در این بخش نمونه بیان مساله هایی از رشته مهندسی برق در گرایشهای مختلف مطرح و آورده شده که دانشجویان و پژوهشگران محترم با نحوه طرح بیان مساله و نحوه ورود به چنین بحثی آشنا شده و تجربه دقیق با مصداق داشته باشند که برای ورود به بیان مساله پروپوزال و سمینار و پایان نامه و یا مقاله های خود و یا حتی پروژه های درسی که در طول تحصیلات با آنها دست و پنجه نرم میکنند چگونه مواجه شده و چگونه ان را طرح و بیان کنند لذا با مطالعه نمونه های زیر شما با این نکات و شاکله کلی بحث آشنا خواهید شد و اینک چند نمونه بین مساله با ذکر عنوان و مطلب مربوط به بیان مساله طرح و ارایه شده و قابل مطالعه هستند 

🔹 نمونه بیان مسأله در نگارش پروپوزال مهندسی برق(قدرت)

جایابی بهینه ایستگاه‌های شارژ خودرو های الکتریکی در شبکه توزیع متصل به شبکه با استفاده از الگوریتم برنامه ریزی خطی

Optimum placement of electric vehicle charging stations in the on grid distribution network using Integer Linear Programming algorithm

الف : تعريف مسئله :

امروزه معضلات زیست محیطی و افزایش میزان گرمایش جهانی موجب روی آوردن کشورهای صنعتی توسعه یافته و در حال توسعه به سمت انرژی های تجدیدپذیر جهت تامین انرژی مورد نیاز خود شده است. دسترس پذیری بالا و رایگان بودن منابع تجدیدپذیر، از دلایل اصلی بهره مندی از این نوع انرژی در کشورهای مختلف جهان است.

از طرف دیگر سوخت مصرفی اغلب خودروها از منابع سوخت فسیلی، نظیر بنزین و گازوئيل بوده است و همین موضوع سبب آلودگی شدید زیست محیطی در شهرهای صنعتی جهان شده است. از راهکارهای کاربردی جهت حل این مشکل که در برخی کشورها به کار گرفته شده است، می‌توان به بهره براداری از خودروهای الکتریکی اشاره کرد. همان‌طور که از نام آن مشخص است، سوخت مصرفی خودروهای الکتریکی، برق است و انرژی مورد نیاز این نوع خودرو پس از طی مسافت مورد نظر، با شارژ‌ مجدد در ایستگاه‌های شارژ خودروی برقی تامین می‌شود. امروزه در برخی کشورهای جهان مانند چین، ایالات متحده آمریکا، نروژ،‌ انگلستان و آلمان ایستگاه‌های شارژ خودرو به یکی از مهم‌ترین زیرساخت‌های بخش حمل و نقل تبدیل شده اند و تعداد زیادی از این ایستگاه‌های شارژ جهت تامین انرژی مورد نیاز خودروهای الکتریکی در بخش‌های مختلف کشورهای مذکور احداث شده اند. کشور ایران نیز در سال‌های اخیر در تلاش بوده است تا وسایل نقلیه الکتریکی در برخی زیربخش‌های حمل و نقل را افزایش دهد و امروزه تعداد محدودی از ایستگاه‌های شارژ خودرو الکتریکی نیز در شهرهای تهران و اصفهان و .. ایجاد شده اند و با توجه به وضعیت زیست محیطی شهرهای مختلف این کشور، بخش حمل و نقل ناگزیر باید احداث ایستگاه‌های شارژ خودرو در شهرهای دیگر را در دستور کار خود قرار دهد. در این قسمت برخی مزایای بهره مندی از خودروهای الکتریکی معرفی خواهند شد:

یکی از راهکارهای پیشنهادی جهت ادغام بهره مندی از خودروی الکتریکی و انرژی‌های تجدیدپذیر به صورت همزمان، استفاده از فناوری‌های تجدیدپذیر در ایستگاه‌های شارژ خودرو است. در حال حاضر در برخی از ایستگاه‌های شارژ خودروی الکتریکی در جهان از انرژی‌های تجدیدپذیر استفاده می‌شود اما در هیچ کدام از ایستگاه‌های شارژ خودرو در کشور ایران، برق مورد نیاز خودروهای الکتریکی از طریق فناوری‌های تجدیدپذیر تامین نمی‌شود. در نتیجه با توجه به عدم ایجاد ایستگاه‌های شارژ خودروی الکتریکی در بسیاری از شهرهای کشور ایران و پتانسیل نسبتا مناسب تابش خورشید در بخش‌های زیادی از کشور ایران، می‌توان جایابی بهینه جهت احداث ایستگاه شارژ مجهز به پنل‌های خورشیدی جهت تامین انرژی و کلکتور‌های حرارتی خورشیدی جهت تامین گرمایش آب مصرفی در مجموعه ایستگاه شارژ توسط الگوریتم پیشنهادی بر اساس برنامه ریزی خطی را در نظر گرفت. طرح پیشنهادی، ترکیب فناوری ایستگاه شارژ وسایل نقلیه، سیستم خورشیدی فوتوولتائيک و سیستم خورشیدی حرارتی با یک دیگر را بررسی کرده و برای تامین برق مورد نیاز خودروی الکتریکی، از احداث یک نیروگاه خورشیدی در ایستگاه شارژ خودرو جهت تولید برق و برای تامین گرمایش آب مصرفی در مجموعه از احداث یک سیستم حرارتی خورشیدی استفاده می‌کند. 

