scholarly journals Unraveling a rare cause of spinal stenosis: Coexistent AL and ATTR amyloidosis involving the ligamentum flavum

2022 ◽  
Vol 13 ◽  
pp. 12
Author(s):  
Amandeep Godara ◽  
Andy Y. Wang ◽  
Knarik Arkun ◽  
Teresa Fogaren ◽  
Adnan S. Qamar ◽  
...  
Keyword(s):  
Spinal Stenosis ◽  
Protein Misfolding ◽  
Ligamentum Flavum ◽  
Treatment Decision ◽  
Amyloid Deposition ◽  
Decompression Surgery ◽  
Treatment Decision Making ◽  
Amyloid Deposits ◽  
Different Types ◽  
A Site

Background: Amyloidosis is a protein misfolding disorder that leads to the deposition of beta-pleated sheets of a fibrillar derivative of various protein precursors. Identification of the type of precursor protein is integral in treatment decision-making. The presence of two different types of amyloid in the same patient is unusually rare, and there are no previous reports of two different types of amyloid deposition in the ligamentum flavum (LF) in the same patient. Case Description: Here, we describe two patients with spinal stenosis who underwent laminectomies and were found to have AL and ATTR amyloid deposits in the LF. Conclusion: As the spine is becoming recognized as a site for ATTRwt amyloid deposition, patients undergoing spinal decompression surgery may potentially benefit from evaluation for amyloidosis in the LF.

scholarly journals Machine learning quantification of amyloid deposits in histological images of ligamentum flavum

2021 ◽  
Author(s):  
Andy Y. Wang ◽  
Vaishnavi Sharma ◽  
Harleen Saini ◽  
Joseph N. Tingen ◽  
Alexandra Flores ◽  
...  
Keyword(s):  
Machine Learning ◽  
Spinal Stenosis ◽  
Ligamentum Flavum ◽  
Amyloid Deposition ◽  
Future Research ◽  
Manual Segmentation ◽  
Training Set ◽  
Transthyretin Amyloidosis ◽  
Amyloid Deposits ◽  
Lumbar Spinal

ABSTRACTBackgroundWild-type transthyretin amyloidosis (ATTRwt) is an underdiagnosed and potentially fatal disease. Interestingly, ATTRwt deposits have been found to deposit in the ligamentum flavum (LF) of patients with lumbar spinal stenosis prior to the development of systemic and cardiac amyloidosis. In order to study this phenomenon and its possible relationship with LF thickening and systemic amyloidosis, a precise method of quantifying amyloid deposits in histological slides of LF is critical. However, such a method is currently unavailable. Here, we present a machine learning quantification method with Trainable Weka Segmentation (TWS) to assess amyloid deposition in histological slides of LF.MethodsImages of ligamentum flavum specimens stained with Congo red are obtained from spinal stenosis patients undergoing laminectomies and confirmed to be positive for ATTRwt. Amyloid deposits in these specimens are classified and quantified by TWS through training the algorithm via user-directed annotations on images of LF. TWS can also be automated through exposure to a set of training images with user-directed annotations, and then application to a set of new images without additional annotations. Additional methods of color thresholding and manual segmentation are also used on these images for comparison to TWS.ResultsWe develop the use of TWS in images of LF and demonstrate its potential for automated quantification. TWS is strongly correlated with manual segmentation in the training set of images with user-directed annotations (R = 0.98; p = 0.0033) as well as in the application set of images where TWS was automated (R = 0.94; p = 0.016). Color thresholding was weakly correlated with manual segmentation in the training set of images (R = 0.78; p = 0.12) and in the application set of images (R = 0.65; p = 0.23).ConclusionTWS machine learning closely correlates with the gold standard comparator of manual segmentation and outperforms the color thresholding method. This novel machine learning method to quantify amyloid deposition in histological slides of ligamentum flavum is a precise, objective, accessible, high throughput, and powerful tool that will hopefully pave the way towards future research and clinical applications.

scholarly journals MRI-Based Classification Scheme for Degenerative Cervical Spinal Stenosis (DCSS Classification)

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Leimert M ◽  
◽  
Hamann I ◽  
Bostelmann R ◽  
von Sachsen S ◽  
...  
Keyword(s):  
Spinal Stenosis ◽  
Interobserver Reliability ◽  
Treatment Decision ◽  
Treatment Decision Making ◽  
Main Class ◽  
Mri Scans ◽  
Cervical Spinal Stenosis ◽  
Magnetic Resonance Imaging Mri ◽  
Representative Image ◽  
Low K

