JP4454212B2 - Image-related data processing method - Google Patents

Description

【００８０】
一過性脳虚血発作(ＴＩＡ)又は可逆性脳虚血性神経障害(ＲＩＮＤ)を解析対象とし、明らかな梗塞巣を有する者は除外したが小窩状態（ｌａｃｕｎａ）は解析対象とした。１０名（女性１名、男性９名、年齢範囲５１〜７０歳）に、局所性の一側性狭窄が認められた（一側性狭窄群）。残る３名（女性１名、男性２名、年齢範囲６３〜７０歳）には両側で狭窄が認められたが（両側性狭窄群）、この場合はＭＲＡ所見から病側を決定した。
【００８１】
上記各患者について、術前の安静時およびＡｃｚ投与後のｓＣＢＦとｓＩＲを術後データと比較した。一側性狭窄群（患者１−１０）及び両側性狭窄群（患者１１−１３）のデータをそれぞれ表２から表５に示す。なお、以下の表において、Ａｎｔは図２の部位１を、ＰｒｅＣは部位２を、Ｃｅｎｔは部位３を、Ｐａｒｉは部位４を、Ａｎｇは部位５を、ＰｏＴｅは部位６を、Ｐｏｓｔは部位７をそれぞれ示す。
【００８２】
【表２】

【００８３】
【表３】

【００８４】
【表４】

【００８５】
【表５】

【００８６】
患 者 例
１. ７０歳男性患者（表１及び２の患者１）：
右内頸動脈（ＩＣＡ）に狭窄度９０％の狭窄が偶然発見され、右頸動脈ステント留置術を受けた。図１１から図１４に、術前・術後条件下にみる本患者の安静時およびＡｃｚ投与後の標準化ＳＰＥＣＴ定量像を示す。表６には、術前・術後条件下で、同患者の中央動脈から灌流を受ける領域（図２の部位３）での２８の連続的ＲＯＩにみる安静時およびＡｃｚ投与後ｒＣＢＦデータをまとめた。
【００８７】
【表６】