در این قسمت برخی واژه‌ها و اصطلاحات تخصصی معرفی خواهند شد:

• پنل خورشیدی فوتوولتائیک 

پنل فوتوولتائیک اساساً یک سیستم نیمه هادی حالت جامد است که انرژی نور را به انرژی الکتریکی تبدیل می‌کند و خروجی آن معمولاً برق DC است، در حالی که اکثر لوازم الکتریکی خانگی و صنعتی از جریان متناوب (AC) استفاده می‌کنند. این سیستم انرژی پاک و سبز را ارائه می‌دهد و در طول تولید جریان الکتریکی با پنل‌های فتوولتائیک، هیچ گاز گلخانه ای مضری در محیط منتشر نمی‌شود، بنابراین پنل خورشیدی نوعی فناوری سازگار با محیط زیست است. 

سلول خورشیدی را می توان به صورت یک منبع جریان موازی با یک دیود مدل نمود. منبع جریان، جریان فوتوولتائیک I_PH را تولید می‌کند که رابطه مستقیمی با شدت تابش دارد. زمانی که هیچ نوری برای تولید جریان وجود ندارد، سلول خورشیدی به عنوان یک دیود عمل می‌کند و هنگامی که شدت نور تابید شده به سلول افزایش می‌یابد، جریانی متناسب با شدت نور ورودی به وسیله سلول خورشیدی تولید می‌شود. این جریان نوری بین مقاومت متغیر دیود و بار، با نسبتی که بستگی به مقاومت بار و شدت تابش دارد تقسیم می‌شود. 

• راندمان پنل خورشیدی فوتوولتائیک:

بازده سلول خورشيدي با پارامتر η نشان داده می‌شود که نسبتی از نور تابشی است که به الکتريسيته تبديل می‌شود. در واقع بازده يک سلول خورشیدی به صورت نسبت توان بيشينه خروجی به توان ورودی است که از رابطه ...بدست می‌آيد:

(رابطه ...)                                                     .... = ᶯ     

در این رابطه پارامتر P_in توان تابشی نور ورودي و P_mp توان بيشينه خروجی است که ....

• کلکتور خورشیدی حرارتی

 از انرژی حرارتی خورشید برای اهداف بسیاری از جمله گرم کردن آب، هوا و فضای داخلی ساختمان‌ها و تولید برق استفاده می‌شود. سیستم‌های گرمایش خورشیدی دو نوع کلی دارند:
الف) سیستم‌های غیرفعال، ب) سیستم‌های فعال.

عملکرد سیستم گرمایش خورشیدی غیرفعال به این صورت است که خورشید از پنجره‌های ساختمان می‌تابد و فضای داخلی را گرم می کند اما سیستم‌های گرمایش خورشیدی فعال، سیال گرم شده (هوا یا مایع) را به داخل ساختمان یا یک سیستم ذخیره‌سازی گرما منتقل می‌کنند، تا در زمان نیاز از آن استفاده شود.

🔹 نمونه بیان مسأله در نگارش پروپوزال مهندسی برق

عنوان پیشنهادی پروپوزال (گرایش قدرت):
بهینه‌سازی مصرف انرژی در شبکه‌های هوشمند برق با استفاده از الگوریتم‌های هوش مصنوعی

بیان مسأله:
در دهه‌های اخیر، رشد سریع مصرف انرژی الکتریکی و افزایش وابستگی صنایع و جوامع به برق، ضرورت مدیریت هوشمند منابع انرژی را بیش از پیش آشکار ساخته است. شبکه‌های برق سنتی به دلیل ساختار متمرکز و محدودیت در پیش‌بینی بار، توانایی پاسخ‌گویی به نیازهای پویا و متغیر امروزی را ندارند. از سوی دیگر، ناپایداری تولید انرژی‌های تجدیدپذیر (مانند خورشیدی و بادی) چالش جدی در بهره‌برداری بهینه از این منابع ایجاد کرده است. یکی از راهکارهای نوین، بهره‌گیری از الگوریتم‌های هوش مصنوعی برای پیش‌بینی، کنترل و مدیریت بهینه مصرف انرژی در شبکه‌های هوشمند است. با این وجود، پرسش اصلی این است که چه الگوریتم یا ترکیبی از روش‌های محاسباتی می‌تواند در شرایط واقعی بیشترین دقت، سرعت و کارایی را در کاهش تلفات و افزایش بهره‌وری شبکه فراهم آورد. این خلأ پژوهشی، ضرورت انجام تحقیق در حوزه تلفیق هوش مصنوعی و مهندسی برق قدرت را توجیه می‌کند.