Background: The severity of Degenerative Cervical Spinal Stenosis (DCSS) is currently assessed by determining the sagittal diameter of the spinal canal, the degree of narrowing, and the level of stenosis using magnetic resonance imaging (MRI). The aim of our study was to develop and evaluate an optimized, MRI-based classification of DCSS to support treatment decision-making. Methods: We analyzed preoperative MRI scans of 75 patients to determine key morphological features of DCSS. Based on the features found, a classification was proposed and tested on ten representative image sets by 53 neurosurgeons to determine practicability and inter-observer reliability. Results: DCSS extended over one (13 and 17 % of pat.), two (23 and 31 % of pat.) or three (39 and 52 % of pat.). Thickening of the ligaments was observed in 71%, scoliosis in 3% and grade I spondylolisthesis in 11% of the patients. The DCSS classification has three main Types (A, B, C), which differ in the extent of the stenoses and thickening of the ligaments. Each main class has 2-3 subtypes depending on the position of the stenosis (lateral/medial) and the number of stenotic segments. An additional suffix indicates the presence of concomitant pathology (spondylolisthesis, scoliosis). 26 (49 %) neurosurgeons rated the classification as useful. For the main classes, interobserver reliability was fair (k=0.23). For subtype and concomitant pathology, interobserver reliability was low (k=0.14). Conclusions: In the study a new classification system for degenerative spinal stenoses was developed, which combines anatomical and clinical defect characteristics. Deviations in the classification result from a strict subdivision, so that adjustments are necessary.

Patient Involvement in Treatment Decision Making Can Help or Hinder Placebo Analgesia

2014 ◽  
Vol 222 (3) ◽  
pp. 165-170 ◽  
Author(s):  
Andrew L. Geers ◽  
Jason P. Rose ◽  
Stephanie L. Fowler ◽  
Jill A. Brown
Keyword(s):  
Patient Involvement ◽  
Cold Water ◽  
Prior Experience ◽  
Water Immersion ◽  
Treatment Decision ◽  
Cold Water Immersion ◽  
Not Given ◽  
Placebo Analgesia ◽  
Treatment Decision Making ◽  
Immersion Experience

Experiments have found that choosing between placebo analgesics can reduce pain more than being assigned a placebo analgesic. Because earlier research has shown prior experience moderates choice effects in other contexts, we tested whether prior experience with a pain stimulus moderates this placebo-choice association. Before a cold water pain task, participants were either told that an inert cream would reduce their pain or they were not told this information. Additionally, participants chose between one of two inert creams for the task or they were not given choice. Importantly, we also measured prior experience with cold water immersion. Individuals with prior cold water immersion experience tended to display greater placebo analgesia when given choice, whereas participants without this experience tended to display greater placebo analgesia without choice. Prior stimulus experience appears to moderate the effect of choice on placebo analgesia.

Patients’ practices for taking the initiative in decision-making in outpatient psychiatric consultations

2017 ◽  
Vol 13 (2) ◽  
pp. 169-184 ◽  
Author(s):  
Shuya Kushida ◽  
Takeshi Hiramoto ◽  
Yuriko Yamakawa
Keyword(s):  
Decision Making ◽  
Conversation Analysis ◽  
Treatment Decision ◽  
Close Inspection ◽  
Important Resource ◽  
Treatment Decision Making ◽  
The Way

In spite of increasing advocacy for patients’ participation in psychiatric decision-making, there has been little research on how patients actually participate in decision-making in psychiatric consultations. This study explores how patients take the initiative in decision-making over treatment in outpatient psychiatric consultations in Japan. Using the methodology of conversation analysis, we analyze 85 video-recorded ongoing consultations and find that patients select between two practices for taking the initiative in decision-making: making explicit requests for a treatment and displaying interest in a treatment without explicitly requesting it. A close inspection of transcribed interaction reveals that patients make explicit requests under the circumstances where they believe the candidate treatment is appropriate for their condition, whereas they merely display interest in a treatment when they are not certain about its appropriateness. By fitting practices to take the initiative in decision-making with the way they describe their current condition, patients are optimally managing their desire for particular treatments and the validity of their initiative actions. In conclusion, we argue that the orderly use of the two practices is one important resource for patients’ participation in treatment decision-making.

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