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系統識別號 U0026-0105201514424400
論文名稱(中文) 手指滑車與扳機指之形態影像學與生物力學研究
論文名稱(英文) Morphological Imaging and Biomechanics of Pulley and Trigger Finger
校院名稱 成功大學
系所名稱(中) 生物醫學工程學系
系所名稱(英) Department of BioMedical Engineering
學年度 103
學期 2
出版年 104
研究生(中文) 楊岱樺
研究生(英文) Tai-Hua Yang
學號 P88971204
學位類別 博士
語文別 英文
論文頁數 79頁
口試委員 指導教授-蘇芳慶
口試委員-安介南
召集委員-孫永年
口試委員-周一鳴
口試委員-郭藍遠
口試委員-郭立杰
口試委員-林槐庭
中文關鍵字 屈指淺肌  屈指深肌  協同化  力臂  肌腱滑移  貢獻度  嚴重度相關性  電腦輔助的  影像分析  扳機指  滑車,高頻率超音波  超音波影像 
英文關鍵字 FDS  FDP  synchronize  moment arm  tendon excursion  contribution  Severity correlation  Computer-aided  Image analysis  Trigger finger  Pulley  High frequency ultrasound  Sonographic image 
學科別分類
中文摘要 現代化、科技化的環境突顯了手部功能的重要性。板機指是手部的常見疾病之一,雖然在部分診斷和治療已經非常成熟,但是在某些問題上仍需要解決,以改善促進對該疾病可能的最佳治療。
其一是深入了解對於手指曲屈扮演重要角色的屈指淺肌肌腱和屈指深肌肌腱在健全的滑車系統下它們的關係。在本論文第一部分研究(第二章節)中,我們透過建立一個封閉系統模型來探討手指肌腱與滑車間的關係。十具手部大體分別裝設在特製的實驗框架上,屈指淺肌肌腱和屈指深肌肌腱透過一個載有力量傳感器的光滑機械滑車連結成一個活動迴路。我們量測在分別的單一指關節活動與自由的全指關節從伸直的休息狀態到最大曲屈狀態下之關節活動角度、肌腱的滑移程度及其相對應的作用力,並轉換計算屈指肌腱相對於各個關節的最短旋轉力臂。在分別的單一近端指關節活動上,我們發現屈指深肌肌腱的貢獻度大於屈指淺肌肌腱。但是在分別的單一掌指關節活動上,我們發現屈指深肌肌腱的貢獻度小於屈指淺肌肌腱。在自由的全指關節活動上,屈指深肌肌腱比屈指淺肌肌腱扮演更為重要的角色。本研究結果證實屈指深肌肌腱和屈指淺肌肌腱在手指屈曲過程中會因應不同角度之手指活動,而分別產生不同比例的肌腱滑移程度,這些發現可提供將來手部疾患在手術和復健介入擬訂上之依據,並為手部力學模型開發上提供重要基礎資訊。
另一個議題在探討關於扳機指病理分級與臨床嚴重度分級的相關性。目前為止, 扳機指的治療主要端賴臨床醫師對病人的症狀與功能性的嚴重程度評估,但是這當中仍然缺乏病理證據支持臨床的評估標準。在我們的第二部分研究(第三章節)中,主要在建立臨床嚴重度分級與扳機指組織病理顯微影像之間的相關性。我們對隨機抽樣的組織檢體切片進行病理與臨床嚴重度分類。此外,我們利用自動化影像分析系統針對所選取的組織檢體切片進行異常組織區域面積比和異常細胞核數目比的自動化分析。實驗發現病理分級和定量圖像參數有顯著的相關性,而且臨床分級和定量圖像參數也有顯著的相關性,此外,透過該評估, 病理分級與臨床嚴重度分級也有良好的一致性。因此該實驗選用的臨床分類標準與該組織的病理變化有高度相關,並提供明確的證據以支持臨床醫師在治療上的策略。
最後一個議題是關於探討在超音波影像上正確的辨識正常A1滑車位置,對於扳機指正確的判別與經皮解離手術的執行是很重要的。在我們的第三部分研究(第四章節)的目的是辨別超音波影像中A1滑車的正確位置並且透過兩種不同頻率的超音波影像呈像與電子測徑器所量測的厚度做比較。本實驗室檢測了十具新鮮冷凍的手部大體,其中我們隨機選取了一具大體的無名指進行分層解剖,並在屈指肌腱和A1滑車之間植入為數不等的細導銷,將組織復位後使用臨床的高頻超音波進行測試並與相關的滑車解剖結構位置進行對比。當確定滑車在超音波影像上的位置之後,我們針對每具手部大體的中指,使用臨床的高頻超音波進行滑車厚度的量測。然後將其滑車組織一一切除下來,使用電子測徑器量測實際的厚度,也另外使用特製化的超高頻超音波儀器分別量測厚度。本實驗發現細導銷所在的位置是位在介於高回聲特性的滑車和屈指肌腱中間的滑液空間,藉此我們界定了滑車的範圍。此外我們發現使用臨床高頻超音波量測的A1滑車厚度明顯低於使用電子測徑器與特製化的超高頻超音波儀器量測的厚度。因此這些新測量技術和對超音波圖像的新見解,可以準確判斷滑車的界限範圍。
以上探討了關於正常與病態的A1滑車問題將有助於改進扳機指的診斷與治療,無論在工作或是日常生活活動上,也將改善許多人的手部操作功能與生活品質。
英文摘要 Technology has increased the value of hand function and the occurrence of hand conditions, of which trigger finger is one of the most common. Yet important questions about diagnosis and treatment remain.