عنوان پیشنهادی پروپوزال (گرایش الکترونیک):
طراحی و شبیه‌سازی تقویت‌کننده‌های کم‌مصرف برای کاربردهای پزشکی قابل‌حمل

بیان مسأله:
با پیشرفت روزافزون فناوری‌های پوشیدنی و پزشکی، نیاز به مدارهای الکترونیکی کوچک، کم‌مصرف و دقیق بیش از گذشته احساس می‌شود. یکی از مهم‌ترین اجزای این سیستم‌ها، تقویت‌کننده‌هایی هستند که قادرند سیگنال‌های ضعیف زیستی را بدون نویز اضافی پردازش کنند. چالش اصلی در این حوزه، دستیابی به طراحی مدارهایی است که ضمن کاهش مصرف انرژی، کیفیت سیگنال را نیز حفظ نمایند. با توجه به اینکه بسیاری از تقویت‌کننده‌های موجود یا توان مصرفی بالایی دارند یا در شرایط واقعی دچار افت عملکرد می‌شوند، این پرسش مطرح است که چگونه می‌توان معماری‌های جدیدی ارائه کرد که همزمان دو ویژگی کلیدی "کم‌مصرف بودن" و "حفظ دقت" را تضمین کند. این نیاز، جایگاه تحقیق و توسعه در طراحی تقویت‌کننده‌های نوین برای کاربردهای پزشکی را پررنگ می‌سازد.

نمونه بیان مساله در نگارش پروپوزال (گرایش مخابرات):
بهبود کیفیت سرویس در شبکه‌های 5G با استفاده از روش‌های یادگیری ماشین

بیان مسأله:
ظهور نسل پنجم شبکه‌های مخابراتی (5G) انقلابی در انتقال داده‌های پرسرعت ایجاد کرده است. با وجود این، افزایش حجم داده‌ها، تنوع کاربران و نیاز به حداقل تأخیر، مدیریت منابع شبکه را به یک چالش اساسی تبدیل کرده است. روش‌های سنتی تخصیص پهنای باند و کنترل ترافیک قادر به پاسخ‌گویی به نیازهای پویای شبکه‌های 5G نیستند. در این راستا، یادگیری ماشین به‌عنوان ابزاری قدرتمند برای تحلیل داده‌های بزرگ و تصمیم‌گیری هوشمندانه، مورد توجه قرار گرفته است. پرسش محوری اینجاست که چگونه می‌توان از الگوریتم‌های یادگیری ماشین برای بهینه‌سازی کیفیت سرویس (QoS) استفاده کرد به گونه‌ای که هم تأخیر شبکه کاهش یابد و هم رضایت کاربران حفظ شود. این شکاف دانشی، ضرورت انجام پژوهش‌های نوین در زمینه کاربرد یادگیری ماشین در شبکه‌های مخابراتی نسل جدید را برجسته می‌سازد.

🔹 نمونه بیان مسأله در نگارش پروپوزال (مهندسی برق – کنترل)

طراحی کنترل‌کننده مقاوم برای سیستم‌های غیرخطی با عدم قطعیت‌های ساختاری

بیان مسأله:
سیستم‌های کنترل صنعتی در شرایط واقعی با عدم قطعیت‌های متعددی همچون تغییرات پارامترها، نویزهای محیطی و غیرخطی بودن دینامیک سیستم‌ها مواجه‌اند. در چنین شرایطی، استفاده از روش‌های کلاسیک کنترل (مانند PID یا کنترل خطی) اغلب پاسخ‌گوی نیازهای عملکردی و پایداری سیستم نیست. به‌ویژه در صنایع حساس نظیر هوافضا، رباتیک، فرآیندهای شیمیایی و سامانه‌های انرژی، کوچک‌ترین انحراف در طراحی کنترل‌کننده می‌تواند منجر به خسارت‌های جبران‌ناپذیر شود.
پژوهش‌های اخیر نشان داده‌اند که طراحی کنترل‌کننده‌های مقاوم و تطبیقی می‌تواند عملکرد سیستم را در برابر عدم قطعیت‌ها بهبود بخشد، اما هنوز پرسش کلیدی این است که کدام روش کنترل مقاوم (مانند H∞، LMI یا کنترل تطبیقی فازی) قادر است بهترین توازن بین پایداری، سرعت پاسخ و مصرف انرژی را برای سیستم‌های غیرخطی پیچیده فراهم آورد. شناسایی و ارائه راهکاری عملی برای این چالش، خلأ پژوهشی موجود را آشکار می‌سازد و ضرورت انجام تحقیق در حوزه کنترل مقاوم سیستم‌های غیرخطی را برجسته می‌کند.

نگارش پروپوزال کارشناسی ارشد و دکتری - نگارش رساله دکتری - نگارش مقاله پژوهشی - نگارش مقاله ISI

Abstract

These instructions give you guidelines for preparing papers for the Journals of The World Academy of Research in Science and Engineering. Use this document as a template if you are using Microsoft Word 6.0 or later. Otherwise, use this document as an instruction set. Define all symbols used in the abstract. Do not cite references in the abstract.