【００８８】
２. ６９歳男性患者（表１及び２の患者４）：
左ＩＣＡの９９％の狭窄のために左眼に一過性黒内障の症状が認められ、左頸動脈内膜切除術を受けた。術後、前述の症状は寛解した。図１５から図１８に、術前・術後条件下にみる本患者の安静時およびＡｃｚ投与後の標準化ＳＰＥＣＴ定量像を示す。
【００８９】
ＭＣＡ領域全体のｍＩＲ（表１）で比較すると、Ａｃｚ反応性低下（ＩＲ＜１.２０）を術前では、一側性狭窄群（患者１−１０）１０名中８名（患者３−１０）の病側、５名（患者４、６、８−１０）の健側で認め、術後も反応性低下が持続したものはＩＣＡ閉塞を有する２名（患者８、９）の病側のみであった。両側性狭窄群（患者１１−１３）３名では、術前に認められた両側の反応性低下は、術後には全て正常化した。
【００９０】
一方、ｓＩＲで比較すると、一側性狭窄群においては、術前は病側では10名のうち患者１を除く９名、健側でも７名（患者３、４、６−１０）の幾つかのセグメントにＡｃｚ反応性低下を認め、術後も３名（患者８−１０）の病側、２名（８、１０）の健側の幾つかのセグメントでＡｃｚ反応性低下は持続した（表２から表４）。両側性狭窄群では（表５）、３名全ての全部位で術前にＡｃｚ反応性低下が認められ、２名（患者１２、１３）の幾つかのセグメントでＡｃｚ反応性低下は持続した。
【００９１】
ｒＣＢＦ及びｒＩＲで比較すると、例えば患者１では、右の中心動脈灌流域の循環予備能の障害のより詳細な検討が可能であった（表６）。術前では１１〜１６番目のスライスのＡｃｚ反応性低下が明らかとなったが、安静時のｒＣＢＦは、健側がむしろ患側よりもわずかではあるが低値を示した。術後では、両側共にＡｃｚ反応性は著しく改善したが、安静時のｒＣＢＦは、やはり健側が患側よりも低値を示した。これらの所見は、３ＤＳＲＴを重ね合わせたＳＰＥＣＴ定量画像により、視覚的にも明瞭に確認することが可能であった（図１１から図１４）。
【００９２】
３ＤＳＲＴを重ね合わせたＳＰＥＣＴ定量画像による視覚的評価と定量解析の併用により、循環予備能の客観的評価が容易となった。例えば患者４（表１及び３ａ）に示す如く、左大脳半球（図１４および図１５）での術前の広汎な低灌流及び循環予備能の低下と、左頸動脈内膜切除術後の著しい改善（図１６ないし図１７）がきわめて明瞭に示されている。
【００９３】
血行再建術の有効性を評価するために、同じ灌流動脈を共有する血行力学的に関連した部位のｒＣＢＦの加重平均から算出したｓＣＢＦを主として用いた。脳動脈の灌流領域はその広がりや位置が異なっていることが知られており、ｓＣＢＦによる検討は、循環予備能の評価において不適当ではないかと当初は考えられた。しかしながら、血管支配領域の位置と基準面の標準化は、脳循環状態の正確な比較には極めて重要であり、表３から表５に示した術前術後のフォローアップデータから見ても、ｓＣＢＦは脳循環障害の客観的評価に有用である。ｍＣＢＦ値では分からない限局した領域での循環予備能を、ｓＣＢＦ及びｓＩＲに基づいて評価することが可能であるが、更に必要があればｒＣＢＦ及びｒＩＲ値の解析を加えることにより、患者１に示す如く、早期の限局した脳虚血をより正確に評価することが可能である。脳血液量を増加させる脳血管拡張が、脳灌流圧低下に対する自動調節能の最も早期の反応であることから、安静時血流は正常であるが、拡張能が低下している部位を薬剤負荷により検出することは非常に重要である。従って、安静時のｒＣＢＦのみで早期の脳虚血を評価する検討することはミスを招きやすく、不適切である。これに対し、従来はＳＰＭによる統計解析用の単なる予備ステップとしか考えられていなかった解剖学的標準化済画像を、３ＤＳＲＴ法により解析すれば局所脳循環予備能に関する有用で直接的な定量情報を客観的に得ることが可能となった。
【００９４】
従来、ＲＶＲ法を行えば、安静時及びＡｃｚ負荷後のｒＣＢＦ ＳＰＥＣＴ画像を短時間で非侵襲的に得ることは可能であった。しかしながらＲＯＩの形状、サイズ及び位置の微妙な変化に伴って得られるＩＲ値にばらつきが生じるため、ＩＲ値による循環予備能の検討は当初の予想以上に困難であった。また、血行再建術前後での同一被験者における比較は、たとえ一人の被験者であっても異なる日時で得られたＳＰＥＣＴ画像に同一のＲＯＩを設定することは不可能なため更に困難であった。
【００９５】
本発明者は、ＲＶＲ法ではＳＰＥＣＴ撮像時の頭部の位置は不変であり、Ａｃｚ負荷後のＳＰＥＣＴ画像も安静時と同一の解剖学的位置座標を有しているため、ＳＰＭで安静時画像に適用したものと同じ移動パラメータで解剖学的標準化を行うことが可能であることに着眼し、安静時及びＡｃｚ負荷後の解剖学的標準化済画像に３ＤＳＲＴ法を適用することにより、術前・術後の循環予備能を客観的に評価することを可能とし、従来のＲＯＩ設定では解決できなかった観察者間、被験者間および被験者内での変動を解消した。
【００９６】
【発明の効果】
以上述べてきたように、本発明における３ＤＳＲＴ方法によれば、従来手動で行なわれていた臓器に関する関心領域の設定を客観的に３次元的にさらには自動的に実施し、精度の高い関心領域検出が可能となった。また、本法によって数値データによる脳内循環状態の評価が定量的だけでなく視覚的にも容易に可能となるほか、さらに、本法によって術前・術後の循環予備能を客観的に評価することが可能となり、従来のＲＯＩ設定では解決できなかった観察者間、被験者間および被験者内での変動を無くすことが可能となり、診断の便利に資するのみだけでなく、検出された関心領域に関して正確な診断を実施する事が出来る。
【図面の簡単な説明】
【図１】 解剖学的標準脳から画像化データを得るための原点およびＸ、Ｙ座標およびスライス番号の方向を示す図面。
【図２】 ３ＤＳＲＴを示す図面である。図中、各数字は区別される区域を示す。１から８の８つの区域は、脳動脈の同じ分枝から灌流を得ている皮質灌流領域（１は前大脳動脈の脳梁辺縁動脈、２は中大脳動脈（ＭＣＡ）の中心前動脈、３はＭＣＡの中心動脈、４はＭＣＡの頭頂動脈、５はＭＣＡの角回動脈、６はＭＣＡの側頭動脈、７は後大脳動脈、８は前大脳動脈の脳梁周囲動脈）を示す。また、９はレンズ核、１０は視床、１１は海馬であり、１２は小脳半球を示す。
【図３】 ＲＶＲ法のプロトコールを示す図面である。
【図４】 アルツハイマー病患者（５３歳女性）の３ＤＳＲＴによる安静時の解剖学的標準化済ｒＣＢＦ ＳＰＥＣＴ定量画像である。
【図５】 図４のＳＰＥＣＴ定量画像の一部（右上側１２枚）について、３ＤＳＲＴを組み合わせないもの（Ａ）と、組み合わせたもの（Ｂ）を対比した図面。
【図６】 アルツハイマー病患者（７３歳女性）の３ＤＳＲＴによる安静時の解剖学的標準化済ｒＣＢＦ ＳＰＥＣＴ定量画像である。
【図７】 アルツハイマー病患者（５１歳女性）の３ＤＳＲＴによる安静時の解剖学的標準化済ｒＣＢＦ ＳＰＥＣＴ定量画像である。以上図４、図６および図７の３図においては、一次感覚運動野の血流が保持されている特徴が両側で認められる。
【図８】 深部灰白質に限局した病変を有する８２歳女性（左被殻梗塞）の３ＤＳＲＴによる安静時解剖学的標準化済ｒＣＢＦ ＳＰＥＣＴ定量画像である。
【図９】 深部灰白質に限局した病変を有する６３歳男性（右視床梗塞）の３ＤＳＲＴによる安静時解剖学的標準化済ｒＣＢＦ ＳＰＥＣＴ定量画像である。
【図１０】 深部灰白質に限局した病変を有する５１歳男性（ＣＯ中毒）の３ＤＳＲＴによる安静時解剖学的標準化済ｒＣＢＦ ＳＰＥＣＴ定量画像である。以上３図においては、それぞれ、左被殻、右視床及び両側淡蒼球の血流低下部位が３ＤＳＲＴの輪郭と良好に一致している。
【図１１】 表１の患者１の、３ＤＳＲＴを重ね合わせた手術前、安静時の解剖学的標準化済脳血流定量ＳＰＥＣＴ画像である。
【図１２】 表１の患者１の、３ＤＳＲＴを重ね合わせた手術前、Ａｃｚ投与後の解剖学的標準化済脳血流定量ＳＰＥＣＴ画像である。
【図１３】 表１の患者１の、３ＤＳＲＴを重ね合わせた手術後、安静時の解剖学的標準化済脳血流定量ＳＰＥＣＴ画像である。
【図１４】 表１の患者１の、３ＤＳＲＴを重ね合わせた手術後、Ａｃｚ投与後の解剖学的標準化済脳血流定量ＳＰＥＣＴ画像である。以上４図から、右の一次感覚運動野内のスライス１１〜１６における循環予備能の術前の低下および術後の著しい改善が観察された。
【図１５】 表１の患者４の、３ＤＳＲＴを重ね合わせた手術前、安静時の解剖学的標準化済脳血流定量ＳＰＥＣＴ画像である。
【図１６】 表１の患者４の、３ＤＳＲＴを重ね合わせた手術前、Ａｃｚ投与後の解剖学的標準化済脳血流定量ＳＰＥＣＴ画像である。
【図１７】 表１の患者４の、３ＤＳＲＴを重ね合わせた手術後、安静時の解剖学的標準化済脳血流定量ＳＰＥＣＴ画像である。
【図１８】 表１の患者４の、３ＤＳＲＴを重ね合わせた手術後、Ａｃｚ投与後の解剖学的標準化済脳血流定量ＳＰＥＣＴ画像である。以上４図から、左大脳半球での術前の広汎な低灌流および循環予備能の低下（図１４および１５）と左頸動脈内膜切除術後の改善（図１６および１７）が観察された。
以 上[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an image-related data processing method using a medical image obtained by photographing an organ in a body, and more specifically, image-related data that is divided into a plurality of regions of an organ and performs imaging to display the status of each region. The processing method.
[0002]
[Prior art]
In recent years, with the advance of medicine, there has been a remarkable progress in diagnostic imaging. An imaging diagnostic machine (X-ray CT, magnetic resonance imaging device (MRI), ultrasound diagnostic machine, radiological diagnostic machine) to capture the state of the body as an image without imposing a heavy burden on patients etc. Is indispensable in the current medical field. Image diagnosis using them is widely used as providing functional information such as early diagnosis of diseases, selection of treatment methods, prediction and determination of treatment effects, and the like.
[0003]
In the field of nuclear medicine clinical practice, single photon emission computed tomography (SPECT) and positron using a radioisotope (RI) into the patient's body and using gamma rays emitted therefrom Emission tomography (PET) is used by using each apparatus.
[0004]
In such a medical image processing apparatus, various programs are prepared so that various image processing such as image reconstruction and image analysis can be performed from collected data.
[0005]
In addition, a region of interest (ROI) is set in an image, and a statistic for the region of interest is calculated. For example, each part of the brain is set as a region of interest in a SPECT image obtained by photographing the head, and an average value or standard deviation of pixel values in each part of the brain is calculated and used for brain diagnosis. It has been broken. In addition, a left ventricular region is set as a region of interest in a SPECT image obtained by imaging the heart, and an average value or standard deviation value of pixel values in the left ventricular region is calculated and used for diagnosis of the heart. . In addition, a renal function test is performed in which an image taken using the kidney as a region of interest is analyzed using the renogram method.
[0006]
More recently, the brain image data of each patient is converted to the standard brain coordinate system standard brain chart, and then compared with the brain image database of normal subjects to more accurately and objectively identify the site of blood flow or metabolic decline. At present, it is being applied to clinical practice as a standard brain coordinate system statistical analysis method.
[0007]
Specifically, by matching each patient's brain image to the shape of a standard brain that can “identify anatomical positions by coordinates”, multiple brain images of different shapes are treated the same, and Comparison between each patient can be performed between the same pixels (three-dimensional voxels). Furthermore, it has become possible to objectively extract abnormal sites using a statistical analysis method by comparing the images of each patient with a normal database.
[0008]
As such a method, SPM method (Statistical Parametric Mapping) and 3D-SSP method (Three-Dimensional Stereotactic Surface Projections) are known, and these are active regions on PET images and functional magnetic resonance imaging (fMRI) images. Has been developed for the purpose of detecting cerebral blood flow, and has since been applied to the analysis of regional cerebral blood flow in SPECT images.
[0009]
The above technique is described in detail in the following documents, for example.
▲ 1 ▼ Friston KJ, Holmes AP, Worsely KJ, et al: Statistical parametric
maps in functional imaging; A general linear approach.Human
Brain Mapping 2: 189-210 (1995)
▲ 2 ▼ Minoshima S, Koeppe RA, Frey KA, et al: Stereotactic PET atlas of
the human brain; Aid for visual interpretation of functional
brain images. J Nucl Med 35: 949-954 (1994)
▲ 3 ▼ Minoshima S, Frey KA, Koeppe RA, et al: A diagnostic approach in
Alzheimer's disease using three-dimensional stereotactic surface
projections of fluorine-18-FDG PET.J Nucl Med 36: 1238-1248
(1995)
▲ 4 ▼ Clinical Psychiatry Course S10 Diagnostic imaging in psychiatry (Nakayama Shoten)
[0010]
[Problems to be solved by the invention]
By the way, in the region-of-interest method, since the shape of each part differs depending on the patient, it is difficult to set the region of interest at exactly the same location when comparing the degree of accumulation at a certain part between different patients. There was a possibility of comparing different sites. Therefore, even the same analyst has a problem that the result is different by reanalyzing. That is, since the analyst subjectively sets the region of interest, it is difficult to set the anatomically correct position, and there is a risk of erroneous diagnosis only by different image analysts. This made it difficult to directly compare changes over time in a series of diagnosis / treatment flows of the same patient. Furthermore, since it is necessary to set a region of interest for each patient, it is practically impossible to set a detailed region of interest for the entire brain. There was a problem that it was not possible to evaluate.
[0011]
In addition, the standard brain coordinate system statistical analysis method analyzes all pixels (or voxels) of the image compared to the region of interest method, so that the entire brain can be targeted, and the difference in the results of the analysts There is an advantage that is not. However, when considering application in clinical diagnosis, there is a problem that this method is an n-to-1 statistical analysis using a plurality of normal data and one patient data. That is, in the case of the above method, it is necessary to collect a plurality of normal data and construct a standard brain database, which is the most important factor. However, it is ethically difficult to collect brain function image data of normal persons with unified diagnostic imaging equipment, collection conditions, and processing methods for each age and gender, and it is very difficult because it has an economic burden. There was a problem that it was impossible in ordinary facilities and general clinical hospitals.
[0012]
Therefore, it solves the problems of the above-mentioned region method and standard brain coordinate system statistical analysis method, and displays the state of each region in the organ objectively and accurately even for different individual organs (brain, heart, etc.) There was a need to develop possible methods.
[0013]
[Means for Solving the Problems]
As a result of earnest research to solve the above problems, the present inventor determined a region to be distinguished in the organ based on the standard organ atlas, and the region was subjected to a certain imaging process. It is possible to display the state of the target site in the organ without individual differences by combining and processing the image data in the range predicted to be shown as the boundary and the image data standardized after imaging. The present invention has been completed.
[0014]
That is, the present invention is an image-related data processing method for distinguishing and displaying a target region in an organ by an imaging processing device,
