University, Cairo, Egypt.
E-mail: drnohamadkour@kasralainy.edu.eg
Introduction: Diffusion can efficiently detect infratentorial and brainstem infarctions. Fluid-attenuation Inversion Recovery (FLAIR) is a widely used Magnetic Resonance Imaging (MRI) technique for the segmentation of brain lesions and strokes.
Aim: To investigate the sensitivity of the Lesion Prediction Algorithm (LPA) within the Lesion Segmentation Tool (LST) in the automated segmentation of acute and subacute brainstem infarctions.
Materials and Methods: This study was a retrospective diagnostic accuracy study where 24 patients with brainstem infarctions were referred from the Emergency Department to the Department of Radiodiagnosis at Kasr Alainy Hospital, Cairo University, Egypt. The study was conducted from September 2016 to June 2023. It included 24 patients (14 males and 10 females) with acute and subacute brainstem infarctions. MRI of the brain and diffusion were performed on all patients. Automated segmentation of brainstem infarctions using FLAIR was conducted in all cases. Manual and segmented volumes of brainstem infarctions were calculated. Sensitivity and accuracy of the LPA within the LST in automated segmentation of acute and subacute brainstem infarctions were evaluated. Pearson correlation was used to correlate volumes of White Matter Lesion (WML) burden in patients with brainstem infarctions and patients’ age.
Results: The mean age of the participants was 51.75±11.95 years. The sensitivity of the LPA in automated segmentation of acute and subacute brainstem infarctions was 63.6% and 76.9%, respectively. An insignificant correlation (r=0.08; p-value=0.68) between the volumes of WML burden in patients with brainstem infarctions and patients’ age was noted.
Conclusion: The sensitivity of the automated method in the segmentation of subacute brainstem infarctions was higher than that in acute brainstem infarctions.
Automated segmentation, Infratentorial, Magnetic resonance imaging, Strokes
Brainstem strokes are relatively uncommon. Many studies have demonstrated the validity of brain diffusion in the identification of acute infratentorial and brainstem infarctions (1),(2),(3),(4). Diffusion can efficiently differentiate between acute and chronic brain infarctions (5). Cerebral infarctions, also known as ischaemic strokes, cause serious disabilities and mortalities (6),(7). On MRI of the brain, several semi-automated procedures have been designed for the localisation and segmentation of brain strokes (8),(9). Automated segmentation provides rapid lesion demarcation. FLAIR is a widely used MRI technique for brain lesion segmentation (10),(11),(12),(13). Multimodal automated methods designed through machine learning approaches have been applied for the segmentation of acute and subacute brain infarctions (14),(15),(16). LST is an automated method for lesion segmentation, including WML, strokes, and other brain diseases. LPA is a subset of LST that requires the FLAIR sequence for lesion segmentation (10),(17),(18),(19). Although some researchers have discussed the utility of automated methods in the segmentation of cerebral infarctions, studies focusing on the segmentation of brainstem infarctions have been rare (20). Recently, automated deep learning procedures have been developed for the segmentation of acute ischaemic cerebral and infratentorial infarctions (21),(22),(23). Thus, the present study aimed to explore the accuracy of LPA within LST in the automated segmentation of acute and subacute brainstem infarctions.
This study was a retrospective diagnostic accuracy study where 24 patients with brainstem infarctions were referred from the Emergency Department to the Department of Radiodiagnosis at Kasr Alainy Hospital, Cairo University, Egypt. The study was conducted during the period from September 2016 to June 2023. The study was approved by the Institutional Research Ethical Committee of the Faculty of Medicine, Cairo University, with registration number (N-42-2016). The requirement for patient consent has been waived.
Inclusion criteria:
• Patients with acute and subacute brainstem infarctions (ischaemic strokes).
• Patients with brainstem infarctions and associated brain lesions.
Exclusion criteria:
• Chronic brainstem infarctions.
• Haemorrhagic strokes, demyelinating brain disease, brain tumours, inflammation, and head trauma.