Key words : About four key words or phrases in alphabetical order, separated by commas.

1. 1.INTRODUCTION

Highlight a section that you want to designate with a certain style, then select the appropriate name on the style menu. The style will adjust your fonts and line spacing. Do not change the font sizes or line spacing to squeeze more text into a limited number of pages.

1.1 Final Stage

When you submit your final version, after your paper has been accepted, prepare it in two-column format, including figures and tables.

1.2 Figures

As said, to insert images in Word, position the cursor at the insertion point and either use Insert | Picture | From File or copy the image to the Windows clipboard and then Edit | Paste Special | Picture (with “Float over text” unchecked).

The authors of the accepted manuscripts will be given a copyright form and the form should accompany your final submission.

2. UNITS

Use either SI (MKS) or CGS as primary units. (SI units are strongly encouraged.) English units may be used as secondary

2.1 Figures and Tables

Because the final formatting of your paper is limited in scale, you need to position figures and tables at the top and

bottom of each column. Large figures and tables may span both columns. Place figure captions below the figures; place table titles above the tables. If your figure has two parts, include the labels “(a)” and “(b)” as part of the artwork. Please verify that the figures and tables you mention in the text actually exist. Do not put borders around the outside of your figures. Use the abbreviation “Figure.” even at the beginning of a sentence. Do not abbreviate “Table.” Tables are numbered with numerals.

Figure axis labels are often a source of confusion. Use words rather than symbols. As an example, write the quantity “Magnetization,” or “Magnetization M,” not just “M.” Put units in parentheses. Do not label axes only with units. As in Figure 1, for example, write “Magnetization (A/m)” or “Magnetization (Am^-1),” not just “A/m.” Do not label axes with a ratio of quantities and units. For example, write “Temperature (K),” not “Temperature/K.”

Multipliers can be especially confusing. Write “Magnetization (kA/m)” or “Magnetization (10³ A/m).” Do not write “Magnetization (A/m) ´ 1000” because the reader would not know whether the top axis label in Figure 1 meant 16000 A/m or 0.016 A/m. Figure labels should be legible, approximately 8 to 12 point type.

Figure 1: Architecture of the Enhanced Fuzzy Resolution Mechanism using ANFIS

Table 1: Attributes of Cleveland dataset

2.2 References

Number citations consecutively in square brackets [1]. The sentence punctuation follows the brackets [2]. Multiple references [2], [3] are each numbered with separate brackets [1]–[3]. When citing a section in a book, please give the relevant page numbers [2]. In sentences, refer simply to the reference number, as in [3]. Do not use “Ref. [3]” or “reference [3]” except at the beginning of a sentence: “Reference [3] shows ... .” Number footnotes separately in superscripts (Insert | Footnote).Equations

Number equations consecutively with equation numbers in parentheses flush with the right margin, as in (1). First use the equation editor to create the equation. Then select the “Equation” markup style. Press the tab key and write the equation number in parentheses. To make your equations more compact, you may use the solidus ( / ), the exp function, or appropriate exponents. Use parentheses to avoid ambiguities in denominators. Punctuate equations when they are part of a sentence, as in

  (1)

Be sure that the symbols in your equation have been defined before the equation appears or immediately following. Italicize symbols (T might refer to temperature, but T is the unit tesla). Refer to “(1),” not “Eq. (1)” or “equation (1),” except at the beginning of a sentence: “Equation (1) is ... .”

2.4 Other Recommendations

Use one space after periods and colons. Hyphenate complex modifiers: “zero-field-cooled magnetization.” Avoid dangling participles, such as, “Using (1), the potential was calculated.” [It is not clear who or what used (1).] Write instead, “The potential was calculated by using (1),” or “Using (1), we calculated the potential.”

Use a zero before decimal points: “0.25,” not “.25.” Use “cm³,” not “cc.” Indicate sample dimensions as “0.1 cm ´ 0.2 cm,” not “0.1 ´ 0.2 cm².” The abbreviation for “seconds” is “s,” not “sec.” Do not mix complete spellings and abbreviations of units: use “Wb/m²” or “webers per square meter,” not “webers/m².” When expressing a range of values, write “7 to 9” or “7-9,” not “7~9.”

A parenthetical statement at the end of a sentence is punctuated outside of the closing parenthesis (like this). (A parenthetical sentence is punctuated within the parentheses.) In American English, periods and commas are within quotation marks, like “this period.” Other punctuation is “outside”! Avoid contractions; for example, write “do not” instead of “don’t.” The serial comma is preferred: “A, B, and C” instead of “A, B and C.”

If you wish, you may write in the first person singular or plural and use the active voice (“I observed that ...” or “We observed that ...” instead of “It was observed that ...”). Remember to check spelling. If your native language is not English, please get a native English-speaking colleague to proofread your paper.