(1) Based on the standard organ atlas, determine the areas to be distinguished in the organ,
(2) Determine the boundary of the region to be distinguished determined in (1) so as to synchronize with the imaging processing conditions, obtain region boundary data,
(3) Imaging the organ to be observed to obtain observation data,
(4) The observation data is converted into data by anatomical standardization to obtain standardized data.
(5) The standardized data and the region boundary data acquired in (2) are processed in combination, and the state of the target part in the organ is displayed.
An image-related data processing method is provided.
[0015]
The present invention also provides an image-related data processing method for distinguishing and displaying a target site in an organ by an imaging processing apparatus,
(1) Based on the standard organ atlas, determine the areas to be distinguished in the organ,
(2) Determine the boundary of the region to be distinguished determined in (1) so as to synchronize with the imaging processing conditions, obtain region boundary data,
(3) Imaging the organ to be observed to obtain observation data,
(4) The region boundary data obtained in (2) is converted into corrected region boundary data using the inverse operation for the operation used to convert the observation data into standard data by anatomical standardization.
(5) The observation data and the corrected region boundary data acquired in (4) are processed in combination to display the state of the target part in the organ.
An image-related data processing method is provided.
[0016]
Furthermore, the present invention provides a program for causing a computer to execute the image-related data processing.
[0017]
DETAILED DESCRIPTION OF THE INVENTION
The method of the present invention is an image-related data processing method for distinguishing and displaying a target site in an organ from others using an imaging processing device. As an imaging processing device used in the present invention, In addition to single photon emission computed tomography (SPECT) and positron emission tomography (PET) using radiation, X-ray CT, magnetic resonance imaging (MRI), ultrasound diagnosis and the like are included.
[0018]
As a method for distinguishing and displaying a target site in an organ by using these imaging processing devices, for example, an organ having a three-dimensional structure is represented as a plurality of images such as a tomographic image, and the plurality of images are displayed. In general, there is a method that can grasp the internal state of an organ from the image of the image, that is, a method of expressing one organ two-dimensionally with a plurality of images, but is not limited to this, for example, numerical information before imaging or You may display by processing this.
[0019]
In addition, to display the target part separately from others, for example, the target part is surrounded by a line in the captured image, or the image of an unnecessary part is deleted from the captured image. This means that a part to be displayed is displayed or only a specific part is emphasized.
[0020]
The method of the present invention includes the following steps:
(1) Based on the standard organ atlas, determine the areas to be distinguished in the organ,
(2) Determine the boundary of the region to be distinguished determined in (1) so as to synchronize with the imaging processing conditions, obtain region boundary data,
(3) Imaging the organ to be observed to obtain observation data,
(4) The observation data is converted into data by anatomical standardization to obtain standardized data.
(5) The standardized data and the region boundary data acquired in (2) are processed in combination, and the state of the target part in the organ is displayed.
Including image related data processing method (hereinafter referred to as “first aspect method”),
(1) Based on the standard organ atlas, determine the areas to be distinguished in the organ,
(2) Determine the boundary of the region to be distinguished determined in (1) so as to synchronize with the imaging processing conditions, obtain region boundary data,
(3) Imaging the organ to be observed to obtain observation data,
(4) The region boundary data obtained in (2) is converted into corrected region boundary data using the inverse operation for the operation used to convert the observation data into standard data by anatomical standardization.
(5) The observation data and the corrected region boundary data acquired in (4) are processed in combination to display the state of the target part in the organ.
Includes an image-related data processing method (hereinafter referred to as “second mode method”).
[0021]
Since the first aspect method and the second aspect method differ only in (4) stroke and (5) stroke, the first aspect method will be described first, and then the second aspect method will be different from the first aspect method. Will be explained.
[0022]
In carrying out the method according to the first aspect of the present invention, it is first necessary to determine a region to be distinguished in an organ based on a standard organ atlas.
[0023]
Generally, organs are dominated by several arteries, and defects in these arteries cause troubles in each organ part. Therefore, the areas to be distinguished are generally distinguished according to the flow of the arteries. Although it is preferable to select a region, the present invention is not necessarily limited to this.
[0024]
For example, taking the brain as an example, it is preferable to use the standard brain atlas of the brain's stereotaxic coordinate system, Talairach, as the standard organ atlas, and the corpus callosum of the anterior cerebral artery supplying blood to the brain 8 of the peripheral arteries, the central anterior artery of the middle cerebral artery (MCA), the central artery of the MCA, the parietal artery of the MCA, the angular artery of the MCA, the temporal artery of the MCA, the posterior cerebral artery, and the anterior corpus callosum of the anterior cerebral artery It is desirable to set a region to be distinguished for each of the two dominant arteries. Further, if necessary, the lens nucleus, thalamus, hippocampus, bilateral cerebellar hemisphere, etc. in the deep gray matter can be set as regions to be distinguished.
[0025]
In addition to the standard brain atlas of Tarailach, the standard brain atlas includes MNI templates developed at the Montreal Neurological Institute and three-dimensional brain MRI images such as HBA (human brain atlas). It is also possible to use the one created based on. In addition to the arterial control area, the areas to be distinguished include the nerve distribution area distinguished according to the classification of cranial nerves, the anatomical area distinguished by anatomical structure, and the brodmann's area distinguished by cytostructuring (brodmann's area ) Etc. can also be used.
[0026]
Next, for the region to be distinguished in the standard organ atlas set as described above, the boundary of the determined region to be distinguished is determined so as to synchronize with the imaging processing conditions, and region boundary data is acquired.
[0027]
Here, determining the boundary region so as to synchronize with the imaging processing conditions means that each of three-dimensional regions assumed in the organ from a plurality of standard organ atlas displayed on the plane (generally included in the region). This means that the boundary of each region that each region will show will be determined if it is assumed that the actual organ was imaged under the imaging conditions. To do.
[0028]
Specifically, based on a large number of objective regions of interest (ROI) in an organ, the boundaries of each region may be created. For example, in the brain, many ROIs in the cortex and deep gray matter Originally, the boundary of each region is shown by showing these positions on a plurality of images on the assumption that they are imaged under the same conditions (slice thickness, slice angle, pixel size, etc.) as later described imaging. Region boundary data is obtained.
[0029]
On the other hand, an organ to be actually observed is imaged by a conventional method to obtain observation data, and the data is converted into data by anatomical standardization to obtain standardized data.
[0030]
As described above, an apparatus for imaging can use SPECT, PET, X-ray CT, MRI, ultrasonic diagnosis and the like. In addition, data conversion by anatomical standardization of this data is performed in order to eliminate individual differences in organ shapes for each subject. For example, anatomical standardization obtained from known statistical parametric mapping (SPM) Can be done.
[0031]
The standardized data obtained in this way is processed in combination with region boundary data created in synchronization with the imaging process, and displays the state of the target site in the organ.
[0032]
As this processing, image processing is generally used. Specifically, the region boundary data is superimposed on the standardized image data and the belonging region in the standardized image is displayed, and the standardized image data other than the predetermined region boundary data is used. For example, a process of displaying only a region including a target part, a process of emphasizing predetermined region boundary data in standardized image data, and the like. These processes can generally be performed using a computer, but more simply, an image showing a plurality of region boundaries is created from the region boundary data in a manner corresponding to the plurality of images from the standardized image data. It is also possible to create and use this as a template after printing on a plastic sheet, for example, and visually observe the correspondence between the target site on the standardized image and the region boundary. In addition, using standardized data and region boundary data, numerical data before imaging can be used to numerically display the state of the target portion.
[0033]
As a display method as an image, normal transaxial (TRANS AXIAL) display (displayed by a transaxial surface perpendicular to the human body axis), sagittal (SAGITAL) display (perpendicular to the human forehead surface, Formats are displayed in a sagittal plane that is parallel to the body axis), and coronal (CORONAL) display (also referred to as a coronal plane, indicated by a coronal plane that is parallel to both the forehead and body axes). It can be used, and may be displayed not only in two dimensions but also in three dimensions.
[0034]
On the other hand, the implementation of the method of the second aspect may be performed according to the method of the first aspect, but the region boundary data obtained as described above is used to convert observation data into standard data by anatomical standardization. Therefore, it is necessary to display the region of the target region in the organ by processing it in combination with the observation data by using the inverse operation expression for the operation expression.