• Children, individuals with metallic implants, and postoperative cases.
Study Procedure
The initial diagnosis of brainstem infarctions was based on the clinical presentation of the acute onset of hemiplegia, nystagmus, dysarthria, and MRI brain, including diffusion images.
Image acquisition: Imaging was performed on a 1.5 Tesla MRI superconducting scanner (Intera; Philips Medical Systems, Best, the Netherlands). Images were obtained using a phased-array head coil. MRI of the brain was performed, including axial T1-weighted Images (T1WI) with Repetition Time (TR)/Echo Time (TE)=477 ms/15s, axial T2WI, coronal, and sagittal images with TR/TE=3659 ms/100s, and axial FLAIR images with TR/TE/Time of Inversion (TI): 4948 ms/120s/2000. A slice thickness of 6 mm, with an intersection gap of 1.5 mm, sections were acquired with a 240 mm×240 mm Field Of View (FOV) and image matrix of 256×256. Diffusion-weighted Images (DWI) were acquired in the axial plane using a single-shot Echoplanar imaging-spin echo pulse sequence with the following parameters: TR/TE=3909/95, FOV=24 cm×24 cm, slice thickness=5.5 mm, interslice gap=1 mm, matrix size of 128×128. ADC maps were generated from the DWIs (b=1000 s/mm2).
Manual measurement of volumes of brainstem infarctions: Volumes of brainstem infarctions were manually measured from FLAIR images using Radiant Digital Imaging and Communications in Medicine (DICOM) Viewer. The volume of brainstem infarction=area of infarction in maximum dimensions×number of slices with brainstem infarctions×slice thickness (24),(25),(26).
Preprocessing and automated segmentation: FLAIR images were realigned, co-registered, smoothed, and spatially normalised to Montreal Neurological Institute (MNI) template space using the Statistical Parametric Mapping (SPM12) software package (www.fil.ion.ucl.ac.uk). The output FLAIR images were fed into the LST toolbox (LST) (version 2.0.15) implemented in (SPM12) running in MATLAB R2017a (The MathWorks, Inc., Natick, MA). LPA within the LST toolbox was operated on all cases with a kappa value of 0.3. Automated segmentation and volumetry for brain WML burden, including brainstem infarctions and associated WML, were performed on all patients, generating coloured overlaid FLAIR output images. Volumes of segmented brainstem infarctions were calculated from each slice. The volumes of the segmented brainstem infarctions obtained by the automated method were compared to the original manual volumes. ‘Incomplete segmentation’ means that less than 70% of the original volume of the brainstem infarction was segmented by the automated method, and ‘near complete segmentation’ means that more than or at 70% of the original volume of the brainstem infarction was segmented by the automated method. True positives (complete or near-complete segmentation) and false negatives (completely unsegmented or incomplete segmentation) for the automated method (LPA) were calculated.
Statistical Analysis
Sensitivity, accuracy, and Dice Similarity Coefficient (DSC) of segmentation of acute and subacute brainstem infarctions using LPA were obtained. Pearson’s correlation was used to correlate the volumes of WML burden in patients with brainstem infarctions and the patients’ age. Continuous data were expressed as mean (range)±SD (Standard deviation). Statistical analysis was performed using the International Business Machines (IBM) Statistical Package for the Social Sciences (SPSS) software version 22.0 (IBM, Armonk, NY, USA). A p-value <0.05 was considered significant.
The current study included 24 cases with acute and subacute brainstem infarctions, with a mean age of 51.75±11.95 years.
Image interpretation: The initial diagnosis of acute and subacute brainstem infarctions was established using diffusion and ADC maps. Acute brainstem infarctions were hyperintense in T2, FLAIR, DWI, and hypointense in the ADC map (indicating restricted diffusion). Subacute brainstem infarctions were hyperintense in T2, FLAIR, DWI, and ADC map [Table/Fig-1a-d]. Pontine infarctions were the most common site for brainstem infarctions (Table/Fig 2). Brainstem infarctions were more common on the left-side (62.5%) compared to the right-side (37.5%).
