Pathology cases — cardiac amyloid

This is a case of a young middle-aged woman with a history of drug use found dead at home with drug paraphenalia nearby.  At autopsy, she had high levels of both methamphetamine and fentanyl.  However, on anatomic evaluation, she had an enlarged and dilated heart (620 g).  That isn’t all that uncommon in my jurisdiction, since many intravenous drug users have endocarditis/valvular disease with resulting functional impairment.  However, in this case, the valves were a little thickened, but there were no vegetations.  Instead, the heart was rock hard to the touch.  It felt as if it had already been fixed in formalin.  On histologic examination, there was a lot of interstitial fibrosis, some of which had that amorphous hyaline look you see in amyloid.  So, I got a Congo red, and sure enough, it had the characteristic “green apple” birefringence.

Here’s an H&E section of the interventricular septum at the septal base, with a portion of the atrioventricular node (click on the image to see the 7Kx4K version):

H&E atrioventricular nodal region
H&E section of septal base near atrioventricular node

As an aside, I recognize the nonuniformity of the background here, but it’s hard to correct for in this instance.  For those of you who pay attention to this stuff, I cannot just take a brightfield image and divide it out.  This is actually a composite (panorama) stitched together from 42 low power shots.  The software I use is great (Hugin is the name), but it does interpolation of brightness as part of the stitching process.  Thus, the background is not only nonuniform, but very nonlinear.  I tried the simple approach of making a gradient from the brightest background to the lightest and dividing that out, but it looked even worse. The ImageJ/Fij background subtraction didn’t work all that well, either. I’m working on some code to do it in an adaptive manner, making local estimations, but I haven’t finished it yet.  If it works, I’ll post it.  If you download it, you can dry different background subtraction methods.

In any case, you can see there’s a little fibrosis there.  Here’s the polarized Congo Red (once again, click on the image to see the 7Kx4K version):

Congo Red atiorventricular node
Congo Red stain of atrioventricular nodal region with polarized light

As another aside, one of my colleagues here noted that everything seems brighter than what he sees in the microscope.  He’s right.  It’s a bit of a long exposure.  Looking directly through the microscope, for instance, the background is black.

Here’s a more random section of myocardium, just to show it’s not just a cardiac skeleton thing:

Left ventricle H&E
Left ventricle H&E
Left ventricle congo red
Left ventricle congo red

Secondary amyloidosis, particularly of the kidney and skin, is associated with intravenous drug use.  I’m not aware of literature that describes cardiac amyloidosis as a consequence of it, however.

As always, free for use in lecture, or teaching, with or without attribution (though attribution is appreciated).  If you put these in a publication, please contact me.  Higher resolution images with lossless compression are available on request until I lose them, if you need them for a lecture or such.  Email me if you want me to send them to you.

4 thoughts on “Pathology cases — cardiac amyloid”

  1. Hi Billo,
    Thanks for all you for forensic pathology!

    I had a case when I was a first year resident, a 32 year old policeman, with no drug use history collapsed at home. For some reason, that I don’t remember now (time flies!) he was submitted for a hospital autopsy, so I got to work him up in a way that I wouldn’t work up a forensic case (electron microscopy, serum free light chain assay, kappa/lambda bone marrow ISH – the whole 9 yards!). He had a clonal lambda population. Very interesting.

    1. Yeah, I wish we forensic pathologists were funded to do those kinds of deep clinicopathologic investigations. One of the things I noticed early on in my career was that we often saw natural disease manifestations that a lot of clinicians don’t see. People who die of disease today often don’t look like the classical descriptions of the disease because it’s been so modified by therapy and intervention. Some years ago, I had a case of a woman who died mysteriously at home. It turned out she had breast cancer that must have been around for a year, but she had never gone to the doctor. It looked like something out of a 19th century textbook.

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