3.  SOME COMMON MISTAKES

The word “data” is plural, not singular. The subscript for the permeability of vacuum µ₀ is zero, not a lowercase letter “o.” The term for residual magnetization is “remanence”; the adjective is “remanent”; do not write “remnance” or “remnant.” Use the word “micrometer” instead of “micron.” A graph within a graph is an “inset,” not an “insert.” The word “alternatively” is preferred to the word “alternately” (unless you really mean something that alternates). Use the word “whereas” instead of “while” (unless you are referring to simultaneous events). Do not use the word “essentially” to mean “approximately” or “effectively.” Do not use the word “issue” as a euphemism for “problem.” When compositions are not specified, separate chemical symbols by en-dashes; for example, “NiMn” indicates the intermetallic compound Ni_0.5Mn_0.5 whereas “Ni–Mn” indicates an alloy of some composition Ni_xMn_1-x.

Be aware of the different meanings of the homophones “affect” (usually a verb) and “effect” (usually a noun), “complement” and “compliment,” “discreet” and “discrete,” “principal” (e.g., “principal investigator”) and “principle” (e.g., “principle of measurement”). Do not confuse “imply” and “infer.”

Prefixes such as “non,” “sub,” “micro,” “multi,” and “"ultra” are not independent words; they should be joined to the words they modify, usually without a hyphen. There is no period after the “et” in the Latin abbreviation “et al.” (it is also italicized). The abbreviation “i.e.,” means “that is,” and the abbreviation “e.g.,” means “for example” (these abbreviations are not italicized).

An excellent style manual and source of information for science writers is [9].

4. EDITORIAL POLICY

The submitting author is responsible for obtaining agreement of all coauthors and any consent required from sponsors before submitting a paper. It is the obligation of the authors to cite relevant prior work.

5. CONCLUSION

A conclusion section is not required. Although a conclusion may review the main points of the paper, do not replicate the abstract as the conclusion. A conclusion might elaborate on the importance of the work or suggest applications and extensions.

APPENDIX

Appendixes, if needed, appear before the acknowledgment.

ACKNOWLEDGEMENT

The preferred spelling of the word “acknowledgment” in American English is without an “e” after the “g.” Use the singular heading even if you have many acknowledgments. Avoid expressions such as “One of us (S.B.A.) would like to thank ... .” Instead, write “F. A. Author thanks ... .” Sponsor and financial support acknowledgments are placed in the unnumbered footnote on the first page.

References

(Periodical style)

3. Lin, M. Wu, J. A. Bloom, I. J. Cox, and M. Miller. Rotation, scale, and translation resilient public watermarking for images, IEEE Trans. Image Process., vol. 10, no. 5, pp. 767-782, May 2001.

(Book style)

(Book style with paper title and editor)

1. The Spread Spectrum Concept, in Multiple Access, N. Abramson, Ed. Piscataway, NJ: IEEE Press, 1993, ch. 3, pp. 121-123.

(Published Conference Proceedings style)

2. .

 (Thesis or Dissertation style)
نگارش پروپوزال کارشناسی ارشد و دکتری - نگارش رساله دکتری - نگارش مقاله پژوهشی - نگارش مقاله ISI - نگارش مقاله مروری - نگارش مقاله کنفرانسی - نگارش پایان نامه کارشناسی ارشد - استخراج مقاله

he predictive values of two MRI and MRV neuroimaging tests in headache patients without neurologic symptoms

 Department of imaging, Milad Hospital,TEHRAN, IRAN

Abstract

Background and Purpose: This study conducted to evaluate the predictive values of two MRI and MRV diagnostic tests in headache patients with different non-specific neurologic symptoms such as blurred vision, nausea, and dizziness sings or all of them.

Materials and Methods: The research population consisted of peoples (n: 54, male; n: 176, female) who referred to three Tehran hospitals, Departments of Neurology, were assigned into 2 groups based on their clinical symptoms, including: HG: patient only suffered from headaches; HBNDG: patients suffered from headache accompanied with one blurred vision, or nausea, and or dizziness sings or all of them. Then, brain MRI and MRV tests were performed for all subjects. There was a poor agreement between two neuroimaging tests in both HG and HBNDG patients. MRI test had low sensitivity in HG patients, HBNDG patients and in all participants. So MRI was a highly specific test in two groups. 

Results: There was no significant difference between groups based on different clinical symptoms (P = 0.33) in age.  The female participants had significantly lower age in comparison with males (40.3 ± 0.97 vs. 45.5 ± 2.04, respectively, P = 0.005). MRV was a relatively sensitive test in all participants (≥ 50). Additionally, the specificity was moderate (nearly 64.5) in all groups.

Conclusions: This investigation shows MRV is more sensitive than MRI for recognition of brain abnormalities in patients with headaches accompanied by nausea, dizziness, and blurred vision. It was suggested that the combination of these clinical symptoms with headache increase the diagnostic values of the MRV test.