[0035]
Here, the inverse arithmetic expression with respect to the arithmetic expression refers to an expression where x = 1 / a · X−b / a when the expression for converting observation data into standard data is X = ax + b. Using this inverse operation expression means that the region boundary data derived from the standard organ atlas that has been anatomically standardized is converted into corrected region boundary data corresponding to the subject, and imaging from the subject is performed. This means that it is possible to display the state of the target part in combination with the region boundary data without modifying the image.
[0036]
According to the method of the present invention described above, once the region boundary data corresponding to the standardized image data is acquired, the state of the target part in the organ can be displayed in an arbitrary manner, and the There are no individual differences between subjects in the display.
[0037]
Therefore, the method of the present invention can be conveniently used as an organ imaging method in the field of treatment.
[0038]
In order to easily implement the method of the present invention, a program for executing these procedures on a computer can be used.
[0039]
That is, as a program for preferably carrying out the first aspect method, a program for sequentially executing the following procedures (1) to (4) is preferable.
(1) Create and store region boundary data of regions to be distinguished in a predetermined organ based on the standard organ atlas so as to synchronize with the imaging processing.
(2) Obtain and store observation data by imaging an organ to be observed.
(3) The observation data is converted into data by anatomical standardization and stored as standardized data.
(4) The standardized data and the region boundary data acquired in (1) are processed in combination, and the state of the target part in the organ is displayed as data.
[0040]
Moreover, as a program for preferably implementing the second aspect method, a program for sequentially executing the following procedures (1) to (4) is preferable.
(1) Create and store region boundary data of regions to be distinguished in a predetermined organ based on the standard organ atlas so as to synchronize with the imaging processing.
(2) Obtain and store observation data by imaging an organ to be observed.
(3) The region boundary data obtained in (1) is converted and stored as corrected region boundary data using an inverse operation to the operation used to convert the observation data into standard data by anatomical standardization.
(4) The observation data and the modified region boundary data acquired in (3) are processed in combination to display the state of the target part in the organ.
[0041]
These programs may be recorded on a computer-readable recording medium, or may be incorporated in an imaging processing apparatus such as SPECT, PET, or MRI.
[0042]
【Example】
EXAMPLES Next, although an Example is given and this invention is demonstrated in more detail, this invention is not restrict | limited at all by these Examples.
[0043]
Example 1
Get region boundary data:
First, the structure of the human brain was classified into the following eight anatomical sites based on the perfused artery according to the standard brain atlas of Tarailach, which is a stereotaxic coordinate system. (1) Anterior corpus callosum artery of the anterior cerebral artery, (2) Central anterior artery of the middle cerebral artery (MCA), (3) The central artery of the MCA, (4) The parietal artery of the MCA, (5) The MCA 8 segments of the coronary artery of the angular artery, (6) MCA temporal artery, (7) posterior cerebral artery, and (8) anterior cerebral artery.
[0044]
Next, based on the above classification, the blood vessel dominating area was set with reference to the Brodmann field classification, and area boundary coordinates were created in the cortical area on the standard brain atlas of Tarailach.
[0045]
In addition to the cortical region coordinates created in this way, for the deep gray matter, the branched arteries are intricately distributed, so the (9) lens nucleus, (10) thalamus, (11) Based on each part of the hippocampus, three zones were set in the deep gray matter, and each region coordinate was created.
[0046]
In addition, (12) 22 ROIs were set on both sides of the cerebellar hemisphere, but visually corrected on the anatomical standardized brain. The reason is that it was determined by visual inspection that the conversion formula described later cannot be applied correctly.
[0047]
These region coordinates were created on the Taira Lach standard brain atlas from 1-2 (65 mm) to 11-12 (-36 mm).
The conversion formula between the coordinates of Taira Lach standard brain atlas and anatomical standard brain coordinates,
[0048]
X = 0.45Yt + 53.75 (7)
Y = 0.49Xt + 39.84 (8)
Z = 1.14Zt−0.056Yt + 0.071 (9)
[In the above formula, (Xt, Yt, Zt) represents the coordinates of the Tarailach standard brain atlas, and (X, Y, Z) represents the anatomical standard brain coordinates]
Was converted using
[0049]
By using these equations, the cortical perfusion area of the cerebral artery defined in the Tarailach Standard Brain Atlas and the coordinates of the boundary points that make up each area and cerebellar hemisphere defined in the deep gray matter are obtained. Converted into continuous three-dimensional position coordinates. The three-dimensional position coordinates obtained here were reconstructed equally with respect to the Z axis so as to form 59 two-dimensional slices.
[0050]
Next, in order to perform actual image processing analysis, the obtained coordinates on the anatomical standard brain are converted to coordinates on image software (IPLab: Scanalytic) having a pixel size of 95 × 79 with the origin as shown in FIG. Converted and set 270 ROIs with symmetry on one side.
[0051]
When converting the coordinates on the converted anatomical standard brain into pixels as image data, taking into account that it can be quantified and analyzed with high precision, use rounded approximations, etc., make integers without decimal points, and Z coordinates Was imaged as slice numbers 1 to 59 from the parietal lobe to the cerebellum. This includes (1) the corpus callosum arterial artery of the anterior cerebral artery, (2) the central anterior artery of the middle cerebral artery (MCA), (3) the central artery of the MCA, (4) the parietal artery of the MCA, (5) the MCA The coronal region of the ROI based on each vascular control region of the coronary artery of (6) the temporal artery of the MCA, (6) the temporal artery of the MCA, (7) the posterior cerebral artery, (8) the periapical artery of the anterior cerebral artery, ROI based on each region of nucleus, (10) thalamus and (11) hippocampus in deep gray matter, (12) ROI of bilateral cerebellar hemispheres in each region boundary data (X pixel number, Y pixel number, Z slice number) ). One side of the obtained area boundary data is described below. FIG. 2 shows an image of this region boundary data (hereinafter abbreviated as “3DSRT”).
[0052]
(1) Callosal marginal artery of the anterior cerebral artery
(68,42, 1), (68,39, 1), (19,39, 1), (18,42, 1), (68,42, 2), (68,39, 2),
(19,39, 2), (18,42, 2), (71,43, 3), (71,39, 3), (17,39, 3), (15,43, 3),
(71,43, 4), (71,39, 4), (17,39, 4), (15,43, 4), (71,43, 5), (71,39, 5),
(17,39, 5), (15,43, 5), (74,43, 6), (74,39, 6), (15,39, 6), (13,43, 6),
(74,43, 7), (74,39, 7), (15,39, 7), (13,43, 7), (74,43, 8), (74,39, 8),
(15,39,8), (13,43,8), (76,46,9), (76,39,9), (14,39,9), (13,46,9),
(76,46,10), (76,39,10), (14,39,10), (13,46,10), (78,47,11), (80,39,11),
(13,39,11), (12,47,11), (78,47,12), (80,39,12), (13,39,12), (12,47,12),
(79,47,13), (80,39,13), (12,39,13), (12,47,13), (79,47,14), (80,39,14),
(12,39,14), (12,47,14), (81,47,15), (82,39,15), (12,39,15), (11,47,15),
(81,47,16), (82,39,16), (12,39,16), (11,47,16), (80,53,17), (84,45,17),
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(83,39,24), (89,46,24), (81,59,25), (74,52,25), (60,39,25), (83,39,25),
(90,48,25), (81,59,26), (74,52,26), (62,39,26), (83,39,26), (90,48,26),
(82,60,27), (73,52,27), (65,39,27), (86,39,27), (90,48,27), (82,60,28),
(73,52,28), (65,39,28), (86,39,28), (90,48,28), (86,55,29), (73,52,29),
(65,39,29), (86,39,29), (90,45,29), (86,55,30), (74,52,30), (67,39,30),
(86,39,30), (90,46,30), (88,56,31), (75,53,31), (69,39,31), (87,39,31),
(91,48,31), (88,56,32), (75,53,32), (71,39,32), (87,39,32), (91,48,32),
(91,48,33), (79,47,33), (71,39,33), (89,39,33), (91,48,34), (79,47,34),
(71,39,34), (89,39,34), (89,54,35), (78,53,35), (68,39,35), (89,39,35),
(89,54,36), (78,53,36), (68,39,36), (89,39,36), (88,53,37), (72,54,37),
(79,47,37), (68,39,37), (89,39,37), (88,53,38), (72,54,38), (79,47,38),
(68,39,38), (89,39,38), (86,57,39), (74,53,39), (77,47,39), (66,39,39),
(89,39,39), (86,57,40), (74,53,40), (77,47,40), (66,39,40), (89,39,40),
(86,55,41), (74,49,41), (62,39,41), (89,39,41), (86,55,42), (74,49,42),
(62,39,42), (89,39,42), (88,49,43), (89,39,43), (62,39,43), (62,45,43),
(88,49,44), (89,39,44), (62,39,44), (62,45,44), (87,48,45), (88,39,45),
(61,39,45), (61,45,45), (87,48,46), (88,39,46), (61,39,46), (61,45,46),
(85,48,47), (85,39,47), (63,39,47), (63,45,47), (85,48,48), (85,39,48),
(63,39,48), (63,45,48)
[0053]
(2) Central anterior artery of middle cerebral artery (MCA)
(68,43, 1), (46,43, 1), (47,58, 1), (58,54, 1), (64,51, 1), (68,43, 2),
(46,43, 2), (47,58, 2), (58,54, 2), (64,51, 2), (71,44, 3), (46,44, 3),
(51,59, 3), (60,56, 3), (66,53, 3), (71,44, 4), (46,44, 4), (51,59, 4),
(60,56, 4), (66,53, 4), (71,44, 5), (46,44, 5), (51,59, 5), (60,56, 5),
(66,53, 5), (74,44, 6), (46,44, 6), (54,61, 6), (62,57, 6), (68,53, 6),
(74,44, 7), (46,44, 7), (54,61, 7), (62,57, 7), (68,53, 7), (74,44, 8),
(46,44, 8), (54,61, 8), (62,57, 8), (68,53, 8), (76,47, 9), (50,48, 9),
(57,63,9), (72,55,9), (76,47,10), (50,48,10), (57,63,10), (72,55,10),
(77,50,11), (49,50,11), (57,64,11), (72,56,11), (77,50,12), (49,50,12),
(57,64,12), (72,56,12), (77,50,13), (49,50,13), (57,64,13), (72,56,13),
(79,52,14), (48,52,14), (52,68,14), (62,64,14), (72,60,14), (79,52,15),
(48,52,15), (52,68,15), (62,64,15), (72,60,15), (79,52,16), (48,52,16),
(52,68,16), (62,64,16), (72,60,16), (79,54,17), (49,54,17), (49,71,17),
(64,66,17), (73,60,17), (79,54,18), (49,54,18), (49,71,18), (64,66,18),
(73,60,18), (80,54,19), (50,54,19), (50,70,19), (65,66,19), (73,61,19),
(80,54,20), (50,54,20), (50,70,20), (65,66,20), (73,61,20), (83,56,21),
(63,56,21), (47,60,21), (50,71,21), (67,66,21), (83,56,22), (63,56,22),
(47,60,22), (50,71,22), (67,66,22), (82,57,23), (64,57,23), (50,59,23),
(53,71,23), (72,66,23), (82,57,24), (64,57,24), (50,59,24), (53,71,24),
(72,66,24), (81,60,25), (74,53,25), (53,59,25), (54,72,25), (73,66,25),
(81,60,26), (74,53,26), (53,59,26), (54,72,26), (73,66,26), (82,61,27),
(73,53,27), (54,59,27), (55,72,27), (73,66,27), (82,61,28), (73,53,28),
(54,59,28), (55,72,28), (73,66,28), (86,56,29), (73,53,29), (47,63,29),
(49,73,29), (66,68,29), (79,63,29), (86,56,30), (73,53,30), (47,63,30),
(49,73,30), (66,68,30), (79,63,30), (88,57,31), (75,54,31), (51,63,31),