Patients with brainstem infarctions were associated with brain WMLs showing hyperintense signals in T2 and FLAIR (Table/Fig 3).
Evaluation of automated segmentation of brainstem infarctions using LPA: True positives and sensitivity of LPA in automated segmentation of brainstem infarctions were higher in subacute infarctions than in acute infarctions (Table/Fig 4),(Table/Fig 5). Complete unsegmentation by the automated method (LPA) was noted in one case with acute brainstem infarction (Table/Fig 3). An insignificant correlation between volumes of WML burden in patients with brainstem infarctions and patients’ age was noted (Table/Fig 6). Results of the segmentation of brain strokes from the current study and other studies were summarised in (Table/Fig 7) (27),(28),(29),(30).
In the current study, the pons was the most common location for brainstem infarctions, which is consistent with studies concerned with brainstem strokes (31),(32).
In line with the current study, Zhu H et al., proposed a multimodal automated approach to segment acute cerebral and infratentorial strokes, with a DSC of 0.64 and sensitivity of 0.561 (27). De Haan B et al., conducted a study on the segmentation of acute brain strokes using the FLAIR sequence and found a reasonable agreement between manual and semi-automated methods in segmenting brain strokes, with a slightly higher DSC than that obtained in the current study, likely due to the presence of large supratentorial infarctions in the former study (28).
Feng C et al., investigated a multispectral automated method using multiple MRI sequences, including FLAIR, to segment subacute brain infarctions and reported a DSC of 0.55±0.3 for the automated method, which aligns with the current results (29). In the current study, the sensitivity of LPA using FLAIR was higher in subacute brainstem infarctions than in acute infarctions, possibly due to insufficient or faint signal intensity in FLAIR images for lesion mapping in early acute infarctions.
A hybrid semi-automated method was proposed by Rajinikanth V and Satapathy SC to segment Ischaemic Stroke Lesions (ISL) using axial FLAIR with a sensitivity of 0.99 which was slightly higher than that obtained by the current study in segmentation of ischaemic brainstem strokes (30). Recent studies have utilised diffusion in the automated segmentation of cerebral and brainstem infarctions due to the high detectability of acute infarctions [33,34]. Earlier studies have shown comparable DSC between manual and semi-automated segmentation of acute brain strokes when applying diffusion and FLAIR datasets separately in lesion segmentation, reflecting the expanded use of the FLAIR sequence (28),(30). WMLs depicted in FLAIR commonly co-exist with brain infarctions due to shared vascular risk factors (35),(36),(37).
In a study led by Guerrero R et al., multiple automated methods were initiated to segment WMLs and accompanying ischaemic brain strokes in FLAIR and found a significant association between automated volumes of WMLs obtained by LPA and patients’ age, which contradicted the current study, likely due to different sample populations and small-sized brainstem infarctions (38). The current research could contribute to the literature by primarily addressing automated segmentation of brainstem infarctions using the FLAIR sequence.
Limitation(s)
Limitations of the study included a small sample size, small-sized infarctions, the retrospective nature of the research, and a scarcity of literature reports.
The LPA within the LST was capable of automated segmentation of acute and subacute brainstem infarctions with high accuracy, particularly in subacute infarctions.
DOI: 10.7860/JCDR/2024/66958.19461
Date of Submission: Aug 09, 2023
Date of Peer Review: Oct 20, 2023
Date of Acceptance: Nov 02, 2023
Date of Publishing: May 01, 2024
AUTHOR DECLARATION:
• Financial or Other Competing Interests: None
• Was Ethics Committee Approval obtained for this study? Yes
• Was informed consent obtained from the subjects involved in the study? No
• For any images presented appropriate consent has been obtained from the subjects. NA
PLAGIARISM CHECKING METHODS:
• Plagiarism X-checker: Aug 10, 2023
• Manual Googling: Oct 27, 2023
• iThenticate Software: Oct 30, 2023 (6%)
ETYMOLOGY: Author Origin
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