Keywords: MRI, MRV, neuroimaging, headache patients 

1. Introduction

Headaches are considered as most common neurological issues which everyone certainly has been experienced at least one time in her/and his life [1]. It has been showed that headaches include up to 30% of patients with neurologic symptoms [2]. Headache problems are categorized in term of clinical pattern and etiology into two primary and secondary groups. The primary headaches are the most common headaches and included 98% of headaches, although potentially affect the quality of life, which revealed that there is any abnormal findings in imaging results [1]. Whereas, secondary headaches are associated with a pathologic abnormality in the brain such as increased intracranial pressure, infection or arterial disorders, etc., with the possibility of life-threatening [3]. The most of headaches can be diagnosed and managed according to correct clinical taking and examination [4]. Sometimes, it may be confusing to diagnose common headache disorders due to many patients cannot present some accurate symptoms from their headaches to clinicians. So, practitioners prefer to perform more diagnostic investigations to justify that headaches disorders are not a severe disease [5].

There are different diagnostic neuroimaging tests can perform to manifest brain abnormalities in a patient with headaches. Neuroimaging with magnetic resonance imaging (MRI), magnetic resonance venography (MRV), computed tomography (CT) and CT venography are the most useful investigations for determining neurologic disorders [6]. The diagnostic values of these neuroimaging tests are not similar in different abnormalities. It was shown that abnormal neurological symptoms can increase to yield a significant positive neuroimaging finding [7].

Moreover, neuroimaging modalities have some risks for patients, as well as very expensive. Sometimes, it is not needed to perform different researches for diagnosing common headaches and an accurate clinical examination can help to make an proper and economic decision before more investigations work up [8].

Although there are different findings according to diagnostic values of various neuroimaging tests, there are inconsistence data regarding the importance of clinical features for selecting a sensitive and specific neuroimaging test in headaches [7].

Therefore, we performed two different neuroimaging tests (MRI vs. MRV) in patients only suffered from headaches and patients suffered from headaches accompanied by different clinical symptoms such as blurred vision, nausea, and dizziness sings or all of them. To evaluate the predictive values of two MRI and MRV diagnostic tests in headache patients without specific clinical symptoms of neurologic disorders. (Fig. 1). We hope to make a correct and proper clinical decision, decrease unnecessary investigations, and accelerate to the best treatment in patients with idiopathic headaches.

Figure 1. It was shown normal brain (a) and the thrombosis positive cord sign in the right transverse sinus (b) in MRV.

2. Materials and Methods

2.1. Study population

A prospective, observational study conducted among peoples (n: 54, male; n: 174, female) who referred to three Tehran hospitals, Departments of Neurology, were enrolled between August 2015 and December 2018. The inclusion criteria included age over 9 years[f1] [f2] , and with a headache complication (exception non-migraine headache). The study was confirmed by the local ethics committee of the hospital, informed consent was reached from the patients. These hospitals are longstanding and well-known hospitals specialized for neurology and neurosurgery.

Patients either show themselves, age, sexuality, duration of headache, the other clinical symptoms excepted of headaches such as history of seizures, concomitant illnesses, and existing pregnancy were all recorded. The patients were assigned into 2 groups according to their clinical symptoms, including: HG: patient only suffered from headaches; HBNDG: patients suffered from headache accompanied with one blurred vision, or nausea, and or dizziness sings or all of them.

Then, these participants were referred to assessed brain imagines including brain magnetic resonance imaging (MRI), and brain magnetic resonance venography (MRV). MRI and MRV were performed using 1.5 Tesla GE Simens scanner.

According to brain imagines, main diagnoses were assigned into two following groups: positive brain abnormalities (P) or and negative cerebrovascular abnormalities (N).

2.2. Statistical analysis

The demographic characteristics of participants (sexuality, age), clinical symptoms and imagines findings were collected into databases created in Microsoft Excel 2016 Microsoft. Then, all databases were imported into SAS for data analyzing. Analyses were performed with SAS version 9.1 (SAS Institute, Cary, NC, USA). Data of age was analyzed with one way-ANOVA test (a GLM PROC in SAS). The fixed effect was group based on gender and clinical symptoms. Then, the Cohen’s kappa coefficients for pairs of diagnostic tests were computed with the FREQ PROC. Due to independent diagnostic tests were imperfect, sensitivity, and specificity of individual tests was estimated using LCA PROC. Statistical significance was determined at P< 0.05.

3. Results

According to Table 1, the age ranged from 9 years to 76 years and the mean age was shown for two men and women as well as different groups of clinical symptoms. Males included 23.68 % of the patients (n= 54) and females included 76.5 % of the subjects (n= 176). There was no significant difference in age between groups based on different clinical symptoms (P = 0.33). The female participants had significantly lower age in comparison with males (40.3 ± 0.97 vs. 45.5 ± 2.04, respectively, P = 0.005).

Cohen’s kappa coefficient is a statistic that evaluated the agreement between diagnostic tests. In this study, two neuroimaging tests were performed in patients with only headache and headache accompany other symptoms. The Cohen’s kappa coefficients were evaluated the correlation between two tests in two groups. According to Table 2, there was a poor agreement between two neuroimaging tests in both HG and HBNDG patients.