(51,73,31), (80,64,31), (88,57,32), (75,54,32), (51,63,32), (51,73,32),
(80,64,32), (91,49,33), (79,48,33), (76,56,33), (60,60,33), (60,69,33),
(75,67,33), (86,60,33), (91,49,34), (79,48,34), (76,56,34), (60,60,34),
(60,69,34), (75,67,34), (86,60,34), (89,55,35), (78,54,35), (74,56,35),
(60,60,35), (62,69,35), (76,67,35), (84,60,35), (89,55,36), (78,54,36),
(74,56,36), (60,60,36), (62,69,36), (76,67,36), (84,60,36), (88,54,37),
(76,51,37), (72,55,37), (62,58,37), (64,67,37), (77,67,37), (82,62,37),
(88,54,38), (76,51,38), (72,55,38), (62,58,38), (64,67,38), (77,67,38),
(82,62,38), (86,58,39), (74,54,39), (61,59,39), (64,67,39), (77,68,39),
(82,62,39), (86,58,40), (74,54,40), (61,59,40), (64,67,40), (77,68,40),
(82,62,40), (86,56,41), (77,66,41), (64,60,41), (74,50,41), (86,56,42),
(77,66,42), (64,60,42), (74,50,42), (85,56,43), (77,65,43), (67,62,43),
(64,53,43), (85,56,44), (77,65,44), (67,62,44), (64,53,44), (85,56,45),
(76,63,45), (66,62,45), (62,53,45)
[0054]
(3) Central artery of middle cerebral artery (MCA)
(46,58, 1), (45,43, 1), (36,43, 1), (36,58, 1), (46,58, 2), (45,43, 2),
(36,43, 2), (36,58, 2), (37,61, 3), (36,44, 3), (45,44, 3), (50,59, 3),
(44,61, 3), (37,61, 4), (36,44, 4), (45,44, 4), (50,59, 4), (44,61, 4),
(37,61, 5), (36,44, 5), (45,44, 5), (50,59, 5), (44,61, 5), (41,65, 6),
(36,44, 6), (45,44, 6), (53,61, 6), (48,64, 6), (41,65, 7), (36,44, 7),
(45,44,7), (53,61,7), (48,64,7), (41,65,8), (36,44,8), (45,44,8),
(53,61,8), (48,64,8), (42,66,9), (37,51,9), (42,48,9), (49,48,9),
(56,64, 9), (50,66, 9), (42,66,10), (37,51,10), (42,48,10), (49,48,10),
(56,64,10), (50,66,10), (42,69,11), (40,50,11), (48,50,11), (56,66,11),
(42,69,12), (40,50,12), (48,50,12), (56,66,12), (42,69,13), (40,50,13),
(48,50,13), (56,66,13), (41,70,14), (41,52,14), (47,52,14), (51,68,14),
(41,70,15), (41,52,15), (47,52,15), (51,68,15), (41,70,16), (41,52,16),
(47,52,16), (51,68,16), (41,71,17), (41,54,17), (48,54,17), (48,71,17),
(41,71,18), (41,54,18), (48,54,18), (48,71,18), (43,73,19), (43,54,19),
(49,54,19), (49,70,19), (43,73,20), (43,54,20), (49,54,20), (49,70,20),
(43,57,21), (46,57,21), (49,72,21), (43,73,21), (43,57,22), (46,57,22),
(49,72,22), (43,73,22), (44,57,23), (49,57,23), (52,72,23), (43,73,23),
(44,57,24), (49,57,24), (52,72,24), (43,73,24), (47,74,25), (45,58,25),
(52,58,25), (53,72,25), (47,74,26), (45,58,26), (52,58,26), (53,72,26),
(49,74,27), (47,61,27), (53,58,27), (54,72,27), (49,74,28), (47,61,28),
(53,58,28), (54,72,28)
[0055]
(4) Parietal artery of middle cerebral artery (MCA)
(34,58, 1), (37,43, 1), (18,43, 1), (24,55, 1), (34,58, 2), (37,43, 2),
(18,43, 2), (24,55, 2), (36,61, 3), (35,44, 3), (15,44, 3), (26,57, 3),
(36,61, 4), (35,44, 4), (15,44, 4), (26,57, 4), (36,61, 5), (35,44, 5),
(15,44, 5), (26,57, 5), (40,65, 6), (35,44, 6), (13,44, 6), (24,59, 6),
(40,65, 7), (35,44, 7), (13,44, 7), (24,59, 7), (40,65, 8), (35,44, 8),
(13,44, 8), (24,59, 8), (41,66, 9), (36,51, 9), (41,48, 9), (13,48, 9),
(19,58,9), (30,64,9), (41,66,10), (36,51,10), (41,48,10), (13,48,10),
(19,58,10), (30,64,10), (41,69,11), (39,50,11), (12,50,11), (20,59,11),
(29,65,11), (41,69,12), (39,50,12), (12,50,12), (20,59,12), (29,65,12),
(41,69,13), (39,50,13), (12,50,13), (20,59,13), (29,65,13), (40,70,14),
(40,52,14), (12,52,14), (20,63,14), (29,67,14)
[0056]
(5) Angular artery of the middle cerebral artery (MCA)
(40,70,15), (40,52,15), (12,52,15), (20,63,15), (29,68,15), (40,70,16),
(40,52,16), (12,52,16), (20,63,16), (29,68,16), (40,71,17), (40,57,17),
(27,54,17), (20,63,17), (29,70,17), (40,71,18), (40,57,18), (27,54,18),
(20,63,18), (29,70,18), (42,73,19), (42,59,19), (26,56,19), (20,64,19),
(29,70,19), (42,73,20), (42,59,20), (26,56,20), (20,64,20), (29,70,20),
(42,73,21), (42,59,21), (26,56,21), (18,64,21), (29,70,21), (42,73,22),
(42,59,22), (26,56,22), (18,64,22), (29,70,22)
[0057]
(6) Temporal artery of middle cerebral artery (MCA)
(42,73,23), (43,63,23), (26,55,23), (19,65,23), (29,71,23), (42,73,24),
(43,63,24), (26,55,24), (19,65,24), (29,71,24), (46,74,25), (44,63,25),
(26,56,25), (20,65,25), (29,71,25), (46,74,26), (44,63,26), (26,56,26),
(20,65,26), (29,71,26), (48,74,27), (46,63,27), (26,56,27), (20,65,27),
(29,71,27), (48,74,28), (46,63,28), (26,56,28), (20,65,28), (29,71,28),
(48,74,29), (46,63,29), (27,59,29), (20,67,29), (31,72,29), (48,74,30),
(46,63,30), (27,59,30), (20,67,30), (31,72,30), (50,73,31), (50,63,31),
(36,64,31), (27,59,31), (20,67,31), (31,73,31), (50,73,32), (50,63,32),
(36,64,32), (27,59,32), (20,67,32), (31,73,32), (59,72,33), (59,61,33),
(43,63,33), (27,59,33), (20,67,33), (35,75,33), (59,72,34), (59,61,34),
(43,63,34), (27,59,34), (20,67,34), (35,75,34), (57,72,35), (54,61,35),
(43,63,35), (27,59,35), (20,67,35), (35,74,35), (57,72,36), (54,61,36),
(43,63,36), (27,59,36), (20,67,36), (35,74,36), (57,70,37), (55,58,37),
(43,63,37), (29,60,37), (25,71,37), (40,74,37), (57,70,38), (55,58,38),
(43,63,38), (29,60,38), (25,71,38), (40,74,38), (59,70,39), (53,59,39),
(43,63,39), (29,60,39), (25,71,39), (40,75,39), (59,70,40), (53,59,40),
(43,63,40), (29,60,40), (25,71,40), (40,75,40), (55,72,41), (58,61,41),
(46,62,41), (37,64,41), (26,60,41), (23,70,41), (33,75,41), (55,72,42),
(58,61,42), (46,60,42), (37,62,42), (26,60,42), (23,70,42), (33,75,42),
(55,72,43), (58,61,43), (46,60,43), (37,62,43), (26,60,43), (23,70,43),
(33,75,43), (64,65,44), (57,57,44), (49,58,44), (41,60,44), (26,72,44),
(42,74,44), (52,71,44), (64,65,45), (57,57,45), (49,58,45), (41,60,45),
(26,72,45), (42,74,45), (52,71,45), (63,62,46), (56,57,46), (50,59,46),
(43,60,46), (33,73,46), (45,73,46), (58,71,46), (63,62,47), (56,57,47),
(50,59,47), (43,60,47), (33,73,47), (45,73,47), (58,71,47), (64,61,48),
(57,55,48), (51,55,48), (34,73,48), (48,73,48), (59,70,48), (64,61,49),
(57,55,49), (51,55,49), (34,73,49), (48,73,49), (59,70,49)
[0058]
(7) Posterior cerebral artery
(26,54,17), (19,48,17), (10,48,17), (13,57,17), (19,63,17), (9,39,18),
(9,47,18), (12,56,18), (19,63,18), (26,54,18), (19,47,18), (22,39,18),
(9,39,19), (9,48,19), (12,56,19), (19,64,19), (25,56,19), (19,47,19),
(22,39,19), (9,39,20), (9,48,20), (12,56,20), (19,64,20), (25,56,20),
(19,47,20), (22,39,20), (9,39,21), (9,48,21), (12,57,21), (17,64,21),
(25,56,21), (20,47,21), (22,39,21), (9,39,22), (9,48,22), (12,57,22),
(17,64,22), (25,56,22), (20,47,22), (22,39,22), (8,39,23), (8,48,23),
(12,58,23), (18,65,23), (25,55,23), (21,47,23), (23,39,23), (8,39,24),
(8,48,24), (12,58,24), (18,65,24), (25,55,24), (21,47,24), (23,39,24),
(7,39,25), (7,49,25), (12,59,25), (19,65,25), (25,55,25), (22,47,25),
(24,39,25), (7,39,26), (7,49,26), (12,59,26), (19,65,26), (25,55,26),
(22,47,26), (24,39,26), (6,39,27), (6,49,27), (12,59,27), (19,65,27),
(25,56,27), (22,47,27), (24,39,27), (6,39,28), (6,49,28), (12,59,28),
(19,65,28), (25,56,28), (22,47,28), (24,39,28), (5,39,29), (5,50,29),
(11,59,29), (19,67,29), (26,59,29), (22,47,29), (24,39,29), (23,39,30),
(5,39,30), (5,50,30), (11,59,30), (19,67,30), (26,59,30), (22,47,30),
(5,39,31), (5,51,31), (11,59,31), (19,67,31), (26,59,31), (22,47,31),
(23,39,31), (5,39,32), (5,51,32), (11,59,32), (19,67,32), (26,59,32),
(22,47,32), (23,39,32), (5,39,33), (4,41,33), (4,50,33), (10,60,33),
(19,67,33), (26,59,33), (18,48,33), (29,53,33), (38,53,33), (38,44,33),
(31,44,33), (20,41,33), (5,39,34), (4,41,34), (4,50,34), (10,60,34),
(19,67,34), (26,59,34), (18,48,34), (29,53,34), (38,53,34), (38,44,34),
(31,44,34), (20,41,34), (5,39,35), (4,41,35), (4,52,35), (10,60,35),
(19,67,35), (26,59,35), (18,48,35), (34,55,35), (39,55,35), (39,44,35),
(34,45,35), (20,44,35), (5,39,36), (4,41,36), (4,52,36), (10,60,36),
(19,67,36), (26,59,36), (18,48,36), (34,55,36), (39,55,36), (39,44,36),
(34,45,36), (20,44,36), (2,41,37), (2,52,37), (11,62,37), (24,71,37),
(28,60,37), (20,50,37), (35,55,37), (40,55,37), (40,46,37), (35,46,37),
(20,44,37), (5,39,37), (2,41,38), (2,52,38), (11,62,38), (24,71,38),
(28,60,38), (20,50,38), (35,55,38), (40,55,38), (40,46,38), (35,46,38),
(20,44,38), (6,39,38), (2,41,39), (2,52,39), (11,62,39), (24,71,39),
(28,60,39), (37,56,39), (42,57,39), (41,47,39), (37,47,39), (29,48,39),
(23,45,39), (5,39,39), (2,41,40), (2,52,40), (11,62,40), (24,71,40),
(28,60,40), (37,56,40), (42,57,40), (41,47,40), (37,47,40), (29,48,40),
(23,45,40), (5,39,40), (2,41,41), (2,52,41), (11,63,41), (22,70,41),
(25,60,41), (46,58,41), (46,50,41), (40,47,41), (32,49,41), (23,50,41),
(18,39,41), (5,39,41), (2,41,42), (2,52,42), (11,63,42), (22,70,42),
(25,60,42), (46,58,42), (46,50,42), (40,47,42), (32,49,42), (23,50,42),
(18,39,42), (5,39,42), (2,41,43), (2,52,43), (11,63,43), (22,70,43),
(25,60,43), (46,58,43), (46,50,43), (40,47,43), (32,49,43), (23,50,43),
(18,39,43), (5,39,43), (2,41,44), (2,52,44), (11,63,44), (25,72,44),
(41,59,44), (49,57,44), (49,47,44), (41,48,44), (39,52,44), (26,57,44),
(19,39,44), (5,39,44), (2,41,45), (2,52,45), (11,63,45), (25,72,45),
(41,59,45), (49,57,45), (49,47,45), (41,48,45), (39,52,45), (26,57,45),
(19,39,45), (5,39,45), (50,46,46), (38,53,46), (24,60,46), (29,71,46),
(32,73,46), (43,59,46), (50,58,46), (50,46,47), (38,53,47), (24,60,47),
(29,71,47), (32,73,47), (43,59,47), (50,58,47), (50,46,48), (34,72,48),
(51,54,48), (50,46,49), (34,72,49), (51,54,49)
[0059]
(8) Artery around the corpus callosum of the anterior cerebral artery
(65,47,17), (65,39,17), (11,39,17), (10,47,17), (20,47,18), (23,39,18),
(65,39,18), (65,47,18), (20,47,19), (23,39,19), (65,39,19), (65,47,19),
(20,47,20), (23,39,20), (67,39,20), (67,47,20), (21,47,21), (23,39,21),
(70,39,21), (70,47,21), (21,47,22), (23,39,22), (70,39,22), (70,47,22),
(22,47,23), (24,39,23), (42,39,23), (42,47,23), (22,47,24), (24,39,24),
(42,39,24), (42,47,24), (23,47,25), (25,39,25), (36,39,25), (36,47,25),
(23,47,26), (25,39,26), (36,39,26), (36,47,26), (23,47,27), (25,39,27),
(35,39,27), (35,47,27), (23,47,28), (25,39,28), (35,39,28), (35,47,28),
(23,47,29), (25,39,29), (35,39,29), (35,47,29), (23,47,30), (24,39,30),
(35,39,30), (35,47,30), (23,47,31), (24,39,31), (35,39,31), (35,47,31),
(35,39,32), (24,39,32), (23,47,32), (35,47,32)
[0060]
(9) Lens core
(53,47,30), (45,52,30), (49,53,30), (58,50,30), (53,47,31), (45,52,31),
(49,53,31), (58,50,31), (55,46,32), (45,53,32), (50,54,32), (57,52,32),
(61,49,32), (55,46,33), (45,53,33), (50,54,33), (57,52,33), (61,49,33),
(54,43,34), (44,53,34), (47,54,34), (50,54,34), (55,53,34), (59,51,34),
(62,49,34), (54,43,35), (44,53,35), (47,54,35), (50,54,35), (55,53,35),
(59,51,35), (62,49,35), (54,43,36), (44,53,36), (47,54,36), (50,54,36),
(55,53,36), (59,51,36), (62,49,36), (54,43,37), (44,53,37), (47,54,37),
(50,54,37), (55,53,37), (59,51,37), (62,49,37), (54,43,38), (48,50,38),
(44,54,38), (47,54,38), (52,53,38), (56,52,38), (59,51,38), (62,49,38),
(54,43,39), (48,50,39), (44,54,39), (47,54,39), (52,53,39), (56,52,39),
(59,51,39), (62,49,39), (54,44,40), (51,47,40), (48,50,40), (45,54,40),
(49,54,40), (52,53,40), (55,52,40), (59,51,40), (62,49,40), (60,45,40),
(57,44,40), (54,44,41), (51,47,41), (48,50,41), (45,54,41), (49,54,41),
(52,53,41), (55,52,41), (59,51,41), (62,49,41), (60,45,41), (57,44,41)
[0061]
(10) Thalamus
(43,43,27), (43,49,27), (50,47,27), (51,44,27), (43,43,28), (43,49,28),