One question is the relationship between the flexor digitorum superficialis (FDS) and flexor digitorum profundus (FDP). In our first study (Chapter 2), we investigated this relationship by creating a closed-system model. Ten human cadaveric hands were mounted individually on our custom frame with the third finger’s flexor tendons looped through a mechanical pulley connected to a force transducer. Individual joint motions and free joint movement were tested from rest to maximal flexion. Joint range of motion, tendon excursion and acquired loading force were recorded and the moment arm calculated. The FDP contributed more than the FDS in individual proximal interphalangeal joint (PIP) motion but less in individual metacarpophalangeal joint (MCP) motion. The FDP also played a greater role in free joint movement. The findings about differences in finger performance and excursion amounts between the FDS and FDP provide important insights into hand modeling and treatment design.
Another question involves the correlation between pathological grading and clinical classification. Treatment has depended on clinical severity evaluation, but supporting pathological evidence is unestablished. In our second study (Chapter 3), we investigated the correlation between clinical classification and pathological changes using tissue abnormality in microscopic images. Images of tissue samples were randomly selected and graded. A custom image analysis system was used to derive the size ratio of the abnormal tissue region and the number ratio of the abnormal nuclei. Significant correlations were found between these parameters and pathological grading and between the parameters and clinical severity classification, and good consistency was found between pathological and clinical classification. These correlations can support treatment strategy development, and this system can improve severity evaluation.
The final question relates to identifying the A1 pulley sonographically for proper percutaneous release. The third study’s purpose (Chapter 4) was to identify the normal pulley’s exact location and thickness in sonographic images by comparing measurements from a clinical high-frequency ultrasound system (CHUS), a customized high-frequency ultrasound imaging research system (HURS) and a digital caliper. Ten human cadaveric hands were used. We inserted guide pins between the flexor tendons and A1 pulley of a randomly chosen and dissected ring finger, recovered the finger and scanned it with the CHUS, using anatomic structures for reference. After identifying the pulley on the image, we measured each long finger’s thickness using the CHUS. Then we excised this pulley and measured its thickness with a digital caliper and the HURS. The guide pins revealed the thin hypoechoic layer to be the synovial fluid space between the hyperechoic pulley and flexor tendons. We also defined the pulley’s boundaries. The significantly lower thickness measurement from the CHUS compared to the digital caliper and HURS indicated the HURS’s greater accuracy. These new data can help the precise identification of the pulley.
Answering these questions should improve the diagnosis and treatment of this widespread hand disease, thus improving many lives.
論文目次 中文摘要 I
ABSTRACT III
LIST OF TABLES VII
LIST OF FIGURES VIII
CHAPTER 1 GENERAL INTRODUCTION 1
1.1 Research Background 1
1.1.1 Pulley and flexor tendon anatomy 1
1.1.2 Pulley system biomechanics 3
1.1.3 Occurrence of trigger finger 3
1.1.4 Classification of trigger finger 4
1.1.5 Histopathology of trigger finger 7
1.1.6 Treatment of trigger finger 8
1.1.7 Use of Sonography 9
1.2 Motivations 11
1.2.1 The relative contributions of the FDS and FDP in a normal pulley system 11
1.2.2 Correlation between pathological grading and clinical classification of trigger finger 11
1.2.3 Identification of the A1 pulley in sonographic images 12
1.3 Specific Aims 13
1.3.1 Establishing an accurate correlation between the FDS and FDP 13
1.3.2 Correlating pathological grading and clinical classification through automatic quantitative image analysis 13
1.3.3 Determining the location and thickness of the A1 pulley in sonographic images 13
CHAPTER 2 A NOVEL CLOSED-SYSTEM MODEL TO ASSESS THE CONTRIBUTIONS OF FLEXOR TENDONS IN FINGER JOINT MOTION 15
2.1 Introduction 15
2.2 Materials and Methods 17
2.2.1 Specimen preparation 17
2.2.2 Specimen mounting 17
2.2.3 Data collection 19
2.2.4 Data analysis 20
2.3 Results 21
2.4 Discussion 24
CHAPTER 3 CLINICAL AND PATHOLOGICAL CORRELATES OF SEVERITY CLASSIFICATIONS IN TRIGGER FINGERS BASED ON COMPUTER-AIDED IMAGE ANALYSIS 30
3.1 Introduction 30
3.2 Materials and methods 32
3.2.1 Materials 32
3.2.2 Methods 35
3.2.3 Statistics 38
3.3 Results 39
3.4 Discussion 42
CHAPTER 4 IDENTIFICATION OF THE POSITION AND THICKNESS OF THE FIRST ANNULAR PULLEY IN SONOGRAPHIC IMAGES 46
4.1 Introduction 46
4.2 Materials and methods 48
4.2.1 Specimen preparation 48
4.2.2 Experimental system 48
4.2.3 Experimental procedure 50
4.2.4 Statistical conditions 52
4.3 Results 52
4.4 Discussion 57
CHAPTER 5 SUMMARY AND FUTURE WORK 63
5.1 Summary 63
5.1.1 A novel closed-system model to assess the contributions of flexor tendons in finger joint motion 63
5.1.2 Clinical and pathological correlates of severity classifications in trigger finger based on computer-aided image analysis 63
5.1.3 Identification of the position and thickness of the A1 pulley in sonographic images 64
5.2 Future Work 65
5.2.1 Flexor tendon contribution model 65
5.2.2 Correlating clinical and pathological severity classifications 65
5.2.3 Identifying the A1 pulley in sonographic images 65
References 67
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