The sensitivity and specificity of two neuroimaging diagnostic tests without any gold standard test were estimated by Latent Class Analysis (LCA) (Table 3). LCA can use to estimate sensitivity and specificity of independent tests when there is not an imperfect diagnostic test. MRI test had low sensitivity in patients with the only headache, headache accompanied by other general symptoms and in all participants. Whereas MRI was a highly specific test in two patient groups with only headache and groups with headache accompany other general symptoms.

MRV was a relatively sensitive test in all participants (≥ 50). Additionally, the specificity was moderate (nearly 64.5) in all groups.

4. Discussion

Usually, in neurologic lesions the clinical findings are revealed according to the mechanism of neurological dysfunction. These features make suggestions that should be accepted by a proper neuroimaging investigation and finally make an accurate diagnose [9]. For example, in cerebral venous thrombosis (CVT), patients clinically show diffuse headache and some focal neurologic symptoms (papilledema). These clinical symptoms pay attention to intracranial hypertension causes [10]. So, practitioners attempted to prevent any delay for treatment by imaging with the most reliable and rapidest modality.  Additionally, durations of presenting clinical symptoms may help for selecting an appropriate imaging test. So the imaging findings may be differed due to the time of imaging from the occurrence of brain lesions [11, 12].

However, in this work we confronted with two groups of patients that complicated from isolated headache, and or headache accompanied by several non-neurologic signs (nausea, dizziness, and blurred vision). These features clinically made a diagnostic challenge. Because of this we did not have any gold standard examination tests. There is any agreement between two MRI and MRV tests (Cohens kappa coefficient values < 0.1) confirmed the aforementioned statement.

Then, it is computed the LCA approach to compare diagnostic values of two tests in both patient groups.

According to LCA findings, MRV was a relatively sensitive neuroimaging test that can be performed to make a sufficient clinical decision. These findings were expectable due to MRV and MRI which have various operator characteristics. The greater MRV sensitivity might have been due to it can make an intravenous contrast dye to detect vascular disorders such as thrombosis. It also diagnoses deep vein thrombosis with high sensitivity in the first days of thrombosis formation [13].

Furthermore, it was revealed that the contrast-enhanced 3D T1-weighted gradient-echo MRI is the most accuracy for the discovering of dural venous sinus and/or cortical venous thrombosis in comparison with conventional MRI and MRV imaging tests [14].

Based on LCA results, MRI had higher specificity for patients with headache without any neurologic symptoms. MRV was moderately specific in this study. According to Lomont et al. (2003) presenting paralysis, reduced conscious level and papilloedema with headache predicted brain abnormalities in neuroimaging examination [7]

We have observed that 76.5 % of participants were women suffered from a headache. This finding is consistent with the findings of previous studies. They have been showed different subtypes of primary and secondary headaches have more incidences in women than men [15, 16].

Moreover, 1.14% of women (n=2) were pregnant and presented headache related to pregnancy. Although, their MRI test was negative, significant brain abnormalities were observed on MRV examinations. The sampling population was plausible affected this result. However, physiologic alterations initiated by pregnancy promote the risk of CVT, pituitary and dissection apoplexy [17]. Therefore, unique considerations regarding the differential diagnosis, imaging options, and medical management are important for evaluating the pregnant patient with headache.

Although, men with headache were significantly older than women (45.5 vs. 40.3 years), we found no data regarding the significant difference of age between sexes. This finding likely is related to sampling population that was not randomized, and then it cannot be generalized in the headache population.

Headaches are the most common neurological issues categorized into two primary and secondary groups based on etiology and clinical symptoms [1]. In the present study, nearly 64.5 % of participants complicated from mild to severe headache without other clinical sings (HG). The neuroimaging tests (MRI and MRV) were obtained to make an accurate clinical decision. The imaging results showed that only 93.9 % of HG was negative in MRI test, whereas, 35.4% of HG discovered positive results on MRV investigation.

In the present study, 6.14 % of participants presented only dizziness, while, 7.02 % of patients presented the combination of nausea and dizziness related to headache. It was shown in the US, near 130 000 to 220 000 patients with stroke referring to the emergency department with dizziness related headache annually [18]. Additionally, dizziness is the symptom most tightly linked to missed stroke [18, 19]. However, it was estimated performing neuroimaging for every patient presenting dizziness related headache in the US, would be cost >$1 billion annually [20]. In a wide range of abnormalities were occurred, the combination of nausea and dizziness such as TBI, aneurysm, and cerebrovascular disorders such as venous thrombosis were similar in both groups. Although there is a rule to obtain an MRI investigation in acute dizziness, the risk of false-negative findings was cleared in the first 48 hours of cerebrovascular disorders by MRI.

Blurred vision is also a non-neurologic symptom of brain pathology that presents with headaches in some cerebrovascular disorders, brain tumor [21], migraine headaches [22], as well as brain aneurysm [23]. According to the research findings, 6.6 % of participants had only blurred vision related to headache and 7.02 % of them presented blurred symptoms accompany nausea or dizziness (HBNDG). There were not observed positive MRI results in HBNDG patients. Also there were positive finding on MRV investigations in HBNDG (31.25 %)

5. Conclusion

The findings of the research showed that MRV is more sensitive than MRI neuroimaging test for recognition of brain abnormalities in patients with headaches and or headache accompanied by nausea, dizziness, and blurred vision. According to findings of research it was suggested that the combination of these clinical symptoms with headache increase the diagnostic values of MRV test. The appearance of neurological symptoms might increase to yield a positive neuroimaging finding and increased predictive values of neuroimaging tests.