(50,47,28), (51,44,28), (40,45,29), (40,49,29), (43,51,29), (53,45,29),
(53,43,29), (51,41,29), (43,41,29), (40,45,30), (40,49,30), (43,51,30),
(53,45,30), (53,43,30), (51,41,30), (43,41,30), (40,44,31), (40,49,31),
(43,51,31), (53,45,31), (54,42,31), (51,40,31), (43,41,31), (40,44,32),
(40,49,32), (43,51,32), (53,45,32), (54,42,32), (51,40,32), (43,41,32),
(40,42,33), (40,50,33), (43,50,33), (49,46,33), (52,41,33), (50,40,33),
(43,41,33), (40,42,34), (40,50,34), (43,50,34), (49,46,34), (52,41,34),
(50,40,34), (43,41,34), (41,45,35), (41,50,35), (44,50,35), (51,44,35),
(51,41,35), (44,42,35), (41,45,36), (41,50,36), (44,50,36), (51,44,36),
(51,41,36), (44,42,36), (41,45,37), (41,50,37), (44,50,37), (51,44,37),
(51,41,37), (44,42,37)
[0062]
(11) Hippocampus
(38,44,33), (38,53,33), (29,53,33), (31,44,33), (38,44,34), (38,53,34),
(29,53,34), (31,44,34), (39,44,35), (39,55,35), (34,55,35), (34,45,35),
(39,44,36), (39,55,36), (34,55,36), (34,45,36), (40,46,37), (40,55,37),
(35,55,37), (35,46,37), (40,46,38), (40,55,38), (35,55,38), (35,46,38),
(41,47,39), (42,57,39), (37,56,39), (37,47,39), (41,47,40), (42,57,40),
(37,56,40), (37,47,40), (46,50,41), (40,47,41), (32,49,41), (37,58,41),
(46,58,41), (46,50,42), (40,47,42), (32,49,42), (37,58,42), (46,58,42),
(46,50,43), (40,47,43), (32,49,43), (37,58,43), (46,58,43), (49,47,44),
(49,57,44), (41,59,44), (39,52,44), (41,48,44), (49,47,45), (49,57,45),
(41,59,45), (39,52,45), (41,48,45), (50,46,46), (50,58,46), (43,59,46),
(38,53,46), (50,46,47), (50,58,47), (43,59,47), (38,53,47), (51,54,48),
(50,46,48), (34,72,48), (51,54,49), (50,46,49), (34,72,49)
[0063]
(12) Cerebellar hemisphere
(39,51,49), (28,50,49), (19,40,49), (9,39,49), (4,45,49), (15,54,49),
(24,60,49), (34,62,49), (39,51,50), (28,50,50), (19,40,50), (9,39,50),
(4,45,50), (15,54,50), (24,60,50), (34,62,50), (39,51,51), (28,50,51),
(19,40,51), (9,39,51), (4,45,51), (15,54,51), (24,60,51), (34,62,51),
(39,51,52), (28,49,52), (19,40,52), (12,40,52), (8,47,52), (15,55,52),
(24,60,52), (34,64,52), (39,51,53), (28,49,53), (19,40,53), (12,40,53),
(8,47,53), (15,55,53), (24,60,53), (34,64,53), (40,51,54), (27,53,54),
(22,48,54), (22,39,54), (15,39,54), (8,46,54), (16,61,54), (28,67,54),
(37,68,54), (40,51,55), (27,53,55), (22,48,55), (22,39,55), (15,39,55),
(8,46,55), (16,61,55), (28,67,55), (37,68,55), (40,51,56), (27,53,56),
(22,48,56), (22,39,56), (15,39,56), (8,46,56), (16,61,56), (28,67,56),
(34,68,56), (40,51,57), (27,53,57), (22,48,57), (22,39,57), (15,39,57),
(8,46,57), (16,61,57), (28,67,57), (34,68,57), (40,51,58), (27,53,58),
(22,48,58), (22,39,58), (15,39,58), (8,46,58), (16,61,58), (28,67,58),
(34,68,58), (40,51,59), (27,53,59), (22,48,59), (22,39,59), (15,39,59),
(8,46,59), (16,61,59), (28,67,59), (34,68,59)
[0064]
Example 2
(1) Imaging by SPECT:
According to the method collectively shown in FIG. 3 (RVR method), half the amount of labeled technetium-99m-L, L-ethylcysteinate dimer (99mTc-ECD) (600 MBq / 3 mL) supplied in 3 mL per syringe (1. 5 mL) was intravenously injected as a bolus and RI angio was performed. Using a dual-head SPECT system (Prism 2000XP, Marconi, Ohio, USA) equipped with a high-resolution parallel-hole collimator, 99mTc-ECD flowing from the aortic arch to the brain for 120 seconds immediately after administration Monitoring was performed at 1 second intervals (magnification 1.0).
[0065]
The ROI was manually set on the aortic arch and both cerebral hemispheres, and brain perfusion was performed from the time activity curve by the method of Matsuda et al. (Eur. J. Nucl. Med. 1992; 19: 195-200). The index (BPI) was calculated. Then, BPI was converted and the CBF average value (mCBF) at rest was calculated.
[0066]
Seven minutes after the completion of RI angio, SPECT imaging was performed in a 64 × 64 format (magnification 1.33) using Prism 2000XP high-resolution fan beam collimator for 20 seconds for each angle in 30 ° steps. . Collection time was 12 minutes.
[0067]
Ten minutes before the completion of the first SPECT imaging, 1 g of acetazolamide (Acz) was intravenously administered to the patient, and the remaining amount of 99mTc-ECD (1.5 mL) was administered simultaneously with completion of imaging. Nine minutes later, the second SPECT imaging was performed under the same collection conditions as at rest without changing the position of the subject's head and the camera at all. In order to obtain projection data after Acz administration, the first SPECT data is subtracted from the second SPECT data obtained by multiplying 1.041 which is a correction coefficient for attenuation of 99mTc between the first and second SPECT data. Data after time and Acz loading were obtained and reconstructed by backprojection using a Ramp filter, followed by a Butter-worth filter (order 8, cut-off 0.26). Furthermore, after performing absorption correction using the Chang method (correction coefficient: μ = 0.09), the body axis cross-sectional image was reconstructed so as to be parallel to the orbital ear canal line. Pixel size and slice thickness are 4.5mm each ² And 4.5 mm.
[0068]
In order to calculate mCBF after Acz administration, two consecutive slices including the basal ganglia were added to create a reference slice (slice thickness: 9.0 mm). The average SPECT count of the reference slice at rest and after Acz loading is calculated from the ROI including all gray matter, white matter, and ventricles, and Lassen's linearization correction algorithm (α = 2.59) was used to calculate mCBF after Acz loading.
[0069]
99mTc-ECD SPECT qualitative images at rest and after Acz loading and respective mCBFs using Lassen's linearization correction algorithm (α = 2.59) at rest and after Acz loading ^99m Tc-ECD SPECT quantitative images were created.
[0070]
(2) Anatomical standardization:
For the calculation of rCBF (local cerebral blood flow), a MATLAB-based SPM99 (MathWorks, Massachusetts) operating on Windows 98 was used, and at rest and cerebral blood flow SPECT quantitative images at rest after Az administration Anatomical standardization using a standardization algorithm of 12 parameters (rigid body, zoom and affine) set in the cerebral blood flow SPECT qualitative image was performed.
[0071]
For proper color display of anatomically standardized quantitative images, pixels that have more than 90 values of cerebral blood flow SPECT quantitative images at rest and after Acz administration before applying standardization Pretreatment to replace all 90 was added. Thereafter, anatomical standardization was performed in exactly the same manner as described above.
[0072]
(3) Quantitative display of anatomical standardized SPECT images:
After applying the pre-processing, by adding several pixels having a value of 90 to the corners of each slice of these images, the maximum value of each slice is made all the same as 90, and then 10 to 90 are performed in 8 steps. The same color table divided evenly was applied to all of these to perform color display.
[0073]
Example 3
Verification of anatomical accuracy of 3DSRT
(1) Examination in Alzheimer's disease patients:
In order to examine the accuracy of 3DSRT set for the superficial cortex, eight resting SPECT quantitative images (five women, three men, age range 51-85 years) were evaluated. Subjects were patients diagnosed with “probable Alzheimer's disease” according to the diagnostic criteria of NINCDS / ARDRA (Neurology 1984; 34; 939-944). As a result of superimposing 3DSRT on the anatomically standardized resting SPECT quantitative image, the position where the blood flow in the MCA central artery perfusion region, which is the region corresponding to the primary sensorimotor region, is retained, and the region 3 in FIG. It was confirmed that the positions of the ROIs coincided exactly. FIG. 4, FIG. 6 and FIG. 7 show a part of the results (three persons). Moreover, about the part of FIG. 4, the case where 3DSRT is not used and the case where it uses is compared (FIG. 5). Since the drawings attached to the present specification are monochrome and difficult to see, the SPECT images (colors) shown in FIGS. 4 and 6 to 18 are submitted separately as reference drawings.
[0074]
(2) Examination in patients with local lesions in gray matter:
In order to examine the accuracy of 3DSRT set for deep tissue, 7 resting SPECT quantitative images (3 women, 4 men, age range 54-80 years) were evaluated. Subjects were patients with lesions limited to the lens nucleus or thalamus (3 putamen infarcts, 3 thalamic infarcts, 1 CO poisoning). As a result of superimposing 3DSRT on the anatomically standardized resting SPECT quantitative image, it was confirmed that the low blood flow site, which is a lesion, and the position of the corresponding ROI of 3DSRT exactly matched. FIGS. 8 to 10 show a part of the results (three persons).
[0075]
(3) Conclusion
The most important perfusion site for examining whether anatomical standardization is properly performed is the central arterial perfusion region of the middle cerebral artery. This region exists on many slices but is all small, and even if there is a slight misalignment, it is fatal to the quantitative result of rCBF. From this point of view, the position of the primary sensorimotor region in an anatomically standardized SPECT image of an Alzheimer's disease patient was evaluated this time. It is well known that this site maintains blood flow regardless of the stage of Alzheimer's disease (J. Nucl. Med. 1995; 36: 690-696, J. Nucl. Med. 1996; 37: 1159-1165, Brain imaging in Alzheimer's disease. Lippincott Williams &Wilkins; 1999: 67-93). Since the ROI position of the primary sensorimotor area in 3DSRT and the region where the perfusion is characteristically maintained on the standardized cerebral blood flow SPECT images (FIGS. 4, 6, and 7) are well matched, The accuracy of 3DSRT was confirmed. Even in patients with a lesion site limited to the deep gray matter region, the ROI position and the blood flow reduction site on the standardized cerebral blood flow SPECT image (FIGS. 8 to 10) show the same good agreement as the superficial site. It was shown that the blood flow value of each ROI at rest by 3DSRT, the reliability of “Regional CBF (rCBF)”, both deep and superficial sites.
[0076]
Example 4
Evaluation of cerebrovascular reserve capacity before and after surgery using 3DSRT method
In order to analyze the reactivity to Acz, “CBF after Acz administration / CBF at rest” is defined as “Increment Ratio (IR)”, IR corresponding to mCBF is defined as mIR, and IR corresponding to rCBF is defined as rIR. The IR corresponding to the segmental CBF calculated from the weighted average of the rCBFs of the ROIs constituting the ROI was defined as the segmental IR (sIR). The IR threshold for normal response to Acz was 1.20.
[0077]
Revascularization (13 superficial temporal arteries (STA) -MCA anastomosis, 4 carotid endarterectomy, 3 carotid stenting) (2 women, 11 men, age) Followed up (range 51-70 years).
[0078]
In Table 1 below, in addition to clinical symptoms, MRI findings, magnetic resonance angiography (MRA) findings, the area-weighted average of mCBF and mIR values of the entire cortex region (2-6 sites in FIG. 2) perfused from MCA Show about.
[0079]
[Table 1]

[0080]
Transient cerebral ischemic attack (TIA) or reversible cerebral ischemic neuropathy (RIND) was the subject of analysis, and those with clear infarct were excluded, but the pit state (lacuna) was the subject of analysis. Local unilateral stenosis was observed in 10 (1 female, 9 males, age range 51-70 years) (unilateral stenosis group). The remaining three (1 female, 2 males, age range 63-70 years) had stenosis on both sides (bilateral stenosis group). In this case, the diseased side was determined from MRA findings.
[0081]
For each of the above patients, sCBF and sIR at rest before surgery and after Acz administration were compared with postoperative data. The data of the unilateral stenosis group (patient 1-10) and the bilateral stenosis group (patient 11-13) are shown in Table 2 to Table 5, respectively. In the table below, Ant is the site 1 in FIG. 2, PreC is the site 2, Cent is the site 3, Pari is the site 4, Ang is the site 5, PoTe is the site 6, and Post is the site 7. Respectively.
[0082]
[Table 2]

[0083]
[Table 3]

[0084]
[Table 4]

[0085]
[Table 5]

[0086]
Patient example
1. 70 year old male patient (patient 1 in Tables 1 and 2):
A stenosis with a degree of stenosis of 90% was accidentally found in the right internal carotid artery (ICA), and a right carotid artery stenting was performed. 11 to 14 show standardized SPECT quantitative images at rest and after Acz administration of the patient under pre- and post-operative conditions. Table 6 summarizes the rCBF data at rest and after Acz administration in 28 consecutive ROIs in the region (site 3 in FIG. 2) perfused from the central artery of the patient under pre- and post-operative conditions. It was.
[0087]
[Table 6]