6. Declarations

• Ethics approval and consent to participate: Not applicable
• Consent for publication: Not applicable
• Availability of data and material: Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
• Competing interests: Not applicable
• Funding: Not applicable
• Authors' contributions: Not applicable
• Acknowledgements: Not applicable

References

1.Ahmed, F., Headache disorders: differentiating and managing the common subtypes. British journal of pain, 2012. 6(3): p. 124-132.

2.Yoon, M., et al., Prevalence of primary headaches in Germany: results of the German Headache Consortium Study. The journal of headache and pain, 2012. 13(3): p. 215.

3.Do, T.P., et al., Red and orange flags for secondary headaches in clinical practice: SNNOOP10 list. Neurology, 2019. 92(3): p. 134-144.

4.Lee, V.M.E., et al., The adult patient with headache. Singapore medical journal, 2018. 59(8): p. 399.

5.Holle, D. and M. Obermann, The role of neuroimaging in the diagnosis of headache disorders. Therapeutic advances in neurological disorders, 2013. 6(6): p. 369-374.

6.Hatami, H., et al., Evaluation of Diagnostic Values in NCCT and MRI of the Patients With Cerebral Venous or Sinus Thrombosis in Loghman Hakim Hospital in Tehran 2014-2018. International Clinical Neuroscience Journal, 2019. 6(1): p. 17-21.

7.Lamont, A., N. Alias, and M. Win, Red flags in patients presenting with headache: clinical indications for neuroimaging. The British journal of radiology, 2003. 76(908): p. 532-535.

8.Micieli, A. and W. Kingston, An Approach to Identifying Headache Patients That Require Neuroimaging. Frontiers in Public Health, 2019. 7: p. 52.

9.Saposnik, G., et al., Diagnosis and management of cerebral venous thrombosis: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke, 2011. 42(4): p. 1158-1192.

10.Appenzeller, S., et al., Cerebral venous thrombosis: influence of risk factors and imaging findings on prognosis. Clinical neurology and neurosurgery, 2005. 107(5): p. 371-378.

11.Damak, M., et al., Isolated lateral sinus thrombosis: a series of 62 patients. Stroke, 2009. 40(2): p. 476-481.

12.Wasay, M. and M. Azeemuddin, Neuroimaging of cerebral venous thrombosis. Journal of Neuroimaging, 2005. 15(2): p. 118-128.

13.Cantwell, C.P., et al., MR Venography with true fast imaging with steady-state precession for suspected Lowerlimb deep vein thrombosis. Journal of vascular and interventional radiology, 2006. 17(11): p. 1763-1770.

14.Sari, S., et al., MRI diagnosis of dural sinus—Cortical venous thrombosis: Immediate post-contrast 3D GRE T1-weighted imaging versus unenhanced MR venography and conventional MR sequences. Clinical neurology and neurosurgery, 2015. 134: p. 44-54.

15.Zhang, Y., et al., Prevalence of primary headache disorders in a population aged 60 years and older in a rural area of Northern China. The journal of headache and pain, 2016. 17(1): p. 83.

16.Felício, A.C., et al., Epidemiology of primary and secondary headaches in a Brazilian tertiary-care center. Arquivos de neuro-psiquiatria, 2006. 64(1): p. 41-44.

17.Schoen, J.C., R.L. Campbell, and A.T. Sadosty, Headache in pregnancy: an approach to emergency department evaluation and management. Western Journal of Emergency Medicine, 2015. 16(2): p. 291.

18.Saber Tehrani, A.S., et al., Rising annual costs of dizziness presentations to US emergency departments. Academic Emergency Medicine, 2013. 20(7): p. 689-696.

19.Tarnutzer, A.A., et al., ED misdiagnosis of cerebrovascular events in the era of modern neuroimaging: a meta-analysis. Neurology, 2017. 88(15): p. 1468-1477.

20.Saber Tehrani, A.S., et al., Diagnosing stroke in acute dizziness and vertigo: pitfalls and pearls. Stroke, 2018. 49(3): p. 788-795.

21.Muthukumar, N., Cerebral venous sinus thrombosis and thrombophilia presenting as pseudo-tumour syndrome following mild head injury. Journal of Clinical Neuroscience, 2004. 11(8): p. 924-927.

22.Friedman, D.I. and R.W. Evans, Are blurred vision and short-duration visual phenomena migraine aura symptoms. Headache, 2017. 57(4): p. 643-647.

23.de Aguiar, G.B., et al., Spontaneous thrombosis of giant intracranial aneurysm and posterior cerebral artery followed by also spontaneous recanalization. Surgical neurology international, 2016. 7.