[0088]
2. 69 year old male patient (patient 4 in Tables 1 and 2):
Due to 99% stenosis of the left ICA, the left eye had transient cataract symptoms and underwent left carotid endarterectomy. After surgery, the above symptoms were ameliorated. 15 to 18 show standardized SPECT quantitative images at rest and after Acz administration of the patient under pre- and post-operative conditions.
[0089]
Compared with the mIR of the entire MCA region (Table 1), Acz reactivity decreased (IR <1.20) preoperatively, 8 out of 10 (patient 3-10) in the unilateral stenosis group (patient 1-10) ) On the diseased side, 5 (patients 4, 6, 8-10) on the healthy side, and only the diseased side of 2 patients (patients 8 and 9) with ICA occlusion continued to have decreased responsiveness after surgery Met. In the bilateral stenosis group (patients 11-13), the bilateral decreased responsiveness observed before surgery was all normalized after surgery.
[0090]
On the other hand, when compared by sIR, in the unilateral stenosis group, some of 9 patients excluding patient 1 out of 10 patients on the disease side and 7 patients (patients 3, 4, 6-10) on the healthy side before surgery. Decreased Acz responsiveness was observed in these segments, and the reduced Acz responsiveness persisted in several segments on the diseased side of 3 (patients 8-10) and 2 (8, 10) on the healthy side (Table). 2 to Table 4). In the bilateral stenosis group (Table 5), Acz responsiveness decline was observed preoperatively in all 3 sites, and Acz responsiveness persisted in several segments of 2 subjects (patients 12 and 13).
[0091]
Compared with rCBF and rIR, for example, in Patient 1, a more detailed study of impaired circulatory reserve in the right central arterial perfusion zone was possible (Table 6). Before the operation, the Az reactivity decreased in the 11th to 16th slices. However, the rCBF at rest was slightly lower on the healthy side than on the affected side. After the operation, Az reactivity was remarkably improved on both sides, but the rCBF at rest was still lower on the healthy side than on the affected side. These findings could be confirmed visually and clearly with the SPECT quantitative image superimposed with 3DSRT (FIGS. 11 to 14).
[0092]
By combining visual evaluation and quantitative analysis using SPECT quantitative images superimposed with 3DSRT, objective evaluation of circulatory reserve became easy. For example, as shown in patient 4 (Tables 1 and 3a), preoperative wide hypoperfusion and reduced circulatory reserve in the left cerebral hemisphere (FIGS. 14 and 15) and significant post-carotid endarterectomy The improvement (FIGS. 16-17) is shown very clearly.
[0093]
To assess the effectiveness of revascularization, sCBF calculated from the weighted average of rCBF at hemodynamically related sites sharing the same perfused artery was mainly used. It is known that the perfusion region of the cerebral artery is different in its extent and position, and it was initially thought that the examination by sCBF was inappropriate in the evaluation of the circulatory reserve. However, the standardization of the position of the blood vessel dominating region and the reference plane is extremely important for an accurate comparison of the cerebral circulatory state. Useful for objective assessment of cerebral circulation disorders. It is possible to evaluate the circulatory reserve capacity in a limited area not known from the mCBF value based on sCBF and sIR, but if necessary, it is shown to patient 1 by adding analysis of rCBF and rIR values. Thus, it is possible to more accurately evaluate early localized cerebral ischemia. Because cerebral vasodilation, which increases cerebral blood volume, is the earliest response of autoregulatory capacity to cerebral perfusion pressure drop, resting blood flow is normal, but the area where dilatability is reduced is It is very important to detect by. Therefore, it is easy to make mistakes and it is inappropriate to evaluate early cerebral ischemia using only rCBF at rest. On the other hand, if an anatomically standardized image, which was previously considered only as a preliminary step for statistical analysis by SPM, is analyzed by the 3DSRT method, useful and direct quantitative information on local cerebral circulation reserve is obtained. It became possible to obtain objectively.
[0094]
Conventionally, if the RVR method is performed, it is possible to non-invasively obtain rCBF SPECT images at rest and after Acz loading. However, since the IR values obtained with subtle changes in the shape, size and position of the ROI vary, it is more difficult to examine the circulation reserve based on the IR values than initially expected. In addition, comparison of the same subject before and after revascularization is even more difficult because it is impossible to set the same ROI for SPECT images obtained at different dates even for a single subject.
[0095]
In the RVR method, the position of the head at the time of SPECT imaging is unchanged, and the SPECT image after Acz loading also has the same anatomical position coordinates as at rest. Focusing on the fact that anatomical standardization can be performed with the same movement parameters as those applied to the anatomical standardized image at rest and after Acz loading, the 3DSRT method is applied to Postoperative circulatory reserve was objectively evaluated, and fluctuations between observers, subjects, and subjects that could not be solved by conventional ROI settings were eliminated.
[0096]
【The invention's effect】
As described above, according to the 3DSRT method of the present invention, the setting of the region of interest related to the organ, which has been performed manually in the past, is objectively performed three-dimensionally and automatically, and the region of interest with high accuracy is obtained. Detection became possible. In addition to the quantitative and easy visual evaluation of the cerebral circulatory state using numerical data, this method objectively evaluates pre- and post-operative circulatory reserves. It is possible to eliminate fluctuations between observers, between subjects and within subjects that could not be solved by the conventional ROI setting, which not only contributes to the convenience of diagnosis but also relates to the detected region of interest. Accurate diagnosis can be performed.
[Brief description of the drawings]
FIG. 1 shows the origin and X, Y coordinates and slice number directions for obtaining imaging data from an anatomical standard brain.
FIG. 2 is a drawing showing 3DSRT. In the figure, each number indicates a distinguished area. Eight areas 1 to 8 are cortical perfusion areas that are perfused from the same branch of the cerebral artery (1 is the corpus callosal marginal artery of the anterior cerebral artery, 2 is the central anterior artery of the middle cerebral artery (MCA), 3 is the central artery of MCA, 4 is the parietal artery of MCA, 5 is the angular artery of MCA, 6 is the temporal artery of MCA, 7 is the posterior cerebral artery, and 8 is the periapical artery of the anterior cerebral artery. Further, 9 is a lens nucleus, 10 is a thalamus, 11 is a hippocampus, and 12 is a cerebellar hemisphere.
FIG. 3 is a drawing showing a protocol for the RVR method.
FIG. 4 is an anatomically standardized rCBF SPECT quantitative image of a patient with Alzheimer's disease (53-year-old woman) at rest by 3DSRT.
5 is a drawing comparing a part (A) not combining 3DSRT with a part (B) combined with 3DSRT for a part (12 pieces on the upper right side) of the SPECT quantitative image of FIG. 4;
FIG. 6 is an anatomically standardized rCBF SPECT quantitative image of a patient with Alzheimer's disease (a 73-year-old woman) at rest by 3DSRT.
FIG. 7 is an anatomically standardized rCBF SPECT quantitative image of an Alzheimer's disease patient (51-year-old woman) at rest by 3DSRT. As described above, in FIGS. 4, 6, and 7, the characteristic that the blood flow of the primary sensory motor area is maintained is recognized on both sides.
FIG. 8 is a resting anatomically standardized rCBF SPECT quantitative image by 3DSRT of an 82-year-old woman (left putamen infarction) having a lesion limited to deep gray matter.
FIG. 9 is a resting anatomically standardized rCBF SPECT quantitative image by 3DSRT of a 63-year-old male (right thalamic infarction) having a lesion limited to deep gray matter.
FIG. 10 is a resting anatomically standardized rCBF SPECT quantitative image by 3DSRT of a 51 year old male (CO poisoning) with a lesion limited to deep gray matter. In FIGS. 3A and 3B, the areas of reduced blood flow in the left putamen, right thalamus, and bilateral pallidus are in good agreement with the 3DSRT contours.
FIG. 11 is an anatomically standardized cerebral blood flow quantification SPECT image of patient 1 in Table 1 with 3DSRT superimposed before and after surgery.
FIG. 12 is an anatomically standardized cerebral blood flow quantitative SPECT image before surgery and after Acz administration, with 3DSRT superimposed on patient 1 in Table 1.
FIG. 13 is an anatomically standardized cerebral blood flow quantitative SPECT image of the patient 1 in Table 1 after resting after 3DSRT operation.
FIG. 14 is an anatomically standardized cerebral blood flow quantitative SPECT image after the operation in which 3DSRT is superimposed on patient 1 in Table 1 and after Acz administration. From FIG. 4 above, a decrease in circulatory reserve before surgery and a significant improvement after surgery in slices 11 to 16 in the right primary sensorimotor area were observed.
FIG. 15 is an anatomically standardized cerebral blood flow quantitative SPECT image of patient 4 in Table 1 with 3DSRT superimposed before and after surgery.
FIG. 16 is an anatomically standardized cerebral blood flow quantitative SPECT image before surgery and after Acz administration, with 3DSRT superimposed on patient 4 in Table 1.
FIG. 17 is an anatomically standardized cerebral blood flow quantitative SPECT image of patient 4 in Table 1 after resting after overlaying 3DSRT.
FIG. 18 is an anatomically standardized cerebral blood flow quantitative SPECT image of the patient 4 in Table 1 after surgery with 3DSRT superimposed and after Acz administration. From the above 4 figures, preoperative wide hypoperfusion and decreased circulatory reserve (Figures 14 and 15) and improvement after left carotid endarterectomy (Figures 16 and 17) in the left cerebral hemisphere were observed. .
more than

Claims (19)

An image-related data processing method for distinguishing and displaying a target region of the brain by an imaging processing device,
(1) Based on the standard brain atlas, a plurality of three-dimensional arterial control areas in the brain are defined,
(2) To determine the boundary of each of the three-dimensional arterial control regions to be distinguished as defined in (1) so as to be synchronized with the imaging processing conditions, obtain region boundary data;
(3) Imaging the brain to obtain observation data,
(4) The observation data is converted into data by anatomical standardization to obtain standardized data.
(5) The standardized data and the region boundary data acquired in (2) are processed in combination, and the state of each arterial dominant region is numerically displayed using numerical data before imaging. Image-related data processing method. (6) the standard data, (2) overlapping the acquired area boundary data, a plurality of two-dimensional images, the first of claims, characterized in that to express separated brain to multiple arteries control area image-related data processing method. The image-related data according to claim 1 or 2 , wherein in (5), sCBF (segmental blood flow) is calculated and displayed in the dorsal marginal artery dominant region of the anterior cerebral artery. Processing method. (5) In calculates the sCBF at the center front artery governed region of the middle cerebral artery, the image-related data processing method according to claim paragraph 1 or 2, wherein the display. (5) In calculates the sCBF in the central artery governed region of the middle cerebral artery, the image-related data processing method as in claim 1 or paragraph 2, wherein the display. (5) In calculates the sCBF in parietal artery governed region of the middle cerebral artery, the image-related data processing method as in claim 1 or paragraph 2, wherein the display. (5) In calculates the sCBF in angular times artery governed region of the middle cerebral artery, the image-related data processing method as in claim 1 or paragraph 2, wherein the display. (5) In calculates the sCBF in temporal arteritis control area of the middle cerebral artery, the image-related data processing method as in claim 1 or paragraph 2, wherein the display. In (5), calculates the sCBF in the posterior cerebral artery control area, the image-related data processing method as in claim 1 or paragraph 2, wherein the display. An image-related data processing method for distinguishing and displaying a target region of the brain by an imaging processing device,
(1) Based on the standard brain atlas, a plurality of three-dimensional arterial control areas in the brain are defined,
(2) To determine the boundary of each of the three-dimensional arterial control regions to be distinguished as defined in (1) so as to be synchronized with the imaging processing conditions, obtain region boundary data;
(3) Imaging the brain to obtain observation data,
(4) The region boundary data obtained in (2) is converted into corrected region boundary data by using an inverse operation equation for the operation equation used for converting the observation data into standard data by anatomical standardization ( 5) The observation data and the modified region boundary data acquired in (4) are processed in combination, and the state of each arterial control region is numerically displayed using numerical data before imaging. Image-related data processing method. (6) Observation data, (4) superimposed the obtained corrected area boundary data, in a plurality of 2-dimensional images, according to claim 10 wherein, characterized in that to represent separate the brain to multiple arteries control area The image-related data processing method described. Imaging X-ray CT, single photon emission computed tomography (SPECT), positron emission tomography (PET) or any one of claims paragraph 1 - paragraph 11 performed by magnetic resonance imaging apparatus (MRI) The image-related data processing method described in 1. A computer program for causing a computer to execute the following procedures (1) to (4).
(1) The region boundary data of a plurality of three-dimensional arterial dominating regions in the brain determined in advance based on the standard brain atlas is stored so as to be synchronized with the imaging processing.
(2) Save observation data obtained by imaging the brain .
(3) The observation data is converted into data by anatomical standardization and stored as standardized data.
(4) The standardized data and the region boundary data acquired in (1) are processed in combination, and the state of each arterial dominant region is numerically displayed using numerical data before imaging. 14. The computer program according to claim 13, which causes a computer to further execute the following procedure ( 5 ).
( 5 ) The region boundary data acquired in (1) is superimposed on the standardized data , and the brain is expressed by dividing it into a plurality of arterial control regions in a plurality of two-dimensional images . A computer program for causing a computer to execute the following procedures (1) to (4).
(1) The region boundary data of a plurality of three-dimensional arterial dominating regions in the brain determined in advance based on the standard brain atlas is stored so as to be synchronized with the imaging processing.
(2) Save observation data obtained by imaging the brain .
(3) The region boundary data obtained in (1) is converted and stored as corrected region boundary data using an inverse operation to the operation used to convert the observation data into standard data by anatomical standardization.
(4) The observation data and the modified region boundary data acquired in (3) are processed in combination, and the state of each arterial dominating region is numerically displayed using numerical data before imaging. The computer program according to claim 15 for causing a computer to further execute the following procedure ( 5 ).
( 5 ) The corrected region boundary data acquired in (3) is superimposed on the observation data , and the brain is divided into a plurality of arterial dominating regions in a plurality of two-dimensional images . An imaging processing apparatus realized by causing a computer to execute the computer program according to any one of claims 13 to 16 . 18. The observation data according to claim 17 , wherein the observation data is data generated by X-ray CT, single photon emission computed tomography (SPECT), positron emission tomography (PET), or magnetic resonance imaging (MRI). Imaging processing device.   14. The observation data is data generated by X-ray CT, single photon emission computed tomography (SPECT), positron emission tomography (PET), or magnetic resonance imaging (MRI). The computer program according to any one of items up to 16.

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